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Announcing: Progress Studies Reading Group.

30 августа, 2020 - 16:34
Published on August 30, 2020 10:39 AM GMT

This is cross-posted from the EA forum. https://forum.effectivealtruism.org/posts/JBuWGZzCb9TMHNgHw/announcing-progress-studies-reading-group

Kris Gulati recently began to organize a virtual Progress Studies reading group. Everyone is welcome to attend. The group is organized on the Progress Studies Slack #reading-group channel, and you can find more details there.

Format

If you're unfamiliar with EA- related reading groups this post will help.

We will have a meeting once a week where one person is selected to summarise the designated reading and present that summary to the rest of the group. We then proceed to discuss that topic.

The meeting will last one hour, and most of the readings will be related to topics that are Progress related [Check this list for guidance]. The reading materials will be book chapters or journal articles. However, since this will be mostly be determined by a group vote, informal articles, podcasts, and videos are not unlikely.


Next steps

Next Saturday at 9:00 pm GMT, we will be discussing chapter one of Order Without Design: How Markets Shape Cities by Alain Bertaud, a member of the group will be presenting it, so you don't even have* to read it!*Although, it's a really good book so maybe you should.



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Thoughts on Neuralink update?

30 августа, 2020 - 07:05
Published on August 29, 2020 10:59 PM GMT

Here is the full stream.

I haven't seen LessWrong discuss BCI technology all that much, so I'm curious what some of the people here think about the current SOTA, and whether such devices will eventually be able to live up to their lofty promises.



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microCOVID.org: A tool to estimate COVID risk from common activities

30 августа, 2020 - 02:01
Published on August 29, 2020 11:01 PM GMT

This is a linkpost for a model and web tool (that I and several friends created) to quantitatively estimate the COVID risk to you from your ordinary daily activities:

This website contains three outputs of our work:

1. a web calculator that you can use to calculate your COVID risk (in units of microCOVIDs, a 1-in-a-million chance of getting COVID).

2. a white paper that explains our estimation method. EAs might be particularly interested in the footnotes throughout, and the detailed research sources section.

3. a spreadsheet to compute your COVID risk in more detail and to track your risk over time. EAs might find this more customizable and powerful than the web calculator.


If you have different beliefs than us and would like to use a version of the model that reflects your beliefs rather than ours, you can make modifications to your copy of the spreadsheet, or fork the repository and make a personal copy of the web calculator. We also hope you will submit suggestions, either by emailing us or by making issues or pull requests directly on github.

Our group house has been using this model as the basis of a shared agreement/protocol, based on a budget of 3,000 microCOVIDs per year to spend outside the house (about 58 per week). We know of another group house that (last we heard) was operating on *4* microCOVIDs per week!

We hope this helps you personally live a better pandemic life with more safety and more flexibility.


(also linkposted to EA Forum: https://forum.effectivealtruism.org/posts/MACKemu3CJw7hcJcN/a-tool-to-quantitatively-estimate-the-covid-risk-to-you-from )



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Pong from pixels without reading "Pong from Pixels"

29 августа, 2020 - 22:01
Published on August 29, 2020 5:26 PM GMT

At the beginning of this summer I finished an undergraduate degree in maths and physics and I decided to spend some time preparing for my master’s degree in AI by learning some reinforcement learning (RL). It’s not like there was a whole lot else to do this summer anyway. Before going into this I had done a module on applied ML (which basically consisted of putting data into scikit-learn functions without looking deeply at how they worked) and a general idea of the basic structure of neural networks.

The first part of the post will outline the steps I took in learning ML and RL in case anyone with a similar background is interested, and in the second part I will discuss the challenges of implementing a Deep Q-Network (DQN) algorithm on Pong directly from the original paper. I’ll also compare my approach and experience to the blog post Deep Reinforcement Learning: Pong from Pixels by Andrej Karpathy, which I didn't read until after I'd written my DQN implementation.


Yes, this game was heavily cherry-picked but at least it works some of the time!

Part I - Background

I started by looking at Spinning Up by OpenAI and reading their introduction. While reading it I thought I was understanding it fairly well but when it came time to try the exercises and implement algorithms for myself I realised I had no clue what was going on and decided to take a step back.

I’m always happiest when I understand a topic from the very basics. It’s why I preferred pure maths to applied - you start from the axioms and rarely have to rely on anything that you haven’t proved yourself earlier. For this reason I started reading Sutton and Barto’s Reinforcement Learning: An Introduction (RLAI), a textbook by two of the early big names in RL. I haven’t read any other RL textbooks but I thoroughly enjoyed the style and pacing of this book - plenty of explanation and exercises.

I read RLAI until I reached a section on neural networks (Chapter 9), at which point I switched to Goodfellow’s Deep Learning (DL), a modern classic on (deep) neural networks. I found this book a little harder to follow as there were no exercises and fewer simple examples, but it was very helpful nonetheless.

To ensure that I was understanding, I wrote my own symbol-to-symbol backpropagation code in Python and used it to construct a basic neural net capable of achieving ~90% accuracy on MNIST. I also implemented a couple of different optimisers (SGD with momentum, RMSprop), and a horrifically slow convolutional layer using for-loops. The DL textbook provides enough detail to do all of this, but I checked my results against PyTorch as I went along because working in high dimensions is tricky.

After I'd read to the end of Part II of DL and was happy that I understood the fundamentals of building and training neural networks, I went back to RLAI and read the rest of Part II of that book as well.

It was at this point that I started to stall out a little. I had decided to consolidate what I’d learnt by implementing all the different algorithms on the classic cart-pole benchmark environment (using the incredibly convenient OpenAI Gym). I initially tried using the neural networks that I’d written from scratch myself, and then switched to using PyTorch. I was getting mixed results - often they’d learn but then after achieving a good score for a few dozen episodes would crash and fail miserably. Sometimes they’d take hundreds of episodes to start learning at all. Even still I’m not sure if there were serious bugs in my implementations or if it was just a combination of sensitivity to hyperparameters and high variance methods.

Either way, I was pleased that I had managed to train an agent using the neural network code I’d written from scratch, and decided that I should move on instead of writing the same thing over and over hoping it would be perfect. I needed a new challenge.

Part II - DQN

In deciding what to try next, I read two very useful essays - one about reproducing a Deep RL paper by Matthew Rahtz, and the original Spinning Up essay by Joshua Achiam. Both give very good advice about deep RL experiments in general, and the latter has some specific suggestions of projects to try. I followed Achiam's advice and, as I'd already done REINFORCE, decided to follow the paper Playing Atari with Deep Reinforcement Learning by Mnih et al. For brevity and clarity, I will call the overall algorithm DQN and refer to the Deep Q-Network itself as the Q-net.

I had seen Rahtz and others recommend the blog post Pong from Pixels by Andrej Karpathy. I am generally very reluctant to read tutorials or look at other implementations of the things that I am trying to do because I can’t shake the feeling that it’s too much like ‘cheating’. I think I sometimes take this too far, but I decided I wouldn’t look at that blog post or any other implementations of DQN until after I’d done it myself, and as of writing this section, I have still not read it. In the next subsection I will give my experience of implementing DQN on Pong, and in the one after that I will read Pong from Pixels and evaluate whether I think I learned more doing it my way, or if it would have been better to read it from the start.

My experience

The theory behind DQN is strikingly simple if you are already familiar with Q-Learning (described in section 6.5 of RLAI and countless online tutorials). We simply replace the tabular Q-function with a convolutional neural network that takes a sequence of pixel images as input and update with gradient descent. The biggest difference is that we make use of an experience replay buffer.

When you are doing RL, normally you process each reward as it comes, either immediately after getting it (called online learning) or at the end of the current episode (offline learning). Q-learning is online, and so typically each update is done on the current reward and then that reward is discarded. Therefore each reward is used only once. Online learning also means that all updates to our policy are done only based on its most recent performance, which can for example cause the policy to get stuck always selecting and updating on the same action. If instead rewards are stored along with information about where the reward came from (in an experience replay buffer) then each can be used repeatedly. If we store a big enough buffer of these experiences, then when we randomly sample from this buffer we will get some experiences from when the policy was different, which can help to avoid the issues of correlation between updates and the current policy like getting stuck selecting the same action over and over.

I started by working on the cart-pole environment because it requires a simpler policy and therefore I would be able to see if it was working more easily. Here I ran into a theme that would continue to crop up: most of my time was spent on getting the pieces around the learning algorithm working, rather than the learning algorithm itself. Getting pixel output from the cart-pole environment without it rendering every episode was a bit tricky.

My initial implementation of the experience buffer was lazy but it worked. I’d save every transition (state, action, reward, next state) in full and then just sample the tuples as needed. Each state was built of the four most recent frames (to preserve some notion of velocity), which meant that each individual frame was stored eight times! This used up a tremendous amount of memory and my poor laptop couldn’t handle it once I tried to store 100,000 of these transitions. I reworked it to store each individual frame and references to which frames were needed to reconstruct each state - this saved a lot of memory and meant I could actually run large experiments. I could have saved even more memory by making use of the fact that both cart-pole and Pong only use a few colours, but it worked without that.

I ran DQN for one million frames on the cart-pole environment and it learned! Not perfectly, but it achieved a perfect score of 200 more than any other score and got an average return of 129.

Modifying the code to work with Pong was surprisingly simple, but before I did that I had to set up the environment, where the theme of my time being consumed by learning-adjacent issues continued. I had forgotten that OpenAI Gym already had Pong and I spent over an hour trying to set up the Arcade Learning Environment (ALE) from scratch before finding someone mention the OpenAI implementation in an old issue on ALE’s GitHub page. This was all well and good for my laptop which runs Linux, but when I tried to start a run on my Windows PC it failed and I had to spend more time fixing that.

When it finally came to modifying the code for Pong, all I had to do was change the way pixel images were pre-processed, a couple of parameters in the shape of the neural network, and the available actions. I tailored the code specifically to Pong rather than have it be general like in the paper. I initially had six possible actions but I reduced it to just three - up, down, and do nothing. I also shifted the pixel data so that the background colour was 0 to reduce its effect on the output of the network.

People often say that hyperparameters don’t matter much and that if it’s not working then you’ve probably got a bug. That may be true, but hyperparameters can sometimes make or break an experiment and it can be very difficult balancing a search for bugs that may not be there with tuning hyperparameters and starting numerous lengthy runs. Using an optimiser with an adaptive learning rate can reduce that burden but not eliminate it. As an example, I somehow got it into my head that the original paper had used a discount factor, gamma, of 0.99. I tried a run of one million frames (which took eight hours, done overnight) and got nothing. It did no better than random. I had a suspicion that it was because the discount factor was flattening out any useful information so I tried 0.999 instead. This simple change was enough to train an agent that had clearly learnt to move its paddle in front of the ball and could return it a reasonable amount of the time.

I looked at a benchmark comparison by OpenAI to get an idea of how long I’d need to run DQN for. It looks as if DQN had basically converged on Pong after a million frames. Mine had not, so I tried a longer run of three million frames. To facilitate this I spent a long time writing code that would allow me to pause a run, which I was too afraid to use when it came to it because I was afraid it would subtly break the run. Even after the full three million frames my agent still lost most of the time, but put up a good fight and won fairly regularly. I suspect that with different hyperparameters such as no discount rate and a slightly higher learning rate (and possibly a larger experience buffer, the size of which is also technically a hyperparameter) I could achieve better performance, but I don’t want to get caught in the same trap of repeatedly making small changes to something that basically works.

Overall I learned a lot about the intricacies of implementing a deep RL model and some of the potential failure modes. I spent at least 19 hours working on it, plus all of the tweaking and plotting I did between runs. I’m interested to see now how much time reading Pong from Pixels would have saved me, and if I still think it would have been ‘cheating’.

After reading

I see now that Karpathy’s blog post follows a different path and does not cover DQN. The post is excellent at building intuition for policy gradients and for the RL approach to the credit assignment problem in general. I feel like his post would not be sufficient to solve Pong from scratch without copying his code verbatim. I will admit that I was expecting it to be more in-depth with step by step instructions, but the fault lies with my expectations and not with the post.

I certainly don’t think it would have been ‘cheating’ to read ‘Pong from Pixels’ ahead of time, especially as it uses a policy gradient method rather than a value function one. I would recommend reading it but not being discouraged if you still don’t understand how it works afterwards. Neither his post nor mine gives enough detail to do it all from scratch. However if it does get you interested, in my experience Sutton and Barto’s book is a great place to start.

All my (rather messy) code is available on GitHub. This is my first attempt at a piece of writing like this so if you have any comments on content and/or style please do let me know .



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Meaningful Rest

29 августа, 2020 - 18:50
Published on August 29, 2020 3:50 PM GMT

An exercise: Set a 5 minute timer, and list the things you want to do when you feel tired and low-energy. Then, set another 5 minute timer, and list the things you feel rejuvenated after having done - the things you like doing when low-energy.

If you’re anything like me, these lists are basically disjoint! When I’m tired, I want to compulsively check things - Facebook, email, the news. I want to procrastinate: to compulsively scroll through Reddit, trashy web-fiction, the latest webcomics. But, empirically, after doing this I don’t feel any happier or more energised. Often, I feel even more tired! While the things I feel happy to have done tend to be completely different: going for a walk, meditating, reading a book. Generally, things that involve going outside and getting away from screens. Yet, these are not the things I reflexively reach for when tired. This is both a puzzle (which seems to have a solid neuroscientific basis) and obviously terrible.

This is terrible, because the things I want to do are the default actions - the things that take no activation energy to start, the things I reflexively reach for. And when I’m tired, I lack the willpower to do anything more ambitious, and will just reach for whatever is most available. And this creates a feedback loop - I am tired, so I do the things I want to do, I am not rejuvenated and made more tired, etc. This both consumes a lot of time, and doesn’t even make me happy in the process!

So, this is a problem. And fixing this is a big deal, because being well-rested and high-energy is super important. It’s key to my productivity - when I’m tired, I find it easy to procrastination, fail to make progress, and go in circles of wasted motion. And it’s bad for my happiness - being tired makes me irritated, fatigued, insecure, etc. I’ve noticed significant increases in my overall happiness after making progress on this problem, and related problems like my sleep.

Worse, this combines really badly with my default working style. I have a strong neurotic desire to finish things, and to fixate on my total output rather than time spent working. I’ll often push myself to complete my current task, going well beyond my allocated working time, and not being willing to take a break until I’m done. And in the process, I’ll push myself past the point of strain, and only take a break when I’m feeling drained. And once drained I’ll only do the default things I want to do, be stuck in that loop for a while, and basically be done for the day.

This was one of the examples that helped me clarify the difference between my inner and outer optimiser - the way to maximise global productivity isn’t always to follow the neurotic voice in my head telling me how to maximise productivity in the moment. And I need to learn how to take breaks even when it doesn’t feel necessary, because my intuitions for when rest is and is not necessary are empirically shite.

So, that’s a lot on what the problem is, but what to do about it? My underlying model is that the problem is one of defaults. Most situations in my life have a default response, and that takes no effort to follow. To deviate from the default response, I need to spend a scarce resource - willpower. Being tired is essentially being low on willpower, and the problem is that my default actions when low willpower do not regenerate willpower. (I elaborate far more on this model in this post)

The solution to this is two-fold - learn to take breaks before being completely drained, so I can resist the default and take rejuvenating actions. And lower the activation energy of rejuvenating actions, to shape the default - making them as close to the default as possible.

The mindset of shaping the default is valuable, because it shows that I can’t only do rejuvenating things when I’m really tired, and wait until it feels really necessary. The default is formed by my habits, and the actions that I actually take. When I feel the compulsion to veg out and scroll through my messages, and don’t feel strongly in need of rest, this is still a bad idea. Because I’m not just choosing to veg out once - I’m making it slightly more likely that I’ll fall into this loop every time my future self is tired. I need to do the rejuvenating thing at the times when I do have the energy to choose it, so that it becomes a habit, and it’s easier to do at the times when I lack the energy. Taking breaks, and especially rejuvenating ones, must be a point of principle - something I do for its own sake, rather than because I want to and feel like I need it. Because the latter is not a policy that will generalise to the times when I do need to take a rejuvenating break, and at those times I can’t do anything but my default policy.

I’ve been deliberately vague about exactly what to do, I expect this to vary a lot between people - I recommend brainstorming the things that you feel rejuvenated after doing and building a system such that doing those is the default. But, if it helps, this was my process:

When brainstorming what rejuvenated me, I found that being outside, away from screens, and doing something that felt pleasant and virtuous was the best source of rejuvenation per unit time. And an easy way to do this was to go lie down in my garden for 10 minutes and read a physical book (which also meant I began to actually work my way through my to-read list!). And actually doing this initially had high activation energy - I needed to get up to walk to the garden, there was less of a dopamine rush than checking messages, etc. So, for a week, I made a policy of always doing this during breaks and ensured I stuck to it - locking my phone and blocking distracting websites during breaks, having brief pings at the start and end. And I shaped my environment to make it easier, making sure to always have my current book close to hand. And I didn’t perfectly stick to this, and it took some energy to do. But making it a habit significantly lowered the activation energy, and built positive associations with it, to the point that it now feels way easier. And I don’t stick to it religiously, but it’s now much easier to do when I feel tired.

This is just what worked for me, and I don’t expect this to generalise! But I hope the underlying philosophy behind it does. And even if you can’t come up with a perfect system, aren’t super sure what you find rejuvenating, or find it aversive to imagine sticking to a system while tired, I recommend running the experiment anyway! I find my intuitions for what will and will not work aren’t strongly reliable, and there’s no substitute for just gathering data. And it’s a cheap test - the downside of wasted time is low, while the upside of becoming better at rest is super high! I wasn’t at all convinced that my experiment would work, but in hindsight it was super valuable.

So, are you satisfied that you intrinsically want to do the things that rejuvenate you? Are you satisfied with your energy levels? And if not, what can you do about that?

(In this post, I’ve mostly focused on taking meaningful breaks on a small scale, throughout a work day. I think taking longer breaks is also extremely valuable (and something I suck way more at - advice appreciated!) I highly recommend this post for thoughts on the topic)



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Safe Scrambling?

29 августа, 2020 - 17:31
Published on August 29, 2020 2:31 PM GMT

Status: half-formed thought on a potential piece of an alignment strategy that I've not heard discussed but probably exists somewhere, might just be missing a concept name.

Idea

Any alignment scheme that plans to allow potentially unsafe systems to be trained but then tests their safety before deploying runs the risk of being uncompetitive by requiring the system to be trained many times before a safe system is found.

One solution to this problem is to find ways of 'scrambling' an unsafe system to quickly create many variants of the system. It would require that in some of the new systems, the subsystems that have learned to perform to a high level are retained, or remain sufficiently intact to be retrained far more quickly, without retaining the elements that made the original unsafe.

Has there been much work in this area? I'm not really sure where to start looking, but curious to pursue since it suggests a practical research direction that could be worked on with current systems and plausibly assist alignment proposals.

Thoughts on scrambling as a safety component

Retaining some of the previous structures would be likely to result in the same incentive gradients that led to the development of an unsafe system in the first place, reducing the safety of the system.

More worryingly, it could result in being able to quickly train a variety of unsafe systems, thereby acting as an adversarial attack on whatever safety-checker is in place, so you'd be wary of using such a system unless you were very confident in the robustness of the safety system.

On the other hand, we might expect that if the computation can loosely be decomposed into that which allows good performance in training and that which provides potentially unsafe goals then scrambling might prove an easy way to retrain the offending subsection.

The crux of this would potentially be the extent to which the nature of the non-alignment is bound up with the computation which makes it successful. For example, a reasoner which deduces correct answers indirectly as an emergent property of maximising some non-aligned goal would be difficult to decompose in this way, whereas a system which directly solves the given problem, but only under certain conditions which always hold in the training distribution might be decomposed more easily.

If we were picking functions according to NNs with gradient descent then I would expect this to result in more decomposable functions, at least relative to picking function by more abstract criteria like the universal prior, since gradient descent encourages a learning trajectory where the learner is always directly trying to solve the whole problem, even at an immature stage, making a jump from a direct form to indirect form of solution more difficult, since an indirect form of solution requires a more mature system and creating it would thus require a significant transition in the way in the approach during training.



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Spoiler-Free Review: Death and Taxes

29 августа, 2020 - 16:10
Published on August 29, 2020 1:10 PM GMT

Death and Taxes is a short Tier 3 game, meaning it is a Good game but not universally Worth It or a Must Play. It is a series of discrete choices and has some interesting questions to ask, and I likely will use it as a reference point in the future once I’ve given people a chance to play. People who don’t generally play games should still be good to go here.

The game is on sale for $8.44 on Steam through the 31st.

This is one of those experiences that is best when you know as little information as possible going in, so that’s all I am going to say at this time. Enjoy!



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Please take a survey on the quality/impact of things I've written

29 августа, 2020 - 13:39
Published on August 29, 2020 10:39 AM GMT

If you’ve read anything I’ve written on the EA Forum or LessWrong, I’d really appreciate you taking this brief, anonymous survey. Your feedback is useful whether your opinion of my work is positive, mixed, lukewarm, meh, or negative. And remember what mama always said: If you’ve got nothing nice to say, self-selecting out of the sample for that reason will just totally bias Michael’s impact survey.

Don’t Panic![1]

I plan to use people’s responses as inputs - rather than definitive answers - in my ongoing efforts to plan my career and improve in various ways. And I’ll combine these inputs with a lot of other inputs.

Thus, you shouldn’t feel that this is uncomfortably high-stakes, nor that you should only take the survey if you’re really confident in what you’d say. You can just provide any tentative thoughts you have, and I can be responsible for working out how much weight I should give them, whether and how they should affect my decisions, etc.

(This is a good division of labour, as I know more about myself and the context of my work than you do, but you have the advantage of existing outside of my swirling vortex of alternating imposter syndrome and overconfidence.)

I’ve also added a comment below with more info on why I’m running this survey, but you’re very welcome to answer the survey without reading that comment.

  1. The Douglas Adams reference, not the Coldplay song. ↩︎



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Updates and additions to "Embedded Agency"

29 августа, 2020 - 07:22
Published on August 29, 2020 4:22 AM GMT

Abram Demski and Scott Garrabrant's "Embedded Agency" has been updated with quite a bit of new content from Abram. All the changes are live today, and can be found at any of these links:

Abram says, "I'm excited about this new version because I feel like in a lot of cases, the old version gestured at an idea but didn't go far enough to really explain. The new version feels to me like it gives the real version of the problem in cases where the previous version didn't quite make it, and explains things more thoroughly."

This diff shows all the changes to the blog version. Changes include (in addition to many added or tweaked illustrations)...

Changes to "Decision Theory":

  • "Observation counterfactuals" (discussed in the counterfactual mugging section at the end) are distinguished from "action counterfactuals" (discussed in the earlier sections). Action counterfactuals are introduced before the five-and-ten problem.
  • The introduction to the five-and-ten problem is now slower and more focused (less jumping between topics), and makes the motivation clearer.
  • Instead of highlighting "Perhaps the agent is trying to plan ahead, or reason about a game-theoretic situation in which its action has an intricate role to play." as reasons an agent might know its own action, the text now highlights points from "Embedded World-Models": a sufficiently smart agent with access to its own source code can always deduce its own conditional behaviors.
  • ε-exploration and Newcomblike problems now get full sections, rather than a few sentences each.
  • Added discussion of "Do humans make this kind of mistake?" (Text versions only.)

Changes to "Embedded World-Models":

  • "This is fine if the world 'holds still' for us; but because the map is in the world, it may implement some function." changed to "... because the map is in the world, different maps create different worlds."
  • Discussion of reflective oracles now gives more context (e.g., says what "oracle machines" are).
  • Spend more time introducing the problem of logical uncertainty: emphasize that humans handle logical uncertainty fine (text versions only); say a bit more about how logic and probability theory differ; note that the two "may seem superficially compatible, since probability theory is an extension of Boolean logic"; and describe the Gödelian and realizability obstacles to linking the two. Note explicitly that "the 'scale versus tree' problem also means that we don’t know how ordinary empirical reasoning works" (text versions only).

Changes to "Robust Delegation":

  • Introduction + Vingean Reflection:
    • Introduction expanded to explicitly describe the AI alignment, tiling agent, and stability under self-improvement problems; draw analogies to royal succession and lost purposes in human institutions; and highlight that the difficulty lies in (a) the predecessor not fully understanding itself and its goals, and (b) the successor needing to act with some degree of autonomy. (Text versions only.)
    • Put more explicit focus on the case where a successor is much smarter than its predecessor. (Text versions only.)
    • Expanded "Usually, we think about this from the point of view of the human." to "A lot of current work on robust delegation comes from the goal of aligning AI systems with what humans want. So usually, we think about this from the point of view of the human." (Text versions only.)
  • Goodhart's Law:
    • Expanded discussion of regressional Goodhart, including adding more illustrations and noting two problems with Bayesian estimators (intractability, and realizability). Removed claim that Bayes estimators are "the end of the story" for regressional Goodhart.
    • Moved extremal to come after regressional instead of after causal, so extremal and regressional can readily be compared.
    • Rewrote and expanded extremal Goodhart to introduce the problem more slowly, and walk through quantilizers in much more detail.
    • Expanded discussion of causal Goodhart to clarify connection to decision theory and note realizability issues.
    • Clarified the connection to mesa-optimizers and subsystem alignment in adversarial Goodhart.
  • Stable Pointers to Value:
    • Added following the Goodhart discussion: "Remember that none of these problems would come up if a system were optimizing what we wanted directly, rather than optimizing a proxy."
    • Introduced the term "treacherous turns".
    • Shortened and clarified introduction to observation-utility maximizers, described how observation-utility agents could do value learning, and removed mention of CIRL in this context.
    • Mentioned the operator modeling problem.
    • Discussed wireheading as a form of Goodharting.

Changes to "Subsystem Alignment":

  • "Optimization daemons" / "inner optimizers" are now "mesa-optimizers", matching the terminology in "Risks from Learned Optimization". (Change also made in "Embedded Agents" / the introduction.)
  • New section on treacherous turns, simulated deployments, and time and length limits on programs.


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Objective Dog Ratings: The Irish Wolfhound

29 августа, 2020 - 07:01
Published on August 29, 2020 4:01 AM GMT

Like other sighthounds, Irish wolfhounds are thin, wiry, and not a little bit tall. Indeed, wolfhounds are the tallest of the Tall Dogs. In personality, I have no complaints: they are intelligent, respond well to training, and get along with people so well that they often make terrible guard dogs. They are very unlikely to eat a small child, and that is a definite improvement over the Original Wolf™. 

Unfortunately, wolfhounds look unkempt and scraggly, like they just got out of a week-long bender. This is not a dog which cares about maintaining a professional appearance. They mostly die of bone cancer, which is less the fault of bad genes than of size (other large dogs are also prone to bone cancer), but they also have a predisposition to heart problems which does seem genetic in nature. 

Irish wolfhounds are perfectly adequate dogs, but they need to dress for the job they want, not the job they have, and their numerous genetic bottlenecks (with subsequent inbreeding) are also a cause for concern.

Rating: ★★☆ (Fine)

Original post (w/ more pictures) here.



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Objective Dog Ratings: An Introduction & Explanation

29 августа, 2020 - 06:54
Published on August 29, 2020 3:54 AM GMT

Because they’re not all good dogs, Brent.

Obviously, not everyone wants the same thing from dogs, but that’s not necessarily the same as saying that any dog is as good as the next, or even that any dog rating system must be subjective. If we’re going to entertain the idea that some dogs are simply better than other dogs, though, then we have to specify how that is.

What we’re looking for is a dog with a certain amount of wolfishness, a dog which is as close to being a wolf as one can get without sacrificing any of those essential characteristics which define a dog as such. Basically, a dog which a politically progressive, forward-thinking wolf would not be ashamed to know. They must be loyal, intelligent, and hardworking, they must have a sense of dignity, they must like humans, and above all they must be healthy. A dog which is perfect in every other way, but is unhealthy, is a bad dog, because it would not be good to be that dog. 

Unfortunately, I’m incapable of doing anything without taking it at least a little bit seriously, so ratings will be on a three-star scale, from ★ (Mediocre) to ★★★ (Good). It is also possible that some dogs will not get any stars at all. Those are bad dogs, Bront. 

I do not know which dog breed will turn out to be the dog breed, the dog of the gods, but I do have my suspicions (some breed of spitz-type, probably), and it’s important to note that this has nothing to do with how much I personally like a dog. Some of my favorite dogs will get no more than two stars, and some may even get just one star. This isn’t “Dogs which are the best at sitting in my lap and being petted,” or “Most Instagrammable dogs.” 

Let us begin.



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The Case for Human Genetic Engineering

29 августа, 2020 - 04:33
Published on August 28, 2020 10:21 PM GMT

This is the first post in what I hope will be a series of posts arguing that genetically engineering humans may provide a huge benefit to individuals and society as a whole. In the interest of creating something readable, this post will largely ignore the controversies and unintended consequences of such a project, but I plan to address those in later posts. It will also ignore perhaps the most impactful genetic change of all: increased intelligence. Such a change deserves a post of its own.

A quick disclaimer before I begin: when I first sat down to write a post about genetic engineering, I planned to thoroughly research everything I wrote about and give links to most of the claims I made. While I will do so for what I judge to be the less commonly understood facts presented in this piece, this will not be as thoroughly researched and comprehensive as I originally planned.

As a result, many of the conclusions I draw in this piece will be based on my own incomplete knowledge and are therefore liable to be wrong. If you spot any particularly glaring errors, or if the pacing is off, or if you get too bored and don't finish reading please let me know in the comments. That being said I think I have read enough about this topic to have something worth reading.

Part 1: A Changing World

Human history is a story of accelerating change. The rapid growth in brain size and general intelligence that took place between 3 million and 50,000 years ago enabled the explosion of human populations and power that culminated in our modern globe-spanning civilization. There is still some debate in the field of anthropology about WHY exactly evolution favored larger brain sizes and increased intelligence so consistently for so long. Whatever the reasons were, they must have been very compelling. Relative to resting metabolic rate -- the total amount of calories an animal burns each day just to keep breathing, digesting and staying warm -- the human brain demands more than twice as many calories as the chimpanzee brain, and at least three to five times more calories than the brains of squirrels, mice and rabbits.

This massively increased brainpower had one particularly notable effect: humans became able to communicate via language, a far more flexible and sophisticated form of communication than that used by any other species. This unique ability probably played a fundamental role in the development of agricultural societies, which was the first step in the march towards modern civilization.

The agricultural revolution led to an explosion in the size of the human population, and the industrial and green revolutions lead to a rate of population growth unprecedented in human history. This massive population growth and increased technological sophistication has dramatically altered human lifestyles. For most of human history, individuals lived in groups of at most a few hundred and subsisted off of a combination of hunting, gathering, fishing, and scavenging. This lifestyle gave us many of our current traits including our upright posture, our teeth (which are optimized for eating a combination of meat and plants), our large brain sizes, our penchant for gossip, and many other human characteristics.

When agriculture spread throughout the world beginning around 12,000 years ago at the end of the last ice age, it dramatically altered human lifestyles and diets. Humans began to live shorter less healthy lives, back neck and tooth problems became much more prevalent and diseases began to spread in the dense sedentary societies that sprung up around the world (particularly in Asia and Europe).

In a very real sense, the agricultural revolution made life worse for the average human. But because life was not so bad that sedentary individuals were less likely to pass on their genes, and because agriculture could support far more humans with the same land area, there was no path back. Humans across the planet turned to agriculture not because it provided for a better, happier life, but because they were stuck in a Malthusian trap.

A Genetic Mismatch

The decline in lifespan, decrease in height, increased incidence of bone and joint issues, the rise of cavities, and the spread of infectious diseases that accompanied the agricultural revolution are attributable to a mismatch between human genes and human lifestyles. It is my contention that despite significant improvements in lifespan, sanitation, and food supply, the rapid progress of modern technology is creating a wider and wider gulf between the environment humans evolved to live in and the one in which we find ourselves today.

Humans are quite adaptable, so we have created ways to bridge the gap between these biological needs and the shape of modern living. Gyms and exercise equipment, for example, give people a way to maintain their physical and mental health in the absence of lifestyles that necessitate exercise as a required part of staying alive. But these solutions are extremely sub-optimal: humans now have to spend several hours per week running, swimming, biking and lifting weights for no particular reason other than to maintain health. And while many people might argue that “exercising makes me feel better and look better and live longer” (all true by the way), it is still the case that our ancestors got the same benefits in the process of doing something they had to do anyways (hunting and gathering).

There are many, many other such examples. Tooth issues such as wisdom teeth crowding out other teeth in our jaw, the frequency of cavities and tooth decay are also an example of a problem introduced by a change in our diet that accompanied the agricultural revolution. Frequent back and neck issues are also a result of a mismatch between our ancestral environment and our modern working conditions. Our tendency to focus on gossip about the lives of celebrities whose lives will never impact us is a relic of an ancestral environment in which the only people whose gossip we heard were those in our tribe (about whom it was useful to know gossip). Our preference for sugary foods devoid of essential nutrients are a relic of an era in which such foods were hard to come by and the risk of starvation was a much greater risk to reproductive success than the risk of obesity. And the disproportionate attention we pay to extremely low probability risks like terrorism and violent crime are a relic of an era in which human to human violence was much more common than it is today.

The incredibly high frequency of death from old age represents perhaps the greatest disconnect between the environment our genes were optimized for and the one in which we now live. As explained in this excellent quora post by Dr. Suzanne Sadedin, the average age at which an individual organism from a given species will die is determined by the rate of all-cause mortality in its natural environment. This evolutionary theory of aging, known as the Antagonistic Pleiotropy Hypothesis, is well supported by theoretical models, animal experiments and human correlational studies. The mechanism of action here is a set of genes with a specific characteristic: they increase reproductive fitness at a young age but decrease the window of reproductive opportunity (often by causing health problems at an older age). When all-cause mortality is high, such genes are beneficial as the organism carrying them is likely to have died by the time the downsides become relevant.

So if the antagonistic pleiotropy hypothesis is to be believed, how long would we expect humans to live for if they were genetically optimized for their current environment? Unfortunately, I wasn’t able to find any models predicting lifespan given all-cause mortality rates of a particular species. However, let us compare the mortality rates of hunter-gatherer societies with those of humans living in the developed world to give us a sense of how massive the difference is. Here’s a graph showing mortality rates in various Hiwi hunter-gatherer groups.

Here's another graph showing mortality rates in Canada.

It isn’t even close. The chance of death between the ages of 1 and 5 are somewhere between ten to thirty times lower in modern societies than in hunter-gatherer societies, and even at age 70 mortality rates are still at about a third of the levels they are in hunter-gatherer societies.

It therefore stands to reason that we could substantially increase the human lifespan by opting for genetic variants that give slightly lower reproductive fitness at a young age in exchange for longer life. It also stands to reason that given the low rate of all-cause mortality in modern society, this trade-off would INCREASE reproductive fitness.

There are many more things that were clearly important considerations in the past that are not as important today. For example, the cost of gaining access to more calories is not as high today as it was in the past. Are there genes that increase health or intelligence at the cost of increasing one’s basal metabolic rate? If so, such genes might have been selected against in the past. But with much easier access to calories today, such genes might provide a net benefit. Are there genes that increase intelligence at the cost of a larger fetal skull size? Babies with such genes might not have fit through the birth canal in the past, but we now perform c-sections on a regular basis. The possibilities here seem absolutely enormous and we already have specific examples of genes with trade-offs that don’t make sense anymore. Are there genes that increase the frequency and severity of the stress response, making us better at fighting off predators and other humans at the cost of longevity? If so, perhaps we decrease the expression of such genes to increase lifespan at the cost of not being able to win bar fights or do amazingly well at contact sports. You get the idea.

Part 2: Surpassing Evolution

Evolution works wonders over long timescales, but it is not efficient or even good at maximizing reproductive fitness. As Eliezer Yudkowsky once wrote, “the wonder of evolution is not how well it works, but that it works at all.” Such a process leaves much to be desired. In this section, I will be describing how genetic engineering will allow us to surpass the fitness maximizing constraints imposed by evolution, and by doing so improve the lives of humans and the rest of this planet’s species.

The first limitation I will be discussing is that of the local fitness maxima. One of the most frustrating things about evolution is that it can only make progress one mutation at a time. If gene B only provides a benefit when gene A is already present, gene A must spread through a breeding population before gene B. And if gene A does not by itself provide a reproductive fitness advantage, it becomes nearly impossible for gene B to ever spread. There are some exceptions to this (see Scott Alexander's excellent post on how weak competition can actually lead to increased fitness), but in general, this is the rule.

Genetic engineering opens up the possibility of escaping from the “local fitness maxima” created by this one-step-at-a-time limitation of evolution. I’m going to tell you the story of one of the most promising such interventions I know of: the project to move genes out of the mitochondria and into the nucleus of cells.

MitoSENS: Lending Evolution A Hand

MitoSENS is an ongoing project to address one of the fundamental causes of aging: damage to mitochondrial DNA caused by free radicals.

This story begins 1.45 billion years ago, when, during an unbelievably rare occurrence, a large cell swallowed a small one, the small one survived and multiplied inside the larger one and neither one died. This small cell was special: it was the ancestor of modern mitochondria, and it dramatically increased the amount of energy available to the large cell. This event was a seminal moment in evolutionary history, surpassed in significance perhaps only by the origin of life itself. As best we can tell, it only happened a single time in the 3.5 billion year history of life, and from that single ancestor all eukaryotic organisms (plants and animals) are descended.

For this reason, mitochondria (along with chloroplasts) are the only organelle in eukaryotic cells that can self-reproduce. A legacy of this independent origin story lives on within the membrane of every mitochondrion: 37 genes and 16,569 base pairs which form the last remaining vestiges of an organism that once lived independently in a much larger world.

You might suspect that 37 genes are not nearly enough for any organism to function, let alone reproduce. You would be correct. This was a bit of a mystery to me as well until I learned what evolution has been doing to mitochondrial DNA over the last billion years of evolution: it has been moving DNA out of the mitochondria and into the nucleus.

You see, mitochondria are one of the single biggest sources of free radicals in our bodies. In fact, the free radicals (AKA reactive oxygen species) that are produced by our mitochondria account for the vast majority of free radical damage in an average person’s body. The inside of a mitochondrion is one of the worst places to be if you are a molecule that values your current atomic arrangement. With no nuclear membrane to protect itself, mitochondrial DNA is exposed to the full fury of this onslaught of free radicals produced as a byproduct of ATP synthesis.

So the process of random mutation and natural selection has been hard at work moving genes out of the mitochondria and into the nucleus of the cell. I still haven't found a satisfying explanation of exactly HOW this transfer happens, but some process appears to have been hard at work over the last 1.5 billion years moving genes out of the mitochondria and into the nucleus of the cell. Proteins necessary for mitochondrial function and now produced outside the mitochondria and transported back inside via the TIM-TOM complex, a series of channels in the membranes of each mitochondrion that allow externally manufactured proteins to be moved inside the mitochondrion. This evolutionary process has moved almost all of the 3000 genes of the ancestor of mitochondria into the cell's nucleus. But evolution can only advance one step at a time, and there’s something special about those remaining 37 genes that makes them particularly resistant to evolution’s effort.

Two chief problems appear to be at the root of evolution’s inability to move those remaining genes out of the mitochondria: hydrophobicity and code disparity. Code disparity is a difference in the interpretations of codons in the nucleus and the mitochondria. A codon is a set of 3 base pairs that represent an amino acid or a regulatory signal such as "end of protein". At some point in evolutionary history, the interpretation of four of these codons was switched in the mitochondria. The first of the four that appears to have changed its interpretation is the codon formed by the base pairs UGA. UGA is used to encode a STOP signal (meaning the end of a protein sequence) in nuclear DNA. But some time around 1 billion years ago this codon’s interpretation was switched from being a STOP signal to encoding the amino acid tryptophan in the mitochondria. Once this happened, gene transfer from the mitochondria to the nucleus became significantly harder, because the proteins synthesized from such genes would be truncated at the location of every tryptophan in the structure.

The rest of the paper explaining why no more genes seem to have transferred is quite interesting and can be read here if you’re interested.

This is of importance because mitochondria free radical damage appears to play a critical role in aging via a process called the "Mitochondrial Free Radical Theory of Aging".

A full explanation of the theory is beyond the scope of this post (read chapter 5 page 68 of Aubrey de Grey's book Ending Aging if you want one.) But the shortest version ever is that a small proportion of mitochondria accumulate a specific set of mutations with age that turns the cell in which they reside into toxic waste production facilities. The ATP synthesis process that Mitochondria normally perform is shut down inside such cells, forcing them to turn to another energy production method whose byproduct is superoxide, a dangerous free radical. These free radicals end up colliding with low-density lipoprotein and creating oxidized cholesterol, one of the primary contributors to high blood pressure and heart disease.

I should point out here that the following explanation is not universally accepted. There is at least some criticism of the “Mitochondrial free radical theory of aging” proposed by de Grey, and the issue doesn’t seem quite settled one way or the other. However, given evolution’s long history of moving mitochondrial genes into the nucleus, it seems very likely that there is a fitness advantage to doing so even if a reduction in the rate of aging is not THE specific reason.

Since we know how to translate mitochondrial genes into nucleus-encoded genes by swapping the codons that cause the code disparity, we could engineer nuclear copies of all the genes. Even after the genes inside the mitochondria are damaged, imported proteins would allow the mitochondria to continue functioning, preventing not only a significant portion of aging damage but simultaneously providing a cure for several dozen mitochondrial genetic diseases such as Leber Hereditary Optic Neuropathy (LHON) and Kearns Sayre syndrome. In fact, clinical trials to express the protein that causes LHON in the nucleus are in clinical trials right now

In short, genetic engineering might allow us to permanently fix a significant source of aging damage and genetic disease with no significant downsides.

Promoting Heterozygous Advantage

Sickle cell anemia is an interesting genetic disease. It is caused by a mutation in the gene that codes for the protein hemoglobin, which is responsible for carrying oxygen in the blood. The disease is recessive, meaning only an individual with two copies of the gene will experience disease symptoms. Those suffering from the condition are often wracked with pain, have restricted blood flow to vital organs, and have difficulty performing moderate exercise.

Carriers (people with one normal copy of the gene and one mutated copy) have an interesting advantage not enjoyed by the rest of us: they are notably more resistant to malaria. Other than this, they only seem to have symptoms under extreme dehydration or oxygen deprivation.

Carriers of the sickle cell disease, therefore, have a notable fitness advantage in environments in which a low percentage of the group of available partners are carriers and the risk of death or disability from malaria is high. This is why when we look at maps of the distribution of malaria and the distribution of people who have (or whose ancestors had) sickle cell, they overlap quite nicely.

Ancestral homeland of individuals with sickle cell anemia

Historical range of malaria

Genetic engineering offers us the opportunity to avoid the “overdominance” problem of genetic conditions like sickle cell: we can ensure that EVERYONE in areas where malaria is a major risk has exactly one copy of the sickle cell gene. In other words, we can reach population states that evolution simply cannot.

Avoiding Losses from Zero-Sum Games

I left this example for last because I do not yet have a specific example of this phenomenon in humans, though I suspect that some exist.

Walk into any forest of old trees and you will likely notice that the first hundred feet or so of the trunk are devoid of any branches. In the competition for access to sunlight, trees grow nearly as tall as physiologically possible in an effort to pass the shading branches of their neighbors. While this tendency is a huge boon for lumber companies that take advantage of the long straight trunks to create lumber products at low cost, the trees themselves do not on net benefit from the arrangement. Each tree must invest considerable energy in producing a hundred or more feet of wood whose sole purpose is to elevate its canopy above those of its neighbors.

The forest as a whole is less successful than if all trees were to grow tall enough to spread their canopies fully but no taller. But alas, the trees have no mechanism for punishing uppity young saplings that dare to grow taller than their older neighbors. So all trees are forced to grow tall and the reproductive fitness of the forest as a whole is reduced.

This is a fairly standard example of the prisoner’s dilemma, a phenomenon in which two self-interested entities compete in a game, and both end up losing due to the lack of ability to punish cheaters. If you are not already familiar with the concept I would highly recommend reading the link above as it does a much better job explaining the setup than my one-sentence summary.

Though I don't have any specific examples, there likely exist specific genetic variants that impose a cost and exist solely to allow humans to compete better in zero-sum games. If we are able to identify such variants, it's possible that we could ban humans from having such variants, thus saving everyone from the cost of carrying such traits. Obviously such a scheme would carry some risk and may be rejected by most people as giving the government too much power, but it is nonetheless a benefit that can only be realized through genetic engineering. For that reason, it

Future Posts

I hope to continue this series. I'd like to devote an entire post to the topic of genetically engineering higher intelligence since this would likely be one of the most important things that we would choose to change. I'd also like to discuss HOW this could actually be done via embryo selection, gene-editing tools like CRISPR, and iterated embryo selection.

Let me know what you thought of this post. My goal here is really to create something that's informative and readable. So if this post could use improvement in either of those areas please let me know.



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My guide to lifelogging

29 августа, 2020 - 00:34
Published on August 28, 2020 9:34 PM GMT

I've defended the practice of lifelogging as a means of life extension here. In this post I'll provide a fairly comprehensive guide on how to lifelog. Since lifelogging exists on a spectrum from "taking a picture every so often" to "recording every single detail of your life, in uncompressed HD video along with continuous MRI scans and storage in a nuclear-safe vault" this guide will present two categories for lifelogging, the first for lower cost options and the second higher cost options. "Cost" here refers not only to the monetary price of buying the equipment, but also the convenience costs of setting up the equipment, and storing the data, and perhaps social embarrassment.

Over the last several months I have spent many hours of research to determine the best setups in terms of time and energy required to record my life. I also recommend viewing Mati Roy's setup.

I intend to update this guide as I learn more, so keep in mind that this post is a work-in-progress.

Lower cost lifeloggingArchiving social media

The lowest hanging fruit of lifelogging is probably creating a long-term archive of your social media data. The method of archiving your social media data will necessarily depend on the websites you visit, but here are some guides for common websites:

Keylogging

I do not keylog myself, but Mati Roy has informed me that Spyrix works well.

Taking pictures

These days, smartphones generally have high quality cameras, and are much less of a hassle than buying professional equipment.

Storage

Since everything in the lower cost section here takes up a small amount of space, cloud storage is an appropriate way of storing data for the long-term. Google Drive offers 15 GB of free storage, though I would also suggest storing a local copy of every file along with checking out the subheader on audio and video compression, and the subheader on long-term storage in the section on higher cost lifelogging.

Higher cost lifeloggingScreen recording

The most salient way that I lifelog is by recording everything that happens on my computer screen, along with a full video of my face and room. I achieve this setup by using Open Broadcaster Software (OBS) and record a continuous split-screen between my screen and my USB camera.

I have heard that OBS can be quite annoying to use if you use a laptop, as it turns up the fans and generally uses too much of the CPU. Therefore, I recommend building a computer with a high quality CPU and buying a wide-angle USB camera, along with a USB microphone to record.

The desktop computer I use is five years old, so I cannot recommend the exact parts I bought at the time. I also do not recommend using the USB camera that I bought, as it does not have a wide enough angle for my tastes. Instead, I recommend browsing the subreddits /r/buildapc and /r/buildapcforme until you have a decent idea of what goes into building a computer.

I would estimate the minimum cost of a desktop computer that can reliably run OBS without problems at around $500, if you know what you are doing. But a price tag of $750 may be better if you don't want to run into issues later. This benchmarking site, and this one are useful for determining low cost high quality CPUs. At the moment I suggest getting around a $200 to $300 newest generation AMD Ryzen CPU.

Nighttime recording

The value of recording yourself sleep is arguable, so I do not suggest this to everyone. My own justification was to have a sense of completeness in my lifelogging, and feel like I wasn't ever missing a moment.

That said, I purchased this USB infrared camera to record myself at night, and it works well. It also functions as a day-time camera, automatically switching to infrared when the lights go out, making it suitable as an all-day recording camera. I also purchased this fitness watch to track my sleep, though this aspect is obviously not necessary.

Just as in the above section, I use OBS to facilitate the recording. It's worth understanding how profiles and scene collections work in OBS so that you can simplify your setup.

When I'm not at my desktop

Recording at my desktop is nice, since I can use OBS, but when I'm on-the-go I have two main ways of recording, using audio and video.

Audio

The first method is audio recording using my phone. I have an iPhone at the moment, and therefore I recommend Android users to look at Mati Roy's advice. I purchased this omnidirectional lavalier microphone along with this lightning-to-headphone jack connector, and am generally pleased with the quality.

I use the app Dictaphone, but I'm not confident at all that this app is the best. It was simply the first thing I looked at for IOS.

The lavalier microphone connects to my shirt, sort of like in this picture, and I don't generally have to think about it much when I'm on the go. Of course, I urge potential lifeloggers to make sure that they have the consent of all parties before recording people on-the-go.

In order to save phone battery, I also purchased this voice recorder, which has surprisingly long battery life and acceptable storage. However, I mostly don't use the voice recorder anymore since I have switched to mainly recording video while I'm on-the-go, as I explain in the next section.

Video

If you aren't satisfied with recording audio continuously on-the-go, you can switch to using video. I experimented with purchasing an action camera (ie. what Go Pros are) for this purpose, but then soon realized that there was a better alternative.

I now recommend lifeloggers purchase a body camera, of the type used by police. Here some of the pros and cons of body cams compared to action cameras:

Pros:

  • They generally have much longer battery life (very important)
  • Most have native infrared recording so you can record at night
  • Body cams are built to allow you to easily clip it onto clothing (this makes continuous recording less awkward)
  • They tolerate shock damage, such as dropping the camera, more than many action cameras

Cons:

  • The video quality is lower
  • Fewer features are available
  • There are fewer online resources for operating body cams

After substantial research I decided to buy this body camera. The primary reason I went with it over other cameras was because it had a detachable battery (with an extra), and detachable storage (but you must purchase the SD card on your own). The main downside is that the lens angle is only 140 degrees compared to 170 in some other body cams.

The body cam is well-built and is much lighter in weight than you might expect. It connects easily to my computer via a USB cable that enables me to transfer the video files to long-term storage.

To minimize storage costs, I record in 480p and compress all my files once I have transferred them to my computer (see next section). The body cam allows an option for on-board storage during recording, but I don't use it because it seems to work by simply halfing the bitrate of the video without anything intelligent involved. A similar thing seems to happens when you turn on the option for pre-recording for some reason.

On a full charge I can get over 5 hours for each battery, and it is easy to replace the battery when the body cam dies. With a 128 GB SD card it can hold about 60 hours of continuous 480p quality video before it runs out of space.

I have tried various ways of connecting it to my body, and the thing that seems to work the best is simply connecting the body cam to my pants, or belt, as shown in the image below. Unfortunately, you do have to tuck in your shirt or else the body cam won't be able to see much. On the bright side, this means that if you want to hide that you are wearing a body cam, all you have to do is make sure your shirt covers it.

More downsides of keeping it on your pants include the fact that it doesn’t get people’s faces if you are talking to them and you are close to them, and it doesn't record very well when you are sitting down at a table or sitting more generally.

See this Google Drive video for a sample of the post-compression quality of using the body cam. I think that Google Drive compresses video uploaded there, so make sure to download it to see the real quality, as it's only 21.9 MB.

Audio and video compression

Video takes up a LOT of storage unless you compress. Audio is similar, though less extreme. Therefore, before transferring my files into long-term storage, I always compress them into something of acceptable size.

I use FFmpeg to compress my media files, which works well on Ubuntu, but I have not tried it out on other operating systems. To compress my videos I run this bash script,

#!/usr/bin/env bash

for i in *.MOV;
do name=`echo "$i" | cut -d'.' -f1`
echo "$name"
ffmpeg -i "$i" -c:v libx264 -preset veryslow -crf 24 -strict -2 "${name}.mp4"
done

rm *.MOV

The two most important things to understand about the script above are the options

-preset veryslow

and

-crf 24

These options determine the quality and size of the video. I recommend choosing quality and size depending on your own tolerance for storage costs (see the section on long-term storage below). The the FFmpeg documentation explains these options in more detail,

A preset is a collection of options that will provide a certain encoding speed to compression ratio. A slower preset will provide better compression (compression is quality per filesize). This means that, for example, if you target a certain file size or constant bit rate, you will achieve better quality with a slower preset. Similarly, for constant quality encoding, you will simply save bitrate by choosing a slower preset.Use the slowest preset that you have patience for. The available presets in descending order of speed are ultrafast, superfast, veryfast, faster, fast, medium – default preset, slow, slower, veryslow.[...]The range of the CRF scale is 0–51, where 0 is lossless, 23 is the default, and 51 is worst quality possible. A lower value generally leads to higher quality, and a subjectively sane range is 17–28. Consider 17 or 18 to be visually lossless or nearly so; it should look the same or nearly the same as the input but it isn't technically lossless.The range is exponential, so increasing the CRF value +6 results in roughly half the bitrate / file size, while -6 leads to roughly twice the bitrate.

For audio, I use this command,

find -name "*.WAV" -exec ffmpeg -i {} -acodec libmp3lame -qscale:a 5 -ab 128k {}.mp3 \;Long-term storage

For large amounts of short-term storage, you can visit the website diskprices.com to view the cheapest storage available to consumers. Personally, I recommend getting SSD storage as opposed to HDD storage for short-term use, as even though it is more expensive, it is also much faster.

However, since both SSDs and HDDs are not built to store data for decades without corruption, the best option at the moment is likely burning data onto blu ray discs. You can find cases of 50 blu ray discs that hold 22.5 GB for between $20 to $25. However, the real costs of long-term storage will be higher than this for two reasons,

  • For the long-term, ideally you should keep at least two copies of every file, and you should store them in separate locations.
  • Data burning often fails with a rate of between 10 to 20 percent, which means that your true cost estimates should take into account the fact that many discs will be useless.

I purchased this blu-ray burner, which works acceptably but I'm unsure whether it is the best option. I also purchased a few of these cases which can hold a lot of discs quite cheaply.

I suggest taking a look at a list of best practices for long-term storage on blu-ray discs as compiled by Brian Tomasik. Like him, I am not an expert either, so take this advice with a grain of salt.



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How to teach things well

28 августа, 2020 - 19:44
Published on August 28, 2020 4:44 PM GMT

(This is a post on my thoughts on good teaching techniques from a daily blogging project, that I thought might be of interest to LessWrong readers)

Introduction

This is a blog post on how to teach things well. I’ll mostly be focusing on forms of teaching that involve preparation and structure, like talks and tutoring, but these ideas transfer pretty broadly. I think teaching and explaining ideas is an incredibly important skill, and one that most people aren’t great at. I’ve spent a lot of time practicing teaching ideas, and I think I’ve found a bunch of important ideas and approaches that work well. I’m giving a talk next week, so I’ll initially focus on how to give good talks, but try to outline the underlying concepts and high-level ideas of teaching. And then talk about how these can transfer to contexts like tutoring, and to teaching specifically maths or applied rationality - the main areas I have actual teaching experience with.

Note: I mostly care about teaching concepts and ideas, and teaching things to people who genuinely want to learn and be there, so my advice will focus accordingly.

I think it’s useful to think about good teaching even if you don’t intend to spend much time teaching - learning and teaching are flip sides of the same process. I’ve found that even when in the role of a student, understanding what good teaching looks like can often fix a lot of the shortcomings of a bad teacher!

Framing

The key insight of this post is that good teaching requires you to be deliberate, and keep the purpose in mind: learning is a process of information compression. When you’re learning something new, you essentially receive a stream of new information. But human cognition doesn’t work by just storing a flood of information as is. The student takes in the information stream, extracts out the important ideas, converts it to concepts, and stores those in their mind. This is a key distinction, because it shows that the job of a teacher is not to give the student information, it’s to get the student to understand the right concepts. Conveying information is only useful as a means to an end to this goal.

In practice, it often works to just give a stream of information! Good students have learned the skill of taking streams of information and converting it to concepts. Often this happens implicitly, they student will absorb and memorise a lot of data, and over time this forms into concepts and ideas in their head automatically. But this is a major amount of cognitive labour. And a good teacher will try to do as much it as possible, to let the student focus their cognitive labour on the important things.

My underlying model here is that we all have a web of concepts in our minds, our knowledge graph. The collection of all the concepts we understand, all of our existing knowledge and intuitions, connected together. And you have learned something when you can convert it to concepts and connect it to your existing understanding. This means not just understanding the concept itself, but understanding where it fits into the bigger picture, where to use it, etc.

The final part there is key - if the student leaves with a good understanding of the ideas in the abstract, but no idea when to think about the ideas again, it’s no better than if they’d learned nothing at all. We call on our knowledge when something related triggers, so in order for a lesson to be useful, you need to build those connections and triggers in the student’s mind.

A key distinction to bear in mind is ideas being legible vs tacit. A legible idea is something concrete that can easily be put into unambiguous words, eg how to do integration by parts. While tacit knowledge is something fuzzier and intuitive, eg recognising the kinds of integrals where you’d use integration by parts in the first place - essentially the intuitions you want the student to have. This is a good distinction to bear in mind, because legible knowledge is much easier to convey, but often your goal is to convey tacit knowledge (at least, it should be!). And there’s a lot of skill to conveying tacit knowledge well, and making it as legible as possible without losing key nuance. And different techniques work better for the two kinds. A lot of my issues with the Cambridge maths course is an extreme focus on legible knowledge over tacit - the underlying intuitions and motivations.

How to teach

There are two key problems when teaching, that any good teaching advice must account for:

  • Limited ways to convey information
    • The ideas I’m teaching are stored as implicit concepts in my mind, but in order to convey them, I must translate them into language. This language maps to ideas in my head according to all of my implicit knowledge and worldview, but translates into the student’s head according to their implicit knowledge and worldview. This often creates errors
    • And converting concepts to language is inherently lossy, ideas have a lot of tacit nuance that is hard to capture
    • Essentially, words can only convey legible knowledge, and I need to figure out how to hack this to convey tacit knowledge. Or how to find alternate information channels
    • Alternately, I need to have error checking mechanisms to notice when I’ve failed to convey something well.
  • Typical Mind Fallacy
    • A key part of learning is combining knowledge you hear with the ideas already in your head.
    • But I only have access to what’s in my head, not what’s in the student’s. And by definition this is different - I already understand what I’m teaching!
    • This is a crippling blow to my ability to teach, and I need to be constantly aware of this and trying to build models of what’s in the student’s heads, and how they receive what I’m saying.

Here are some of the most important tools I have for addressing these problems:

  • High-level picture
    • The student’s knowledge graph is big. So the first, and most important part, is identifying which part of the graph they should add these ideas to
    • Thus you should always highlight where this fits in to the bigger picture. Which questions are we currently trying to answer? Why is this idea interesting at all? Where can the student use this? What are its limitations?
    • This should always be the first thing when introducing a new idea
  • Prioritising information
    • Learning is information compression. This fundamentally means that the student needs to be paying selective attention. When learning something new, the Pareto Principle always applies - 80% of the importance lies in 20% of the ideas.
    • Identifying this 20% is significant cognitive labour, because it’s not immediately obvious. They need to pay attention to everything and later filter.
    • But, the question of “what matters here” is tacit knowledge that I already have! This talk is high labour for the student, but easy for me. Thus, the most important thing a teacher can possibly do is to highlight what matters and what doesn’t, to tell the student where to focus their attention.
    • In practice, you should always be saying “this is really, really important” or “these are just fiddly details” or “this is a bit of a niche edge case” etc. It is extremely hard to do this too often.
      • And give more time to the important things. If you say an important point, write it down and put a box around it. Explain why it’s important and how it fits into the bigger picture. Give an alternate explanation, or an example.
      • This is really easy to miss if you think of teaching as information transfer - where your goal is to tell the student everything and hope they figure out what to pay attention to themselves.
    • Another tool: Have frequent summaries, highlighting the key points in the previous section.
      • This is further useful to highlight connections. Some ideas will fit into their knowledge graph more easily than others, and pointing out connections can leverage the easy connections to make hard ones easier
    • I’m a big of the advice “say what you’re going to tell them, tell them, and say what you’ve just told them”, I think it’s a good way to implement this principle
    • The fundamental principle behind this is that students retain a tiny fraction of what they hear. If you give a one hour talk, they’ll retain maybe a few minutes worth of content. This is a fundamental fact of the learning process, and the only thing you can do about it is to control what they retain. Focus their attention on the important parts
      • This mindset helps me identify what’s important. Set a 5 minute timer, and write down everything important that you want people to retain. These are the key points around which your talk should be structured!
      • Everything else you say should be intended to help these key points stick better - to highlight connections between them and to existing knowledge, to ensure good information transfer, and to convey the tacit knowledge underlying the key points
    • Another key skill of prioritisation is cutting things. If one part is irrelevant, or it’s boring and fiddly, cut it! It’s painful to not talk about everything cool, but you have limited time - if you don’t actively prioritise, you aren’t avoiding trade-offs, you’re just ceding control to “whatever you leave last”
      • Anyone who’s gone to a talk by me knows that I have yet to internalise this lesson
    • If there’s one point you retain from this post, let it be this one - this is incredibly important, and the main mark of a good teacher vs a mediocre one
  • Understand pre-requisites
    • A consequence of the Typical Mind Fallacy, is that it’s super easy to forget that your students don’t have all the context you have! This manifests as people teaching ideas without the pre-requisites.
      • The underlying idea: the ideas you teach are in your knowledge graph, and are built upon existing ideas - these are the pre-requisites. You need to figure out whether the students
    • A common secondary mistake is to understand pre-requisites, and then try to explain all of them!
      • A good framing here is inferential distance. The inferential distance of a new idea is the number of steps of new concepts someone must understand before they can understand the new idea. Eg, to teach a young kid about the quadratic formula, they first need to understand the idea of polynomials, for which they need to understand algebra - this is three inferential steps.
      • A general rule of thumb: never teach things with more than 2 inferential steps. An idea just learned is shaky, and doesn’t yet have good connections built. It’s very, very hard to anchor new ideas onto new ideas.
    • This is really hard to get right. Pre-requisites require you to have a good model of somebody else’s mind. A useful technique is often to do a practice run on someone from your target demographic, and ask them to flag everything that confuses them.
    • Further, for groups, this can be an intractable problem, everyone has different prior knowledge. You need to have a clear picture in your head of who the talk is aimed at.
  • Students should learn actively, not passively
    • It’s really easy for a student to just passively sit in a stream of information, taking none of it in. This achieves neither of your goals, because to form connections, compress information and connect it to their knowledge graph, they need to be putting in some cognitive labour.
    • Good ways to encourage this: explicitly telling them that this is important, giving exercises and time to think through them, asking the audience regular questions and giving them some time to think.
      • Question asking has the failure mode where most people won’t volunteer, or just zone out a bit - I lack great solutions to this problem
    • This is much easier to handle in smaller settings, I’m bad at handling it in talks. The main solution I have is just to be engaging and keep the pace going well.
      • Often people will zone out, so having regular breaks, and check-points of “if you weren’t following, we’re changing topic so it doesn’t matter” can help to rectify this
        • Even short, 30s-120s breaks can be helpful! Encourage people to get up and stretch.
        • Breaks never feel important, but they really, really help
  • Give examples
    • Examples are an insanely powerful tool for teaching things well, and people rarely use them enough. I have never given a class with too many examples (and believe me, I’ve tried)
      • “You can teach a class with no content, only examples; you can’t teach a class with only content, no examples”
    • Why examples are awesome:
      • Examples are an excellent way to resolve lossy information transfer - they’re a completely different channel of communication than normal. If nothing else, they serve as an error check
      • Examples are a great way to transfer tacit knowledge, without necessarily making it legible - this is what it means to build intuition
      • Examples can help fit things in to the bigger picture, they can motivate the ideas, and locate where they fit in to the student’s knowledge graph
      • By giving the student a pool of motivating examples, they can often generate the ideas themselves by generalising from the examples
      • Examples can bridge the gap from “understanding the knowledge in the abstract” to “understanding where to use these ideas, and where they should come up”
    • How to use them?
      • Often when giving a point, I’ll give a micro-example to give context to it - eg “sometimes straight lines aren’t enough to model data, eg with a quadratic”. This should be quick and effortless, the example should make immediate sense to the students, with 0 inferential steps
        • (I can’t believe it’s taken me 18 posts to get to my first nested example :( )
      • Examples can be good at the start, to motivate things and show the questions we’re trying to answer. It can be good to give an example, and then constantly refer back to it as we generalise the example into a concept
      • After introducing a complex idea, go through a long example and illustrate which parts of the example embody the complex idea
      • Use examples to illustrate the importance and relateability of an idea - eg if explaining how to think about good planning to students, give an example of a student with a deadline crisis that they missed - everyone relates to this
    • Examples contain a lot of information, so the idea of information prioritisation applies strongly here - tell the students what to pay attention to in the example, and why it’s interesting
  • Visual information and diagrams
    • Often tacit knowledge manifests as a literal picture in my head - draw this!
    • This is another good alternate communication channel
    • Our visual memory and processing is often much better than our abilities with language - this can work well for clarified confusing and complex parts
  • Pacing
    • An easy mistake that I often fall into is to give a section the amount of time it takes me to say it. I convert the ideas into words, and just read through what I’ve come up with.
      • This is the fallacy of viewing teaching as giving an information stream! Time should be allocated for people to process and compress information, and they need more time for hard parts and less time for easy parts
    • This is hard to get right intuitively - when you understand an idea, it feels easy!
    • A good trick: make a high-level summary, and rate each section out of 5 for difficulty. Then go and explicitly give more time to those sections - eg add more intuitions, say the key ideas more, give more examples
      • Note - pacing doesn’t mean the speed at which you speak, it’s about the time you give to different ideas!
      • Note that difficulty =/= importance. If one part is hard, but unimportant, cut it. Or give a brief overview, explain the important idea, and say “don’t sweat the details”
    • Another trick - explicitly tell students which ideas are important and worth paying attention to, and which aren’t
    • If doing a practice run (which you totally should), regularly check in with the test audience about pacing - the default state of the world is that you get pacing wrong
    • It's key to get pacing right - people zone out in slow, easy sections, and get lost in fast, hard sections. Your job as the teacher is to keep as many people as possible absorbing information at the optimum rate.
    • It’s very hard to give accurate time estimates for things - my trick is to have a bonus section at the end which I’ll cut if need be, and to pace in the moment according to my existing notes and my intuitions
  • Understand the mindset behind a question
    • When somebody asks a question, the default response is to answer it. This is a failure to be deliberate! The student asks a question because they’re confused about something, and your goal is to resolve that confusion - answering the question directly is just a means to an end.
      • This is an important distinction, because often questions are weird. They’re confused, or don’t quite make sense, or are asking about unimportant things. This manifests, for me, as the student’s mind not making sense. And it’s easy to get frustrated, or just to answer the dumb question directly. But this is ineffective.
        • A related effect - somebody asks a question that isn’t the real question they want to ask. Eg, a student at a university open day who asks “how many A-Levels did you do?”, when what they really care about is “how many A-Levels do I need to do to get in”
      • Your goal should be to understand the state of mind from which that question made sense - once you’ve done this, you can often resolve the confusion directly, or answer the question they really care about.
        • Do this by asking clarifying questions, trying to answer and saying “did that answer your question?”, giving them several interpretations of what they’re really asking and asking whether any resonate, paraphrasing the question back to them, etc.
        • The main trigger to look for here is a note of confusion - the question feeling a bit off, or out of nowhere, something isn’t quite making sense.
        • It’s a delicate balance between doing this and moving on with the talk - try to gauge whether many people share the same confusion, if not, just move on
    • Often doing this can uncover Pedagogical Content-Knowledge, common ways that people misunderstand the ideas you’re teaching. It’s super valuable to collect these, because then you can recognise them in future and dissolve them directly.
  • Illusion of transparency
    • A consequence of the typical mind fallacy - it’s easy to think you’ve clearly communicated knowledge when you really, really haven’t. As a consequence, you need to put a lot of effort into being grounded and calibrated - because often a confused audience won’t feel like a confused audience to you.
    • Ask questions! Especially ones that highlight the key ideas, eg “how to do easy thing X” or “what was the key idea in here?”
    • Do hand-polls - ask people to indicate their understanding by putting their hand up high if it’s clear, and low if it’s less clear. This is a good technique, because most people will actually do it, unlike “does anyone have any questions?” or “is this making sense to people?”
  • Seek feedback and iterate
    • Teaching is hard. You’re fundamentally trying to convey tacit knowledge, via lossy and low bandwidth communication channels, into an alien mind that you have very limited access to. The default state of the world is that you suck at this
    • The solution is to regularly ask for specific, actionable feedback and calibration, and to actually put meaningful effort into updating on this! Feedback is one of the main ways you can better understand the mind of a student.
Teaching 1-on-1

Practicing tutoring and explaining things one on one can often be more valuable! I think a great use of time for most students is to do tutoring - it’s pretty fun, you get paid decently, and you get way better at explaining ideas. And the ability to explain an idea clearly in a conversation is an amazingly applicable skill - I use this all the time in daily life.

The main difference is that it’s a lot easier to get them to be active, and it’s much easier to adapt the pace and difficulty well. Essentially, invert all of the ideas in my post on how to learn from conversation

  • The key technique is asking the student to paraphrase what you’ve said back to you
    • This forces them to be active, and to process information
    • It identifies errors, and helps you to correct them
      • Often you can then recognise th
    • It helps build a model of what’s going on in their mind
    • It helps you calibrate the difficulty and pacing
    • If you’re a tutor who doesn’t do get the student to this, I think you’re missing out on a major free win
      • This is also super effective when explaining ideas to friends, though can seem a bit rude
  • Get the student to tell you the key points/ideas in what you’ve said
  • Get the student to generate examples, especially typical examples
  • Here, understanding the mindset behind the question is even more important. You should always do this when they ask a question, especially if they seem dissatisfied with your answer.
Teaching Maths
  • It’s easy to neglect the tacit information - the intuitions, underlying concepts, motivations. This is terrible. One of the most important parts of teaching maths well is to convey this high-level overview
  • Every proof can be heavily compressed. Most proofs have some key ideas, followed by repeatedly doing the obvious thing. “Repeatedly doing the obvious thing” will inevitably be compressed in the student’s mind, so you should skip saying it at all, and just give the key ideas
  • Examples, especially motivating examples, are incredibly important. It’s really, really hard to learn a new concept without having a clear motivating example in mind.
    • Examples teach tacit knowledge well - they illustrate what you can and can’t do, and why you care about ideas
  • After learning rigour for a while, you’ll end up with post-formal intuitions, where you mostly ignore rigour and think intuitively, but can drop into rigour if need be. Most of the cognitive labour in maths is reaching this point, and a good teacher will try to give as much of the post-formal intuition as possible
  • Maths, especially pure maths, is often formalising an intuition. Probability is the formal study of uncertainty. Groups are the formal study of symmetries. Topology is the formal study of continuous deformations (things which don’t rip or glue). Pointing this out is vital
    • A good way to find these is to notice which questions the topic newly lets you answer. This is a great way to motivate things!
  • Diagrams are awesome
  • Often you begin being able to answer a type of question with a lot of tacit knowledge, and are expected to pick all this up with examples. Often 80% of this can be captured in an explicit algorithm - this is a great way to make tacit knowledge legible.
Teaching Applied Rationality/Life Advice
  • These are much more about tacit knowledge than explicit, so these should be done in a workshop format with a big focus on exercises
    • Emphasise that everything is highly personal and subjective - all ideas should be adapted to your mind and your circumstances
    • Pairing people up works well for getting them to actually do the exercises!
  • Ideally, boil down the tacit knowledge to a rough algorithm, and alternate explaining steps and getting the students to practice them
  • The impact of the class is mostly students retaining key insights and mental habits - what the “time when I should apply this idea” feels like from the inside. This is the small fraction of information they’ll retain. Thus it’s your job to boil down the idea to these habits, say this explicitly, and structure the class to reinforce them
  • Much of the impact comes from the students taking action after the class - this is hard! You want to emphasise this, and minimise barriers
    • Give time for the students to generates lists of ways to apply the ideas, and how they’re relevant in their day to day life
    • Give time for them to set reminders for actions taken after the class
  • Make it feel actionable - it’s easy to think an idea is important, but for it to feel abstract. Eg, to think that prioritisation is a good idea, but to never get round to it.
    • Emphasise how the idea fits into everyday life and everyday problems
    • Give a lot of examples of how to use it - this can form connections like “oh! I never thought of using it for that”
      • This conveys the tacit knowledge of when to use the idea!
  • Emphasise relatability and importance - give examples of a bad situation where the technique wasn’t applied, and make it feel visceral and relatable
Conclusion

If you’re planning on teaching something in the future, I hope these thoughts were useful! But even if not, I think these skills transfer excellently to explaining things in everyday life. And that thinking about teaching can make you a much more effective learner.

I find that often, as a student, I can help the teacher be more effective by asking the right questions - asking them which information is the most important, checking that my understanding is correct by paraphrasing back, asking them for the motivations and higher-level picture. The feeling of “something not fitting into my knowledge graph well” can be made into a pretty visceral one. And realising the habits of students that hinder them from learning, like being passive instead of active, and not trying to do information compression themselves, can help me recognise when I fail to do those things!



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How hard would it be to change GDP-3 in a way that allows audio?

28 августа, 2020 - 17:42
Published on August 28, 2020 2:42 PM GMT

GDP-3 currently only works on text. If OpenAI would desire to make it work with similar performance for audio, how much work would that likely be?



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Zibbaldone With It All

28 августа, 2020 - 14:37
Published on August 28, 2020 11:37 AM GMT

Less Zettelkasten! More Zibbaldone!

A Zettelkasten requires you to intricately interconnect and crosslink your thoughts, figuring out exactly how each concept relates to every other concept. A Zibbaldone is writing down whatever random thing comes to mind - an omnisubject diary of sorts. That's what people are throwing into their Zettelkasten, with their careful annotations and interrelations. What if everyone could access everyone else's Zettelkasten, and interrlate them into a glorious omniscient noospheric substrate? Wow! Whatta thought!

Buuuuuuullshit. This is semantic web stuff all over again - and right at the cusp of it having been clearly and entirely outmoded by automatic natural language processing. We don't need to manually mark up pages when Google will index them all for us anyway! Humans might think in that chaotic, random Zettelkastian way, but explicit sentence composition and task completion is temporally linear, and so we need to output our thoughts in much the same way. Not that we wouldn't love to manually annotate our every passing thought, but god, who has time for that?

What we're really missing is a tool that will take whatever random trash I throw out of my brain, figure out how it relates to historical junk I threw out of my brain, and point out the connections for me. Hell, ideally mid-composition: a modern ersatz Clippy pops up - "Hey, it looks like you're talking about Wittgenstein again! Do you want me to autofill what you already think about it, or have you changed your mind about the topic?"

Not only that: once you get your thoughts out of your head bereft of order, an AI could rephrase your thoughts back to you more clearly, more concisely, help interrogate what you mean, point out logical contradictions, challenge your ideas. We need only Zibbaldone out our stream of consciousness and it can be autonomously interrlated into a glorious omniscient noospheric substrate! Wow! Whatta thought!

...just ignore the risks of mentally coupling with an opaque box, whose biases you don't understand, whose intentions may be short term and not long term, who may network you with exactly the wrong people. Zibbaldone to Zettelkasten mapping seems like a middling-difficulty problem with existing tools, and whoever solves it is going to make a lot of money. When we can auto-generate a Zettelkasten from a blog - or dozens of them - you'll have a whole world of brilliance to tap into!

...or bias. Or noise. Or exactly the sort of thing you're trying to escape from - the internet, where the awful people are, with the Bad Opinions. And what you end up is just another wiki to mindlessly trawl through, to process, to "integrate". I'm starting to think the important part of a Zettelkasten isn't making the links for your future self so much as training yourself to notice the links at all. The Zettelkasten's just external practice for what should be an internal and subconscious process - seeing the fnords, noticing the interconnectedness, it's just training to be a holistic discordian - getting you past the madness of your surface layer thoughts and into the deeper crystalline method.

Of course, everyone will think you're a little crazy - and of course, they'll be a little right. But when the going gets weird, the weird turn pro, and when insanity's the zeitgeist, nothing's more professional than crazy talk. Have fun making bank on the Zibbaldone-Zettelkasten mapping, crafting neurological parasites, offloading the part of our brain with connections and opinions to an external cognitive artifact! No way that can go wrong.

Really, the harder problem's going the other way - give me a web, which path should I walk? What is the narrative of a human mind? You can't read a Zettelkasten effectively, it has too many strands and streams and errant thoughts; you have to craft a narrative out of it, even if you're consuming it out of order, but figuring out how to knit the threads together into a cohesive chunk for consumption's the hard part. What's the mapping then? Zibbaldone to Zettelkasten to... Roman-Fleuve, ministructure to the metastructure? Zettel-fleuve, Zibbal-fleuve? Zittal, Zabbal, Zettaldone, Zibbalkasten, - god, we're all turning into lunatics aren't we? The jargon's making zibbering lunatics of us all - just write something down, anything, throw it to the aether and be zibbaldone with it all.



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C̶a̶m̶b̶r̶i̶d̶g̶e̶ Virtual LW/SSC Meetup

28 августа, 2020 - 05:45
Published on August 28, 2020 2:45 AM GMT

The September Cambridge Less Wrong / Slate Star Codex (RIP) meetup will be held online due to the plague.

Hangouts link



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RE "On Bullshit" and "On Truth," by Harry Frankfurt

28 августа, 2020 - 03:44
Published on August 28, 2020 12:44 AM GMT

Salticidae Philosophiae is a series of abstracts, commentaries, and reviews on philosophical articles and books.

Harry Frankfurt asks, “What is bullshit, anyway?” Also, “What is truth?” but we all know that book proposal wouldn’t have flown except as a companion to the first one.

Highlights
  • Something can be true, and still be bullshit.
  • Something can be a lie, and yet not be bullshit.
  • Bullshit is that which is (1) unconcerned with truth and (2) intended to change attitudes rather than beliefs.
  • Truth is useful to us as individuals and as societies
  • Truth-seeking and truth-telling must be rewarded and their inverse must be punished.
  • Truth is truth whether or not anyone believes it or even knows it.
New or uncommon terminology
  • On Bullshit is described as a prolegomenon to On Truth, or an extended introduction that serves to discuss and interpret the work in a manner that is more exhaustive than the typical introduction.
Book-by-bookOn Bullshit

There is not much literature on bullshit, and no "theory of bullshit" or rigorous analysis thereof. This is in large part because we all assume that we recognize and evade bullshit pretty well.

According to Max Black, humbug is essentially a (false) statement made, not to convince you about that thing, but to convince you of something else. For example, one might make blatantly and obviously exaggerated or otherwise false statements about U.S. history not to convince another of these things, but to convince another of one's patriotic fervor.

Starting from this definition of humbug, Frankfurt makes a number of comparisons and caveats that might be useful:

  • Bullshit may be made carelessly, and we could easily compare bullshit to shoddy goods.
  • Shit is excreted, not crafted. However, advertising can be carefully-crafted bullshit.
  • Similes are not lies, but they can be made too thoughtlessly. In their own way, they can be bullshit.

Frankfurt argues that bullshit is, to start with, deliberate misrepresentation. Some say that lying requires intent; others, that any false statement is a lie. Bullshitting, however, is not exactly the same as lying. Indeed, bullshit can be true. Frankfurt's position is that bullshit is distinguished not by its truth or falsity, but by a disregard for the truth; as he puts it, honest folk and liars are playing the same game, to convey the facts or to obscure them, but the bullshitter is playing another game entirely.

Truth-tellers and liars are both concerned with changing your beliefs; a bullshitter is concerned with changing your attitude.

  • "Someone who ceases to believe in the possibility of identifying certain statements as true and others as false can have only two alternatives. The first is to desist both from efforts to tell the truth and from efforts to deceive. [...] The second alternative is to continue making assertions that purport to describe the way things are, but that cannot be anything but bullshit." [pg 61 para 2]
  • "Just as hot air is speech that has been emptied of all informative content, so excrement is matter from which everything nutritive has been removed. Excrement may be regarded as the corpse of nourishment, what remains when the vital elements in food have been exhausted. In this respect, excrement is a representation of death that we ourselves produce and that, indeed, we cannot help producing in the very process of maintaining our lives." [pg 43 para 1]
On TruthIntroduction

This is a sequel to On Bullshit, which addresses an oversight of his: the author failed to make any argument as to why the truth is important, and bullshit is therefore reprehensible. This book is about why truth is important.

There is lots of bullshit but it hasn't destroyed civilization, so some people think that truth isn't important. Some people even refuse to admit that there is such a thing as truth. though these people are very silly (not least because they tend to represent themselves as truly holding this belief). The book therefore assumes that there is an "objectively meaningful or worthwhile distinction to be made between what is true and what is false," and concerns itself solely with addressing whether this distinction matters outside of academia.

He spends more that a tenth of the book explaining what he's doing and why he's doing it.

Chapter I

Truth is useful to us. Societies cannot function without fostering truth. Both individuals and groups must know facts and as societies become more complex they must know more facts, and more accurately (while many individuals, it must be said, can remain free riders).

Postmodernists reject the idea that truth has objective reality or value, at least as perceived by us; our view of the truth is determined by constraints that have been imposed upon us by personal and social environments and histories. It is interesting that postmodernism does not exist (in this form) in medicine, physics, and other fields whose assertions are easily testable. Even in history, there must be objective facts: "They will not say that Belgium invaded Germany," the author reports Georges Clemenceau as saying.

Chapter II

Even if some value statements are not verifiable, they can generally be connected back to facts that can be discussed. Knowing the facts of the matter lets us determine whether we ought to value the things that we do, or whether other goals and activities might better accomplish our terminal values.

  • Healthy societies must reward truth-finders and punish truth-obscurers.
  • Having facts is not enough to succeed (you must use them properly), but not having facts prevents you from taking any action at all.
Chapter III

One might argue that we could just not care about this need for truth. Spinoza argued that we cannot help but care, because of love, which is "nothing but Joy with the accompanying idea of an external cause." essentially an experience that broadens one's understanding of oneself and improves one's capacity for perfection. or (in the author's words) "the way that we respond to something that we recognize as giving us joy." Additionally, joy is the experience of being ennobled or otherwise improved (and, preferably, knowing this). Therefore, truth gives us joy, because it improves us, and because we wish to preserve and keep nearby that which we love, we will seek to preserve truth.

Chapter IV

When we act, we interact with reality, and we have a desire or at least an expectation regarding the outcome of our action. To the degree that we lack truth, we are disconnected from reality and that desire or expectation may be thwarted.

  • It is always better to face uncomfortable truths than to hide away from them, because if we do not confront them then, one day, we will be confronted by them.
  • Without truth, we are blind. We might not run into trouble immediately, but we will do so inevitably.
  • "The relevant facts are what they are regardless of what we may happen to believe about them, and regardless of what we may wish them to be. This is, indeed, the essence and the defining character of factuality, of being real: the properties of reality, and accordingly the truths about its properties, are what they are, independent of any direct or immediate control by our will." [pg 55 para 2]
Chapter V

Truth fosters trust. Honesty is the foundation of society, while dishonesty undermines social fabric. Even the capacity for self-recognition (or self-awareness, we might say) ultimately depends on our relationship with the truth. If we do not know the world, then we cannot know ourselves.

  • If someone starts getting into etymology as part of some Deep Explanation, then prepare for a torrent of bullshit.
  • Immanuel Kant, "On a Supposed Right to Lie from Altruistic Motives": "A lie always harms another; if not some particular man, still it harms mankind generally.
  • Michel Montaigne, "Of Liars": "If we did but recognize the horror and gravity of [...lying], we would punish it with flames more justly than other crimes."

Even the capacity for self-recognition (or self-awareness, we might say) ultimately depends on our relationship with truth. If we do not know the world, then we cannot know ourselves.

Comments

On Bullshit argues that bullshitting doesn't necessarily undermine society, at least not up to a point, but I I would expect a hypothetical society with even slightly less bullshit than ours to function more smoothly. I also disagree with the position that truth intrinsically gives us joy. Many of us love bullshit more than truth.

Frankfurt says that lying is bad at its core because the liar "tries to impose his will on us," even if it is for our own good, but he fails to argue that this in itself is bad. More convincing is Frankfurt's argument that we are being pushed into another world insofar as our beliefs are false, but what if the lie is believed on a large scale? Then we would be isolated by believing the truth. He also argues that the liar is personally isolated, and cannot even speak of that isolation, but this is untrue if the liar has partners.

Favorite passageAs conscious beings, we exist only in response to other things, and we cannot know ourselves at all without knowing them. Moreover, there is nothing in theory, and certainly nothing in experience, to support the extraordinary judgment that it is the truth about himself that is the easiest for a person to know. Facts about ourselves are not peculiarly solid and resistant to skeptical dissolution. Our natures are, indeed, elusively insubstantial--notoriously less stable and less inherent than the natures of other things. And insofar as this is the case, sincerity itself is bullshit. [On Bullshit, pg 66 para 2]Author biography

Harry G. Frankfurt is Professor of Philosophy Emeritus at Princeton University. His books include The Reasons of Love (Princeton), Necessity, Volition, and Love, and The Importance of What We Care About.

Philosophers & works mentioned

Philosophers given significant attention include:

  • Max Black, a British-American philosopher who, for some reason, has a longer article on the Unitarian-run New World Encyclopedia than he does on Wikipedia, even though the former takes its articles from the latter before it edits and builds upon them.
  • Immanuel Kant, a German philosopher who argued that reason is the basis of morality, and drew attention to the difference between the world-as-it-is and the world-as-it-appears-to-us.
  • Michel Montaigne, a French philosopher of the Renaissance period who wrote on child education, psychology, and other topics, and popularized (but did not invent) the essay format.
  • Baruch Spinoza, a Jewish Portuguese philosopher who is best known for his writings on God, which have gotten him labeled as everything from a pantheist to an atheist.
Other articles & books on this subject

Discuss

Notes on "The Anthropology of Childhood"

27 августа, 2020 - 20:11
Published on August 27, 2020 5:11 PM GMT

Crossposted from The Whole Sky.

I read David Lancy’s “The Anthropology of Childhood: Cherubs, Chattel, and Changelings” and highlighted some passages. A lot of passages, it turns out.

[content note: discussion of abortion and infanticide, including infanticide of children with disabilities, in “Life and Death” section but not elsewhere]

I was a sociology major and understood anthropology to be basically “like sociology, but in Papua New Guinea.” This is the first cultural anthropology book I’ve read, and that was pretty much right. I found it very accessible as a first dive into anthropology. The first chapter summarizes all his points without the examples, so you could try that if you want to get the gist without reading the whole book.

I enjoyed it and would recommend it to people interested in this topic. A few things that shifted for me:

  • I feel less obliged to entertain my children and intervene in their conflicts. We don’t live with a tribe of extended family, but my two children play with each other all day, which is how most people throughout time have spent their childhoods. Lancy isn’t a child development expert, but I buy his argument that handling conflict (for example about the rules of a game) is a skill children need to learn, rather than having conflicts always mediated by adults.
  • Even though it doesn’t change anything concrete, I feel some relief that not having endless patience for toddlers seems to be normal. Except where families were very isolated, it’s not normal in traditional societies for one or two adults to watch their own children all day every day. And childcare has traditionally looked mostly like “being sure they don’t hurt themselves too badly.”
  • It surprised me that childcare by non-parents was so common. Some more modern views treat women’s childcare work as basically free, traditional cultures have valued women’s labor enough that the society wants to free up their time from childcare. It was striking to me that the expectation that stay-at-home mothers will be responsible for all childcare was a relatively short historical blip. But of course, having childcare done by teenagers and grandmothers requires that those people’s time be available, which usually isn’t the reality we live in.
  • I was surprised at how apparently universal it is for fathers to be uninvolved.

I’m a little unclear on how valid Lancy’s conclusions are or how much data they’re based on. It seems like an anthropologist could squint at a society and see all kinds of things that someone with a different ideology wouldn’t see.

Big caveat that what Lancy is describing is traditional, non-industrialized societies where children are expected to learn how to fit into the appropriate role in their village, not to develop as an individual or do anything different from what their parents and ancestors did. He stresses that traditional childrearing practices are very poor preparation for school. Given that I want my children to learn things I don’t know, to think analytically, etc, the way I approach learning is very different from how traditional societies approach it.

One complaint is that Lancy periodically complains about how much money Western families spend on fertility treatments, medical care for premature infants, etc. He argues that the same money could be used to provide adequate nutrition for many more children in the societies he’s studied. I’m sympathetic, but assuming that families would donate this money if they weren’t spending it to have a baby is not realistic. I see cutting luxury spending as a much more feasible way that people might do some redistribution.

And now, my notes:

Views of childhood

As in many areas of research, the children who have been studied by academics are mostly from WEIRD ("Western, educated, industrialized, rich, democratic”) populations. Thus our understanding of good or normal childrearing practices is very different from how children have typically been raised. Lancy contrasts modern childrearing norms with those of traditional agrarian or forager societies.

Lancy contrasts neontocracy (where babies and children are most valued) with gerontocracy (where elders or ancestors are most valued). I can think of ways our society isn’t very good for children, but I agree that compared with traditional societies, we spend a lot of attention and money on children. (Albeit sometimes by micromanaging them, while Lancy would rather have them figure out more for themselves as children have historically done.)

Even studying children is a strange thing to do in most societies. “Examples of children treated as lacking any sense, as being essentially uneducable, are legion in the ethnographic record.” “Anthropologists interested in children are treated in a bemused fashion; after all, why bother to observe or talk to individuals who ‘don’t know anything’?” (Lancy 1996: 118; also Barley 1983/ 2000: 61)“

“Infants were widely seen as insensible. Almost like plants, their care could be rudimentary”

Traditional societies have two broad patterns toward young children: “One response is ‘benign neglect’– everyone waits until the child can talk sensibly before acknowledging its existence. A second typical response is to aggressively humanize the child, including ruthless suppression of all ‘sub-human’ tendencies (e.g. bawling, crawling, thumb-sucking).”

Europeans were of the second view:

“Like wild men [or beasts], babies lacked the power to reason, speak, or stand and walk erect. [They were] nasty, brutish, and dirty, communicating in wordless cries, grunts, and screams, and were given to crawling on all fours before they could be made to walk like men … Left to their own devices, they would remain selfish, animalistic, and savage. Parents believed they had to coerce their babies into growing up, and they expected protests and resistance. (Calvert 1992: 26, 34)”

“The Puritans were perhaps the first anxious parents, fearing they might fail and their children would turn out badly.”

“We now take for granted the “need” to stimulate the infant through physical contact, motherese, and playing games like peek-a-boo to accelerate physical and intellectual development. Contrast these assumptions with the pre-modern objective of keeping babies quiescent so they’d make fewer demands on caretakers and not injure themselves (LeVine et al. 1994).”

“Much of what we think of as the routine duties (e.g. reading bedtime stories; cf. Lancy 1994) or expenses (e.g. orthodontics) of modern parents are completely unknown outside modern, mainstream societies.”

“150 years ago, the idea of the useful child began to give way to our modern notion of the useless but also priceless child (Zelizer 1985). Children become innocent and fragile cherubs, needing protection from adult society, including the world of work. Their value to us is measured no longer in terms of an economic payoff or even genetic fitness but in terms of complementing our own values – as book lovers, ardent travelers, athletes, or devotees of a particular sect.”

“Known as the “largest children’s migration in history,” so-called “orphan trains” carried about 200,000 children (Warren 2001: 4) from orphanages and foundling homes in eastern coastal cities to families in the Midwest (Kay 2003: iii) and West. The orphan trains continued until 1929 (Warren 2001: 20), which indicates how very recently our fundamental conception of children as chattel changed to viewing them as cherubs.”

Anne of Green Gables is a story about this dynamic in Canada — the family was expecting to adopt a boy who could serve as an unpaid farmhand, but got a girl orphan by mistake.

Who cares for children?

Surprisingly to me, in traditional societies it’s usually not mothers.

In the early days of infancy, of course, breastfeeding necessitates keeping mother and baby convenient to each other. “Nearly all societies hold very strict views on the necessity for almost constant contact between a mother or other nurturing adult and the infant. Infants are fed on demand, carried constantly, and sleep with their mother. Young mothers are severely chastised for any lapse in infant care. However, once the infant begins to walk, it immediately joins a social network in which its mother plays a sharply diminished role – especially if she’s pregnant – and its father may play no role at all.”

On the saying “it takes a village to raise a child”: “If one actually looks at real kids in real villages, either one sees infants and young children in a group of their peers, untended by an adult, or one sees a mother, or a father, or an older sister, or a grandmother tending the child. These helpful family members are referred to in anthropology as ‘alloparents.’ The rule governing their behavior would not necessarily be ‘Everyone’s eager to have a hand in caring for the child,’ but, rather, ‘Whoever can most easily be spared from more important tasks will take care of the child.’ And the next rule we might derive from our observations might be, “The mother is often too busy to tend to the child.” At the same time, babies are not simply passive recipients of care. They not only look cute, they beguile caretakers with their gaze, their smiling and their mimicry (Spelke and Kinzler 2007: 92). While alloparents may want to minimize their effort (Trivers 1974) in caring for the child, the very young have an arsenal of tactics they can deploy to secure additional resources (Povinelli et al. 2005).”

“Weisner and Gallimore examined hundreds of ethnographies in the Human Relations Area Files (HRAF) archive and found that, in accounts of childcare, 40 percent of infants and 80 percent of toddlers are cared for primarily by someone other than their mother, most commonly older sisters (Weisner and Gallimore 1977).”

“Three-year-old children are able to join in a play group, and it is in such play groups that children are truly raised” (Eibl-Eibesfeldt 1989: 600).”

“Once the infant has been judged worthy of rearing, it will be displayed to a community eager to interact with it. In particular, its older sisters will be in the forefront of those wanting to share in the nurturing process. The circle of caretakers may gradually widen to include aunts, grandmothers, and, occasionally, the father. Even more distant kin can be expected to cast a watchful eye on the child when it is playing on the ‘mother-ground’ (Lancy 1996: 84). Indeed, the toddler must seek comfort from relatives as it may be abruptly weaned and forcibly rejected by its mother as she readies herself for the next child.”

In a large polygynous household the author visited in Liberia, even after a few weeks he was unable to figure out which children belonged to which mothers: “I was stymied because the children, once they were no longer attached marsupial-like to their mother’s body with a length of cloth, spent far more time in each other’s company and in the company of other kin, particularly grandmothers and aunts in nearby houses, than with their mothers. And as far as the chief was concerned, I just had to assume that since these were his wives, the majority of the children in the vicinity must be his as well. Aside from dandling the occasional infant on his knee during the family’s evening meal, I never saw him enjoy more than the most fleeting interaction with a child.” Later, “I began to see their family arrangements and childcare customs as neither unusual nor exotic, rather as close to the norm for human societies, and, simultaneously, to see the customs of the middle-class Utah community I live in now as extraordinary.”

Older sisters are often alloparents:

“Across the primate order, juvenile females show great interest in infants (Hrdy 1999: 157), and it is not hard to sustain an argument that their supervised interaction with younger siblings prepares them for the role of motherhood (Fairbanks 1990; Riesman 1992: 111). The weanling’s need for mothering corresponds to the allomother’s need to mother.”

This seems to be true in other primates as well (though I do imagine researcher bias could interpret some kinds of carrying around a stick as ‘doll play’ depending on the gender of the young chimp.)

Several studies have documented the gender bias in “baby lust” (Hrdy 1999: 157). Females show far more interest in babies, images of babies, and even silhouettes of babies than do males. In fact, there’s some evidence that young chimp females will cradle, groom, and carry around a “doll” (a stick or a dead animal) in the absence of a live infant (Kahlenberg and Wrangham 2010: 1067).

“In Uganda in 2003, I observed and filmed numerous primate species and, after resting, eating, and play, “baby-trading” is the most common occupation. Often I observed what amounted to a “tug-of-war” between the nursing mother and her older daughters for possession of the infant, which may lead to what Sarah Hrdy (1976) referred to as “aunting to death.” By contrast, mothers tend to discourage interest shown by juvenile males in their offspring (Strier 2003).12

“Aunting to death” sounds familiar to me. When Lily was born, we lived with Jeff’s family including his two sisters. They would literally race each other to the baby each morning when I came downstairs with Lily, as each aunt tried to arrive first for baby cuddles.

Boys are not seen as good caregivers:

“Dozens of studies have documented the heightened likelihood of sensation-seeking (Zuckerman 1984) or risk-taking by adolescent primate males in groups. Demographers have identified an “accident hump” in mortality curves for male primates, including humans, during puberty (Goldstein 2011).”

"I had a personal epiphany regarding the inadvisability of assigning boys as sibling caretakers in May 2007 as I stood on a busy street in front of the Registan in Samarkand. Two boys were pushing baby carriages in the street, just barely out of traffic. The street sloped downward and the lead carriage-pusher began a game of chicken, releasing his grip on the bar, then rushing after to grab it as the carriage rolled away on its own. This game was repeated with longer intervals between the release and retrieval."

Children need less oversight in less dangerous environments:

“Tether-length is definitely a useful concept in observing human mother– toddler interaction (Broch 1990: 71–72). As Sorenson discovered in a Fore village, the infant’s “early pattern of exploratory activity included frequent returns to the mother. She served as the home base, the bastion of security but not as director or overseer of activities” (Sorenson 1976: 167). For the forest-dwelling Chewong, the tether is shorter. Toddlers are discouraged from wandering away from proximity to adults with “loud exclamations …‘it is hot,’ or ‘it is sharp,’ or ‘there are … tigers, snakes, millipedes’” (Howell 1988: 163).”

Swaddling makes children easier to watch:

“A swaddled baby, like a little turtle in its shell, could be looked after by another, only slightly older child without too much fear of injury, since the practice of swaddling made … child care virtually idiot proof. (Calvert 1992: 23–24)”

There is a chain of oversight:

“toddlers are managed by slightly older siblings, who are, in turn, guided by adolescents, while adults serve as rather distant “foremen” for the activity, concentrating, primarily, on their own more productive or profitable activity.”

The stereotype of grandmothers “spoiling” children is not unique to the West:

“[I]n the Mende view, grannies are notoriously lax with children. They are said to feed children upon demand and do not beat them or withhold meals from them for bad behavior or for failing to work … Children raised like this are said to grow up lazy and dishonest …”

In Rome, nurses were responsible for childcare in wealthy families:

“It was the nutrix [nurse] who … took responsibility for … early infant care: breast-feeding, powdering and swaddling, bathing and massaging, rocking and singing the child to sleep, weaning the child from milk to solid food … The nutrix, in fact, was only one of a sequence of child-minding functionaries who influenced the early lives of children.”

“Public attitudes in Europe reflect a view of the family that echoes the utopian ideals of the Israeli kibbutz from the mid-twentieth century. While the mother might be the primary caretaker during infancy, shortly afterward the child should be placed in a nursery with trained staff as she returns to her job. This policy is seen as beneficial to the mother’s self-esteem, the economy, and the child itself (Corsaro 1996; Dahlberg 1992; Eibl-Eibesfeldt 1983: 181). Publicly supported pre-school or daycare in the US has been blocked by the politically powerful religious right, which insists on keeping wives tied full-time to the kitchen and nursery.”

When childcare is a collective task, discipline is also collectivized:

“The mother must, however, accept the consequence that virtually anyone older than her child can scold or even discipline them (Whiting 1941). In societies like our own, where childcare is handled within the nuclear family and/or by professionals, the necessity for learning manners and kinship arcana is reduced. At the same time, we are often reluctant to concede to outsiders, even “professionals,” the right to discipline our young.”

Why do mothers outsource childcare?

“In a majority of the world’s diverse societies, women continue as workers throughout pregnancy and resume working shortly after the child is born. This work is physically demanding, so, for many, there is a peak period in their lives when they have the stamina and fat reserves to do their work and have babies. How many babies they successfully rear will depend heavily on their access to a supportive community of relatives who can help with household work, assist with childcare, and provide supplementary resources.”

How children are taught to relate to others

Contrasted with the emphasis on the mother-child bond in WEIRD society generally and especially in “attachment parenting”, traditional cultures may emphasize finding other caregivers:

“The baby’s cherub-like features aid the mother in her quest for helpers. Young mammals, generally, but especially humans, display a suite of physical features that seem to be universally attractive to others, and these features are retained longer in humans than in other mammalian species (Lancaster and Lancaster 1983: 35; Sternglanz et al. 1977). Also critical is the fact that human infants vocalize, make eye contact, and smile from very early on (Chevalier-Skolnikoff 1977) – unlike chimps, for example, whose mothers make more limited use of helpers. Mothers may not always rely on the inherent cuteness of their babies; they may take pains to showcase the baby – at least among close kin. The Kpelle mothers I observed didn’t stop at frequently washing and cleaning their babies. They oiled the babies’ bodies until they gleamed – an ablution carried out in public view with an appreciative audience. The Kaluli mothers studied by Bambi Schieffelin in Papua New Guinea not only hold their infants facing toward others in the social group – a practice often noted in the ethnographic record – but treat the baby as a ventriloquist’s dummy in having him or her speak to those assembled (Schieffelin 1990: 71). The Beng advise young mothers: Make sure the baby looks beautiful! … put herbal makeup on her face as attractively as possible … we Beng have lots of designs for babies’ faces … That way, the baby will be so irresistibly beautiful that someone will feel compelled to carry her around for a while that day. If you’re lucky, maybe that person will even offer to be your leng kuli. (Gottleib 1995: 24) When [Guara] neighbors visit … relatives – identified by kinship terms – are repeatedly indicated to the child. (Ruddle and Chesterfield 1977: 29) [Marquesan mothers] … spent much time calling the baby’s name, directing him to look and wave at others … directing three- to six-year-old siblings to play with him. (Martini and Kirkpatrick 1981: 199)”

“Samoan …toddlers were fed facing others and prompted to notice and call out to people. (Ochs and Izquierdo 2009: 397) From the moment a [Warlpiri] child is born … she will hear every day … for the next few years; “Look, your granny,”‘That’s your big sister, your cousin, your auntie.” In fact, they make up the bulk of verbal communication with babies and little children. (Musharbash 2011: 72)”

“There were numerous constraints put on young [Orissa India] mothers to prevent them from focusing too much attention on a new infant. Close, intimate mother-child bonds were viewed as potentially disruptive to the collective well-being of the extended family … In such families, much early child-care was organized so as to subtly push the infant away from an exclusive dependence on its mother toward membership in the larger group. (Seymour 2001: 15)”

How do parents learn to parent?

Partly through alloparenting as described above. Among other primates:

“While the benefits to the mother are obvious, allomothering daughters also clearly benefit by learning how to care for infants (Fairbanks 1990). A study of captive chimpanzees showed that females prevented from interacting with their mothers and younger siblings were themselves utterly incompetent as mothers (Davenport and Rogers 1970).”

I was surprised at how hard it was to feed a newborn - in my case I got help from the midwife, a lactation consultant, and the pediatrician, but traditionally advice would come from family and neighbors:

“Field and colleagues, working with Haitian immigrant mothers in Miami, find these mothers often have difficulty feeding their offspring, who are therefore hospitalized for dehydration and malnutrition at a high rate (Field et al. 1992: 183). I think it’s possible these young women immigrants lost the opportunity to learn how to care for infants from older women.”

Among the Fulani of West Africa:

“All women caring for their first babies will have had years of experience taking care of babies … under the watchful and sometimes severe eyes of their mothers, aunts, cousins or older sisters. The other women … will immediately notice, comment on, and perhaps strongly criticize any departure from customary behavior on the part of mothers. (Riesman 1992: 111)”

(Anthropologists traveling with their own children also get a lot of advice from locals.)

Nutrition

I hadn’t really thought about how much of life in traditional societies revolved around the essential, never-ending task of getting calories. There is often not enough to go around, and social differences can be observed through which children’s growth is stunted.

“A study of the Mende found that senior wives did have higher fitness while junior wives had fewer surviving children than their counterparts in monogamous unions (Isaac and Feinberg 1982). Similarly, in Botswana, children of more senior wives enjoyed nutrition and school attendance advantages (Bock and Johnson 2002: 329).”

The author recalls seeing “a picture of a mother holding on her lap a boy and girl of about the same age, possibly twins. The girl was skeletal, obviously in an advanced state of malnutrition, the boy robust and healthy. He sat erect, eyes intent on the camera; she sprawled, like a rag doll, her eyes staring into space. That picture and what it represented has haunted me ever since.”

Babies of the preferred sex are likely to be nursed longer and have higher survival rates.

Many folk traditions recommend foods for children, or diets for sick children, that are undernourishing or likely to be contaminated:

“Meat is usually among the foods kept from children. This is probably harmful, as a protein shortage, in particular, is often found in recently weaned children. However, malnutrition is rarely identified by parents as the root of a child’s illness. Katherine Dettwyler pointedly titled her study of the Dogon Dancing Skeletons, describing, in graphic detail, the horrific sight of severely malnourished children. She finds that, while the mothers are aware of something amiss, they attribute the problem to locally constructed folk illnesses and seek medicine from the anthropologist to effect a cure. When she tells them to provide the child with more food, they are skeptical. Children can’t benefit from good food because they haven’t worked hard to get it, and they don’t appreciate its good taste or the feeling of satisfaction it gives. Anyway, “old people deserve the best food, because they’re going to die soon” (Dettwyler 1994: 94–95). Yoruba mothers feed children barely visible scraps compared to the portions they give themselves. Good food might spoil the child’s moral character (Zeitlin 1996: 418; also true for the Tlingit – cf. de Laguna 1965: 17). The prescription for a sick child among the Gurage tribe in southwest Ethiopia is often the sacrifice of a sheep: “The flesh of the sacrificial animal is eaten exclusively by the parents of the sick child and others who are present at the curing rite; no portion of the meat is consumed by the patient, whose illness may well stem from an inadequate diet” (Shack 1969: 296).”

“Aside from a demonstrable shortage of food (Hill and Hurtado 1996: 319), under-nutrition may be attributable to customs that support a shortening of the nursing period, such as the belief by some East African pastoralists that certain babies nurse “too much” and should, therefore, be weaned early (Sellen 1995). On Fiji, nursing beyond one year is condemned as keeping “the child in babyhood [, leading to] a weak, simpering person” (Turner 1987: 107). The Alorese use threats to discourage nursing: “If you continue nursing, the snakes will come … the toad will eat you” (Du Bois 1941: 114).” (The WHO currently recommends breastfeeding until age 2 or beyond.)

While medical science considers the first milk (colostrum) to be especially beneficial to the newborn because of the antibodies it contains, folk tradition often withholds it from newborns: “In a survey of fifty-seven societies, in only nine did nursing begin shortly after birth (Raphael 1966).”

Spacing children

Contrasted with agricultralists who go for large families, “foragers adopt a “survivorship” reproductive strategy. Around-the-clock nursing and a post-partum sex taboo combine to insure long intervals between births, leading to lower fertility. Low fertility is offset by the attention bestowed on the few offspring, enhancing their chances of survival (Fouts et al. 2001).” Breastfeeding suppresses women’s fertility.

“Another way in which nature contributes to increasing IBI [inter-birth interval] is through post-partum depression following a miscarriage, stillbirth, or infant death. Binser notes that depression elevates cortisol and leaves the mother lethargic and sleepy, which may just serve to put off the next pregnancy until she has had a chance to recoup her vigor (Binser 2004). Nature is aided by culture in promoting longer IBIs through injunctions that militate against long intervals between nursing bouts. Frequent, round- the-clock nursing maintains high prolactin levels. The post-partum taboo on intercourse between husbands and wives also plays a critical role in spacing births.”

In other cases the mother is physically separated from her husband: “The wife may be lodged in a birthing or 'lying-in' house (Lepowsky 1985: 64), or secluded in her own home, until, in the Trobriands, 'mothers lost their tans and their skin color matched that of their infants' (Montague 1985: 89).”

In traditional societies, early sexual activity was less likely to result in pregnancy because adolescents were often malnourished and their fertility lower than we’d expect.

Which children are preferred

I had assumed that boys were always preferred in traditional societies, but it depends. The gender preference, or lack therof, is influenced by parents’ expectations of help their children will provide them with.

“There is a world in which children almost always feel “wanted” and where “there is no cultural preference for babies of either sex” (Howell 1988: 159). Infants are suckled on demand by their mothers and by other women in her absence. They are indulged and cosseted by their fathers, grandparents, and siblings. Children wean themselves over a long period and are given nutritious foods (Robson and Kaplan 2003: 156). They are subject to little or no restraint or coercion. Infants and toddlers are carried on long journeys and comforted when distressed. If they die in infancy, they may be mourned (Henry 1941/1964: 66). They are rarely or never physically punished or even scolded (Hernandez 1941: 129–130). They are not expected to make a significant contribution to the household economy and are free to play until the mid to late teens (Howell 2010: 30). Their experience of adolescence is relatively stress free (Hewlett and Hewlett 2013: 88). This paradise exists among a globally dispersed group of isolated societies – all of which depend heavily on foraging for their subsistence. They are also characterized by relatively egalitarian and close social relations, including relative parity between men and women (Hewlett et al. 1998).”

“One thorough study compared Hungarian Gypsies (matriarchal) with mainstream Hungarian (patriarchal) society. Gender preferences were as expected and behaviors tracked preferences. Gypsy girls were extremely helpful to their mothers and tended to remain at home longer than their brothers, helping even after marriage. They were nursed longer than their brothers, while Hungarian boys were nursed longer than their sisters. “Gypsy mothers were more likely to abort after having had one or more daughters, while Hungarians are more likely to abort pregnancies when they have had sons” (Bereczkei and Dunbar 1997: 18).”

“Names such as “Boy Needed” (Oghul Gerek) or “Last Daughter” (Songi Qiz) are common for girls. (Irons 2000: 230)”

Family structure

“We now realize that mothers, fathers, and children have differing agendas. The nursing child wants to be the last child his mother will ever have so that he can enjoy her care and provisioning exclusively. The father will be opportunistic in seeking mating opportunities and display a similar fickleness toward the provisioning of his offspring. He will, in other words, spread his investment around to maximize the number of surviving offspring. The mother has the most difficult decisions of all. She must weigh her health and longevity and future breeding opportunities against the cost of her present offspring, including any on the way. She must also factor in any resources that might be available from her children’s fathers and her own kin network.”

(Of course I can think of many loving and capable fathers, not least my own partner. But I was surprised that they seem to have historically played so little role in childrens’ lives.)

Polygyny is a common traditional way of structuring families, “the great compromise” between these competing interests.

“Estimates range from 85 percent (Murdock 1967: 47) to 93 percent (Low 1989: 312) of all societies ever recorded (about 1,200) having practiced polygyny.”

“Women in a polygynous relationship gain access to a higher-ranking, reliable provider at the cost of emotional strain in sharing resources (including the husband’s affection) with others. In one study, children of senior wives were better nourished than children in monogamous unions, who were, in turn, better nourished than children of later wives (Isaac and Feinberg 1982: 632). A woman must weigh the trade-offs between marrying a young man in a monogamous union or marrying an older man and joining a well-established household as a junior wife. Studies show that, if they choose monogamy, they enjoy slightly higher fertility (Josephson 2002: 378) and their children may be somewhat better nourished (Sellen 1998a: 341). However, they are, perhaps, more likely to be abandoned or divorced by their husbands.”

Both polygyny and monogamy have their pros and cons:

“In my fieldwork in Gbarngasuakwelle, I lived (as a guest) in a large, polygynous household and the tensions were palpable. This was seen as harmful to children. The shaman (village blacksmith in this case) came often to divine the cause and, using appropriate rituals (inevitably involving the sacrifice of a chicken), would attempt to ameliorate it (Lancy 1996: 167).”

“In Uganda, monogamy has led to less stable marriages. A man, rather than bringing a second wife into the household, now abandons the first wife and her children to set up a second separate household with his new mate (Ainsworth 1967: 10–11). A typical case among the Nyansongo in Kenya describes a mother, whose childhood was spent in a large polygynous compound where multiple caretakers were always available, who must cope alone in a monogamous household. She leaves her three-year-old to mind her six-month- and two-year-old infants as she performs errands like bringing the cow in from pasture. Unfortunately, the three-year-old is simply not mature enough for this task and is, in fact, ‘rough and dangerously negligent’ (Whiting and Edwards 1988a: 173).”

“As societies become more mobile and men migrate seeking employment, the likelihood that the male will abandon (or neglect) his family in the village in order to establish a new family in the city is increasingly high (Bucher and d’Amorim 1993: 16; Timaeus and Graham 1989). And, perhaps most common of all, women whose fertility is on the decline are replaced by younger wives in peak breeding condition (Low 2000: 325)”

“The abandoned spouse and her children may face severe difficulties. One might think that an obviously fertile woman would be a ‘catch,’ but ‘Having a child towards whom a new husband will have to assume step-parental duties diminishes rather than enhances a woman's marriageability’ (Wilson and Daly 2002: 307). “

“In the case of a young, pregnant widow, ancient Roman law permitted both annulment and the exposure of the infant in order to enhance her chances of remarriage (French 1991: 21). Raffaele describes an unfortunate case in a Bayaka13 foraging band in Central Africa:

Mimba had been in a trial marriage … her partner’s father had refused to pay the bride price and she had just been forced to return to her own family. She is two months’ pregnant, and it is a disgrace for an unmarried Bayaka woman to give birth” (Raffaele 2003: 129). Fortunately for Mimba, the tribe’s pharmacopoeia includes sambolo, a very reliable and safe herbal abortifacient, which she will use. Mimba will return to the pool of eligible mates and, hopefully, will find a family willing to pay the bride-price so their son can join her in raising a family – something she could not accomplish by herself.’”

“Studies in the USA indicate that living with a stepfather and stepsiblings leads to elevated cortisol levels, immunosuppression, and general illness (Flinn and England 1995)31 as well as poorer educational outcomes (Lancaster and Kaplan 2000: 196). Daly and Wilson find that a child is a hundred times more likely to be killed by a stepparent than by a biological parent (1984: 499).

Some form of fostering, adoption, or “child circulation” is practiced in many societies:

“Most commonly the child is transferred ‘to fulfill another household’s need for labor’ (Fée – Martin 2012: 220) as a ‘helper’ (Inuit – Honigmann and Honigmann 1953: 46). The request may be for a girl in families with a shortage of female labor (Kosrae – Ritter 1981: 46; Bellona – Monberg 1970: 132). On Raroia boys are requested as they can work in copra processing (Danielsson 1952: 120). On the other hand, the impetus may begin with a family that has a surplus of children (Bodenhorn 1988: 14), or children too close in age, or discord within the family; or as the means to defray a debt. Stepchildren are often moved out of the natal home to make way for the new parent’s biological offspring.”

Life and death

The topic that most surprised me in the book was traditional attitudes toward abortion and infanticide. I thought of life before birth control as “the bad old days” when women, perhaps not even understanding how babies are conceived, might be sentenced to a lifetime of childbearing and rearing against their wishes. I had never thought about how traditional societies actually handled unwanted babies.

“Data from a range of societies past and present suggest that from one-fifth to one-half of children don’t survive to five years (Dentan 1978: 111; Dunn 1974: 385; Kramer and Greaves 2007: 720; Le Mort 2008: 25). The first-century CE philosopher Epictetus cautioned, “When you kiss your child, say to yourself, it may be dead in the morning” (Stearns 2010: 168).

"Extrapolating from these figures I’d guess that miscarriages and stillbirths were also common by comparison with modern, post-industrial society. And I’d expect that if half the children died, then the majority were seriously ill in childhood. Indeed, in many villages studied by anthropologists the level of clinical malnutrition is 100 percent, as is the level of chronic parasite infestation and diarrhea. There are, then, ample reasons for withholding investment in the infant and maintaining a degree of emotional distance.”

“Humans have always had to cope with the loss of infants, and societies have developed an elaborate array of “cover stories” to lessen grief and recrimination (Martin 2001: 162; Scrimshaw 1984: 443). As discussed in the previous chapter, the primary strategy is to treat the infant as not yet fully human. Most importantly, if the baby is secluded initially and treated as being in a liminal state, its loss may not be widely noted.”

Some societies believed repeated miscarriages or stillbirths were caused by demons, and treated them with various attempts at exorcism. “It should be understood that these folk theories and treatments not only serve to dampen the sense of grief or loss but, more importantly, they deflect blame from the living. The Nankani have constructed an elaborate myth of the “spirit child not meant for this world” to explain away the tragedy of mother or infant death in childbirth and/or chronic infant sickness and, eventually, death (Denham 2012: 180). The alternative to, in effect, blaming the deceased child or “evil forces” is to blame the parents or other family/community member.”

“While new mothers may be evaluating the actuarial odds, we know that many are also suffering from post-partum depression or, less severely, detachment from and indifference toward their offspring. An argument can be made that this failure to bond immediately with the infant is adaptive in that it permits the mother to keep her options open, and also shields her emotionally from the impact of the infant’s death – often, a likely outcome (de Vries 1987a; Eible-Eibesfeldt 1983: 184; Hagen 1999; Konner 2010: 130, 208; Laes 2011: 100).”

“In the Himalayan kingdom of Ladakh, high-altitude living imposes an extra cost on the expectant mother who does farm-work throughout her pregnancy. Her infant’s life chances, owing to inevitably low birth-weight and other complications, are sharply reduced (Wiley 2004: 6). The worth of a new child in Ladakh will always be calculated as a tiny fraction of that of his fully mature, productive mother. While the mother’s health is closely monitored and she is treated with great solicitude, her infant’s fate is of less concern. Its death will be “met with sadness, but also with a sense of resignation … they are buried, not cremated like adults” (Wiley 2004: 131–132).”

“It is not unusual for the [Ayoreo] newborn to remain unnamed for several weeks or months, particularly if the infant is sickly. The reason given is that should the child die, the loss will not be so deeply felt. (Bugos and McCarthy 1984: 508)”

“Being a “calculating” mother is not synonymous with wickedness; on the contrary, it is adaptive behavior. While the well-to-do mothers in the first section seem to “live for their children,” in the next section, we discover just how recently these attitudes have become incorporated in Western society. We will trace the fluctuating value of infants in history and see that what we now consider horrible crimes were, in earlier periods, the principal means of birth control.”

In ancient Greece, “Illegitimacy was usually a death sentence. “Identity was given by the family, and without a recognized father and family, the child had no proper guardian (kurios) since its mother could not legally fulfill such a function. Without a father, the child had no true place in the patrilineal kin structure, no right to the family name” (Patterson 1985: 115). Until at least the end of the eighteenth century, any Venetian infant of questionable parentage would have been abandoned or destroyed (Ferraro 2008).”

“While the termination of the fetus or of the infant’s life is most often the parents’ decision and we’ve seen numerous possible reasons for this behavior, societies often legitimize that decision. Overpopulation, the burden on the community of a hard-to-raise child, the social disharmony created by illegitimacy: all give the society a stake in this critical decision. Ultimately, also, the community must value the life and emotional wellbeing of its experienced, productive adult females over any potential value a tiny infant might have.”

In foraging societies, “Both men and women face significant health and safety hazards throughout their relatively short lives, and they place their own welfare over that of their offspring. A survey of several foraging societies shows a close association between the willingness to commit infanticide and the daunting challenge “to carry more than a single young child on the nomadic round” (Riches 1974: 356).”

“The Inuit, among others, were known to cull females in anticipation of high mortality among males through hunting accidents, homicide, and suicide (Dickemann 1979: 341).”

Twins, being hard to nourish, were often discarded: “Mothers are unable to sustain two infants, especially where both are likely to be underweight. As Gray (1994: 73) notes, “even today, with the availability of western medical services it is difficult to maintain twins.” On Bali, which is otherwise extraordinary in its elevation of babies to very high esteem, giving birth to more than one child at a time is seen as evidence of incest. Priests consider the birth of twins as sub-human or animal-like (Lansing 1994; Barth 1993; Belo 1980). Similarly, the Papel (Guinea-Bissau) believe that it is mufunesa to give birth to many children at the same time like animals. Pigs have many offspring. Human beings give birth to only one each time. Therefore twins have to be thrown away. If not, the father, the mother, or somebody in the village may die. (Einarsdóttir 2004: 147).

Among the !Kung, Nancy Howell found that mothers whose toddlers had not been weaned might terminate the life of their newborn. In a society with high infant mortality (IM), an unweaned but otherwise thriving child is a better bet than a newcomer of unknown viability. The mother is expected by the band to kill one of a pair of twins or an infant with obvious defects. She would not be committing murder because, until the baby is named and formally presented in camp, it is not a person (Howell 1979: 120).

We can juxtapose this picture – paralleled in pre-modern communities the world over – with the almost legendary affection and love the !Kung show their young (Konner 2005). Similarly, Trobriand Island (Papua New Guinea) women, who also shower affection on their children, “were surprised that Western women do not have the right to kill an unwanted child … the child is not a social being yet, only a product manufactured by a woman inside her own body” (Montague 1985: 89).”

“In farming communities, additional farmhands are usually welcomed. Still, in rural Japan, a family would be subjected to considerable censure for having “too many” children and might find themselves ostracized if they failed “to get rid of the ‘surplus’” (Jolivet 1997: 118; see also Neel 1970). Bear in mind that breastfeeding is more costly – metabolically – than pregnancy (Hagen 1999: 331). In the impoverished northeast of Brazil, women can count on very little support from their child’s father, and their own resources are meager. Hence, “child death a mingua (accompanied by maternal indifference and neglect) is understood as an appropriate maternal response to a deficiency in the child. Part of learning how to mother … include[s] learning when to ‘let go’” (Scheper-Hughes 1987b: 190). Early cessation of nursing – one manifestation of the mother’s minimizing her investment – is supported by an elaborate folk wisdom that breast milk can be harmful, characterized as “dirty,”“bitter,”“salty,” or “infected.” Another folk illness category, doença de crianca, is used flexibly by mothers in justifying a decision to surrender the child into the hands of God or, alternatively, raise it as a real “fighter.” Of 686 pregnancies in a sample of 72 women, 251 infants failed to reach one year of age (Scheper-Hughes 1987a).”

“Long before the “one-child policy,” abortion was common in China. The oldest Chinese medical text found so far, some 5,000 years in age, includes reference to mercury as an abortifacient.”

I also hadn’t thought about traditional attitudes toward children with disabilities, or children (perhaps with autism) who don’t engage in eye contact, smiling, and other behavior that charms adults. “Hrdy (in press) suggests that the infant’s gaze-following and close attention to facial expressions and moods – along with a plump body and other neotenous features – are designed to send a clear signal to its mother and other caretakers: “Keep me!””

“In earlier times, the “difficult” or unwanted child might be dubbed a “changeling” or devil-inspired spirit, thereby providing a blanket of social acceptability to cloak its elimination (Haffter 1986). In cases where mothers are forced to rear unwanted children, the young may suffer abuse severe enough to end their life. While our society may treat such behavior by the parent as a heinous crime, “This capacity for selective removal in response to qualities both of offspring and of ecological and social environments may well be a significant part of the biobehavioral definition of Homo sapiens” (Dickeman 1975: 108).”

“Changelings represent a special sub-group of “demon” children who provoke a negative response from caretakers. The changeling was an enfant changé in France, a Wechselbag in Germany, and, in England, a “fairy child.” Strategies to reverse the switch included tormenting the infant or abandoning it in a lonely spot (Haffter 1986). A Beng mother-to-be who breaks a taboo may have her uterus invaded by a snake. The snake takes the fetus’s place and, after birth, is gradually revealed by the infant’s strange behavior. “The child may be harassed and hit by stones; however, being boneless like a snake, the snake-person is thought to feel no pain” (Gottlieb 1992: 145). A Papel infant deemed abnormal may be a spirit that’s entered the mother’s uterus. Two procedures are available to determine whether the child is human, but surviving either procedure seems improbable (Einarsdóttir 2008: 251). Dogon children thought to be evil spirits are taken: Out into the bush and you leave them … they turn into snakes and slither away … You go back the next day, and they aren’t there. Then you know for sure that they weren’t really [Dogon] children at all, but evil spirits. (Dettwyler 1994: 85–86) Among the Nuer, it is claimed, a disabled infant was interpreted as a hippopotamus that had mistakenly been born to human parents; the child would be returned to its proper home by being thrown into the river. (Scheer and Groce 1988: 28) In … northern Europe, changelings were left overnight in the forest. If the fairies refused to take it back, the changeling would die during the night – but since it was not human, no infanticide could have occurred. (Hrdy 1999: 465) [For Lurs] Djenn are said to be … jealous of the baby, especially during the first ten to forty days; they might steal the baby or exchange it for their own, sickly one. A baby indicates that it might be a changeling by fussiness, weakness, or lack of growth. (Friedl 1997: 69)”

Foragers vs. agriculturalists

Attitude toward children in general seems to vary by livelihood.

“In Central Africa, systematic comparisons have been drawn between foragers and farmers in the same region. Bofi-speaking foragers follow the !Kung model. Babies are carried or held constantly, by mothers and fathers, are soothed or nursed as soon as they cry, and may wean themselves after three to four years. Children are treated with the affection and respect consistent with preparing them to live in an egalitarian society where the principal subsistence strategy is cooperative net-hunting. Bofi-speaking farmers, on the other hand, tend not to respond as quickly to fussing and crying, are likely to pass the infant off to a slightly older sibling, and are verbally and physically abusive to children, who are treated like the farmhands they are soon to be.”

“The Garo, who live in the forests of Bengal, all share in infant and childcare, and parents “seldom roughhouse with their children, but play with them quietly, intimately, and fondly” (Burling 1963: 106). In the Northwest Territory of Canada, the Inuit (aka Eskimo) would never leave a child alone or let it cry for any length of time. Infants receive a great deal of solicitous care and lots of tactile comfort, anticipatory of “the interdependence and close interpersonal relations that are an integral part of Inuit life” (Condon 1987: 59; Sprott 2002: 54).

Draper observed a similar mindset operating among !Kung foragers in the Kalahar: Adults are completely tolerant of a child’s temper tantrums and of aggression directed by a child at an adult. I have seen a seven-year-old crying and furious, hurling sticks, nutshells, and eventually burning embers at her mother … Bau (the mother) put up her arm occasionally to ward off the thrown objects but carried on her conversation nonchalantly. (Draper 1978: 37)”

How children are expected to speak

“Clearly Euroamerican and Asian parents are preparing children to be more than merely competent native speakers. They encourage the development of narrative ability through frequent queries about the child’s activity, including their subjective assessments: “mothers pick up on children’s … topics, repeat and extend what their children say, and adjust their language … to support the child’s projects” (Martini 1995: 54). Toddlers are expected to hold and to voice their opinions! As parents seek “explanations” from their children, they also tolerate interruptions and contradiction (Portes et al. 1988). And this entire package of cultural routines is almost completely absent in the ethnographic record (Robinson 1988).

“In a Mayan community … children are taught to avoid challenging an adult with a display of greater knowledge by telling them something” (Rogoff 1990: 60). West African Wolof parents never quiz their kids by asking known-answer questions (Irvine 1978) – a favorite trick of Euroamerican parent-teachers. Fijian children are never encouraged to address adults or even to make eye contact. Rather their demeanor should express timidity and self-effacement (Toren 1990: 183).”

“Qualities we value, such as precocity, verbal fluency, independent and creative thought, personal expression, and ability to engage in repartee, would all be seen by villagers as defects to be curtailed as quickly as possible.25 These are danger signs of future waywardness. “Inquisitiveness by word or deed is severely censured, especially in [Kogi] women and children” (Reichel-Dolmatoff 1976: 283). “A [Sisala] child who tries to know more than his father is a ‘useless child’ (bichuola), for he has no respect” (Grindal 1972: 28). In rural Turkey the trait most valued by parents (60 percent) was obedience; least valued (18 percent) was independence (Kagitçibasi and Sunar 1992: 81).”

How do children learn?

“I discuss the prevailing view in WEIRD society – among most scholars as well as the public at large – that children’s development into mature, competent members of society depends critically on the guidance and lessons, beginning in infancy, provided by an eager parent who’s a “naturally gifted” teacher. Based on unequivocal evidence of the relative unimportance of teaching in the ethnographic record, I question that assumption as well as its evolutionary foundation.”

“De León (2012) records an episode from her Zinacantecan site where a three-year-old boy nearly runs, barefoot, through a fire. Adults do not react sympathetically. Instead, they comment that the child is flawed in not developing awareness of its surroundings, not paying close attention, and not figuring things out. There is an uneasy trade-off here. On the one hand, by indulging their curiosity about the environment and the things in it, parents insure that children are learning useful information without the necessity of parental intervention. This efficiency comes at a cost of the occasional damage to or loss of one’s offspring (Martini and Kirkpatrick 1992).”

“Active or direct teaching/instruction is rare in cultural transmission, and that when it occurs, it is not aimed at critical subsistence and survival skills – the area most obviously affected by natural selection – but, rather, at controlling and managing the child’s behavior.”

“Outside WEIRD or post-industrial society, this suite of parent–infant interaction patterns is rare. Mothers don’t often engage cognitively with infants, they may only respond contingently to their distress cues, and they probably do not gaze at them or engage in shared attention to novel objects (de León 2011: 100; Göncü et al. 2000; LeVine 2004: 161).”

In most traditional societies, children and young adults are expected to learn by observation rather than direct teaching.

In a Guatemalan indigenous community where people use a traditional learning style to approach factory work: “The newly hired worker performs menial tasks33 such as bringing material to the machine or taking finished goods off of it, but most of the time is spent observing the operations of the person running the machine. [The new worker] neither asked questions nor was given advice. When the machine snagged or stopped, she would look carefully to see what the operator did to get it back into motion … This constituted her daily routine for nearly six weeks, and at the end of this time she announced that she was ready to run a loom … and she operated it, not quite as rapidly as the girl who had just left it, but with skill and assurance … at no time during her learning and apprentice period had she touched a machine or practiced operating … She observes and internally rehearses the set of operations until she feels able to perform. She will not try her hand until she feels competent, for to fumble and make mistakes is a cause for verguenza – public shame. She does not ask questions because that would annoy the person teaching her, and they might also think she is stupid. (Nash 1958: 26–27)”

“I provide an extended example, of mother Sua and daughter Nyenpu each weaving a fishnet. As the vignette unfolded, the main point seemed to be how little interest Sua had in getting involved in Nyenpu’s weaving. Sua claimed that her stance was typical and replicated her own mother’s attitude when she was learning net-weaving. Several other informants told me of approaching experts for help and being rebuffed (Lancy 1996: 149–150). Other ethnographers report similar tales. Reichard describes a Navajo girl who learned to weave in spite of her mother’s repulsing her interest (1934: 38), which paralleled a case from Truk of a weaver/basket-maker whose kin were unsupportive of her efforts to learn their skills (Gladwin and Sarason 1953: 414–415), and a case from the Venda tribe where a potter is vehement that “‘We don’t teach. When women make pots some (children and others) come to watch, then go and try’” (Krause 1985: 95).”

A Javanese shellfish diver responds to the question of whether she learned the practice from her mother:

“My mother! she said loudly, She drove me away! I tried to follow her to the bottom to watch, but she shoved me back. When we were on the surface again, she practically screamed at me to move OFF and find my danged abalone BY MYSELF. So we had to discard [one] cliché about how artisans learn. (Hill and Plath 1998: 212)”

There are a few cases of explicit teaching:

“There are a few cases in the literature of grandmothers conducting educational tours through the bush to acquaint their younger kin with medicinal plants (Ngandu – Hewlett 2013: 76; Tonga – Reynolds 1996: 7).”

“An interesting “work-around” for the prohibition on teaching is provided by the Fort Norman Slave [Canada], who hunt during severe winter weather and must traverse ice-fields. Fathers “instruct” sons about this dangerous environment (which comprises thirteen kinds of ice and multiple modes of travel) via a game-like quiz (Basso 1972: 40).”

Analytic thinking

While there's a lot of knowledge being transmitted in traditional societies, like how to make and use a blowgun for hunting or how to hollow a canoe, analysis and taxonomy seem to be absent in societies where people haven't gone to school. Lancy cites Alexander Luria's 1930s interviews with peasants in Central Asia:

"In the first example we can see the villager reasoning from personal experience (or lack thereof) and inability or unwillingness to apply a general rule. 'Problem posed: 'In the Far North, where there is snow, all bears are white. Novaya Zemlya is in the far north and there is always snow there. What color are the bears?' Response: 'We always speak of only what we see; we don’t talk of what we haven’t seen.' (Luria 1976: 108)

In another problem, men and women were asked to sort and group various kinds and colors of weaving yarn (Uzbekistan is noted for its carpets). The male response was 'men [not being weavers] don’t know colors and call them all blue.' The women refused to impose any grouping or organization – something educated Uzbeks did quite easily – exclaiming that 'none of these are the same' (Luria 1976: 25, 27).

In a fishing community in Sulawesi, Vermonden found directly parallel results, with fishers resistant to discussing marine life more generally; they eschewed speaking of types of fish or of considering different ways of grouping them. Their thinking was governed by their practice (true also for Penan hunters – Puri 2005: 280 – and South American and African subsistence farmers – Henrich et al. 2010: 72). . . Had Vermonden’s informants been schooled, they might have used broader and more inclusive organizing principles and been able to display a more encyclopedic knowledge of fish." I assume that these people did in fact know a lot about fish, yarn, etc, which were their daily livelihood, but were used to thinking in practical terms.

(I was telling Jeff the bear example at dinnertime. "It's white," piped up our four-year-old without prompting. She's used to "known-answer questions" where grownups ask you things even though they know the answer.)

Learning to be street-smart

While children in some societies need to learn to avoid predators and poisonous plants, Lancy also briefly covers urban environments where children must be equipped for other dangers. "A mother in a favela of Rio de Janeiro knows “intuitively that in order for her children to survive, toughness, obedience, subservience, and street smarts are necessary; otherwise, the child can end up dead” (D. Goldstein 1998: 395)."

Charles Dickens depicts a similar strategy in 19th-century London, with a father describing how he's trained his son: “I took a good deal o’ pains with his eddication, sir; let him run in the streets when he was very young, and shift for hisself. It’s the only way to make a boy sharp, sir” (Dickens 1836/1964: 306)."

Learning through play

“Play is a truly universal trait of childhood. The one thing that children can appropriate for themselves, without the sanction of culture or explicit blessing of parents, is play. It is ubiquitous. A baby will play with its mother’s breast. The first glimmer of understanding about the natural world and how it works comes through play with objects. After its nurturing mother, the child’s first close relationships are with its playmates – usually siblings. The child’s first active engagements with the tasks that will occupy most of its adult life – hunting, cooking, house-building, baby-tending – all occur during make-believe.”

“Many of the child’s most basic needs seem to be fed by play – their need to socialize with peers and their need for physical, sensory, and, to a lesser extent, cognitive stimulation (Lancy 1980a). The demands of earning a living and reproduction gradually extinguish the desire to play. This happens earlier in girls than in boys – almost universally.”

Modern children:

“To encourage object play, we provide lots of toys, including safe, miniature tools, in various sizes, along with the dolls to use them. We also provide objects to play with that are specifically designed to facilitate the kind of cognitive complexity and flexibility that many assert is the raison d’être of object play (Power 2000). And, what is perhaps most remarkable, we sometimes intervene to “teach” our children how to use their toys or nudge them into more complex uses (Gaskins et al. 2007). I have found only one example of this in the ethnographic literature – a Wogeo father assisting his son with a miniature canoe (Hogbin 1946: 282) – and I am confident it occurs rarely. In research where the investigators created conditions designed to facilitate their involvement, East Indian and Guatemalan villagers would not intervene in their toddlers’ play (Göncü et al. 2000). It’s hard to escape the conclusion that our “micro-management” of children’s toys and play is driven by the inexorable demands of schooling.”

In contrast to play with specially provided objects, social play and pretend play are ubiquitous.

“Comparing across fifteen species of primates, observers found a statistically reliable relationship between cerebellum size and time devoted to social play (Lewis and Barton 2004; see also Fisher 1992).”

“This rapid growth in understanding – correlated with a rapidly growing brain – emerges in early childhood as two powerful motives. These are, first, to “fit in,” to be liked, appreciated, and accepted. The second motive force is a drive to become competent, to replicate the routine behaviors enacted by those who’re older and more capable. The presence of these drives accounts for the child’s ability to learn through observation, imitation, and, by extension, playing with objects and ideas in make-believe.”

“Esther Goody describes the richness and complexity of make-believe cooking in a village in north Ghana. Miniature kitchens are constructed, ingredients gathered, and soup made, all the while accompanied by singing and the construction of play scripts that mimic adult discourse. And, of course, the girls must insure that their play enfolds the younger siblings who are in their care. Boys have bit parts in these playlets as “husbands,” and are limited to commenting on the flavor of the soup (Goody 1992).

My kids and their cousins are avid mud-soup makers. Boys are full participants in this case

“Make-believe reveals children’s insight into the adult world. Araucania boys accurately mimic the speech and movements of drunken males celebrating fiesta (Hilger 1958: 106). Yanamamo boys pretend to “smoke” hallucinogens and then stagger around in perfect imitation of their stoned fathers acting as shamans (Asch and Chagnon 1974).”

Of course, an anthropologist in the village provides an interesting topic for pretend play: “Parenthetically, many an anthropologist has seen herself or himself reflected (unflatteringly) in the play of erstwhile subjects (Bascom 1969: 58).”

“The doll is arguably the most widely found toy and the range of materials used and designs employed is immense (Ruddle and Chesterfield 1977: 36).16 From rags tied into a shapeless bundle to high-tech baby dolls that produce a babble of baby-talk, wet themselves, and eagerly move their limbs, the variety is fascinating. While baby dolls seemed to have been a universal adjunct to Roman girls’ play, lower-class girls had infant dolls that they mock-nursed, comforted, and cleansed while upper-class girls, whose future as adults would not include childcare, dressed and primped the ancient equivalent of Barbie (Wiedemann 1989: 149–150).

Not all cultures encourage play

“Play may be seen as a sign of waywardness. Bulusu’ view play as naughty (jayil) and those who play “too much” as crazy (mabap) (Appell-Warren 1987: 160). Children may be scolded for getting dirty or telling stories they know aren’t true (e.g. fantasizing) (Gaskins et al. 2007: 192). On Malaita Island, where children are expected to carefully observe and report on newsworthy events in the village, children’s fantasy constructions are discouraged; they “are mildly reprimanded with ‘you lie’” (Watson-Gegeo and Gegeo 2001: 5).

Following the Protestant Reformation, many influential authorities condemned play in general as well as specific kinds of play, such as solitary play or contact sports. Morality came to be equated with decorum and emotional restraint; “indulging children was a cardinal sin” (Colón with Colón 2001: 284).

Similar sentiments were expressed by Chinese sages: Huo T’ao had no tolerance for play … as soon as a child is able to walk and talk, it must be taught not to play with other children. Children must practice treating one another as adults … When [children] see each other in the morning, they must be taught to bow solemnly to each other. (Dardess 1991: 76)”

When do parents play with young children?

Parents playing with babies varies a lot:

“An analysis of 186 archived ethnographies of traditional societies indicated wide variation in the amount of mother-infant play and display of affection (Barry and Paxson 1971). In a more recent comparative observational study, “Euro-American adults were much more likely than Aka or Ngandu adults to stimulate (e.g., tickle) and vocalize to their infants. As a result, Euro-American infants were significantly more likely than Aka and Ngandu infants to smile, look at, and vocalize to their care providers” (Hewlett et al. 2000: 164).21 Play with infants also seems generally less common among agrarian societies; for example, an Apache (North American agro-pastoralists) “mother sometimes plays with her baby … A father is not likely to play with a baby” (Goodwin and Goodwin 1942: 448). In hundreds of hours of close observation of parent–child interaction among Kipsigis (Kenyan) farmers, Harkness and Super (1986: 102) recorded “no instances of mothers playing with their children.””

“Among the !Kung, parents not only don’t play with their children post-infancy, they reject the notion outright as potentially harmful to the child’s development. They believe that children learn best without adult intervention (Bakeman et al. 1990: 796). The mother of a toddler not only faces potential conflict between childcare and work, she’s likely pregnant as well. I would argue that the mother’s greatest ally, at this point in the childrearing process, is the magnetic attraction of the sibling or neighborhood play group (Parin 1963: 48). The last thing a pregnant mother wants is for her child to see her as an attractive play partner. Even verbal play is avoided.”

I found this such a relief to read. The hardest stage of parenting for me was caring for an infant while being my two-year-old’s only regular playmate. She had an insatiable desire for stories, and I just wasn’t up for it.

Young monkeys play with each other, but chimpanzee mothers play with and tickle their babies.

“Why is the chimpanzee mother providing her baby with what monkey infants get from their peers? One clue in the direction of an answer may be the group structure of chimpanzees. I observed that chimpanzee mothers spend most of their time alone with their babies. As a consequence it is the chimpanzee mother who has to give her baby this sort of interaction if he gets it at all. (Plooij 1979: 237) "

Similar forces may promote mother–child play among humans. The small band of “Utkuhikhalingmiut [Inuit are] the sole inhabitants of an area 35,000 or more miles square” (Briggs 1970: 1). Aside from the almost total lack of other children to play with, the mother–child pair is isolated inside their igloo for days on end during the worst weather. Jean Briggs observed mothers talking to their children, making toys for them, playing with them, and encouraging their language development. Further, there is every reason to believe that modern living conditions in which infants and toddlers are isolated from peers in single-parent or nuclear households produce a parallel effect. That is, like chimps in the wild, modern, urban youngsters only have access to their mothers as potential play partners. In Japan, the mother–child pair has become quite isolated, sequestered in high-rise apartment buildings.”

This sounds very familiar to me.

Learning through chores

Learning to do the chores of adult daily life is of great interest to children everywhere.

“In the Giriama language the term for a child roughly two through three years in age is kahoho kuhuma madzi: a youngster who can be sent to fetch a cup of water … A girl, from about eight years until approximately puberty, is muhoho wa kubunda, a child who pounds maize; a boy of this age is a muhoho murisa, a child who herds. (Wenger 1989: 98)”

“Generally speaking, a girl’s working sphere coincides with that of her mother: the household, kitchen, nursery, laundry, garden, and market stall. (Paradise and Rogoff 2009: 113) depict a five-year-old Mazahua girl closely following her mother’s lead in setting up an onion stand in the market – trimming, bunching, and arranging their onions. When invited to establish a satellite onion stand, 'her excitement is unmistakable and she quickly takes the initiative in finding an appropriate spot and setting it up.'”

“In WEIRD society, parents and adults generally take every opportunity to instruct children, even when they are patently unmotivated or too awkward and immature. The term “scaffolding” may be used to describe the process whereby the would-be teacher provides significant assistance and support so that the novice can complete a task that is otherwise well beyond his grasp (McNaughton 1996: 178). Elaborate scaffolding is rarely seen elsewhere (Chapter 5). No one wants to waste time teaching novices who might well learn in time without instruction.”

“Little girls strap bundles of leaves on their backs as babies, boys build little houses … A little girl accompanying her mother to the fields practices swinging a hoe and learns to pull weeds or pick greens while playing about … Playing with a small gourd, a child learns to balance it on his head, and is applauded when he goes to the watering-place with the other children and brings it back with a little water in it. As he learns, he carries an increasing load, and gradually the play activity turns into a general contribution to the household water supply. (Edel 1957/1996: 177)”

“In the Sepik region of Papua New Guiena, Kwoma children eagerly embrace the piglets they’re given to protect, raise, and train (Whiting 1941: 47). Talensi boys are said to possess “a passionate desire to own a hen” (Fortes 1938/1970: 20).”

“The Touareg boy progresses from a single kid (at three years of age) to a herd of goats (at ten) to a baby camel (at ten) to a herd of camels (at fifteen) to managing a caravan on a trek across the Sahara (at twenty). Preferentially, the aspirant herder interacts with and learns from herders who are slightly older, not adults. Adults are too forbidding to ask questions of or display ignorance in front of. Above all, it is a hands-on experience, as “The abstract explanation so typical of our schooling is completely absent” (Spittler 1998: 247).”

“Four-year-old Bafin has already grasped the meaning of sowing and is able to perform the various movements … he is entrusted with an old hoe as well as with some seeds so that he can gain some practice in this activity. However … he has to be allocated a certain part of the field where he neither gets in the way of the others nor spoils the rows they have already sown … As a rule, his rows have to be re-done. (Polak 2003: 126, 129)”

This is one of the few passages that got at my concern about children’s involvement in chores: it usually creates more work for the parents. It did persuade me to let Anna load the dishwasher, which she does ineptly but avidly.

Chores vs. crafts

“I was surprised to discover that, in Gbarngasuakwelle, there is a gulf between the chore curriculum and what we might call the craft curriculum. The former is often compulsory – a child may be severely chastised or beaten for failure to complete appropriate chores satisfactorily. The latter is not only entirely voluntary, but children seem to be offered little encouragement in it. Indeed, they may be actively discouraged from trying to learn a craft or otherwise complex trade.”

“Somewhat later, the child may elect to move beyond the core skills expected of everyone to tackle more challenging endeavors such as learning pottery or weaving. She or he must demonstrate adequate strength, physical skill, and motivation before anyone will deign to spend time on his or her instruction.”

Rites of passage

Most traditional societies involve some initiation ceremony to mark the transition to adulthood, may involving “days of hazing, fasting, beating, sleeplessness, and sudden surprises.”

After being raised by women, boys’ rituals often focus on separating them from the world of women:

“One element that looms large in the training of male adolescents in much of Africa and Papua New Guinea is misogyny, as noted above. There is a distinct focus on teaching boys to feel superior toward and contemptuous of women. The “text” of many messages conveyed to initiates is replete with references to women’s physical weakness relative to men and their power to pollute through menstrual and puerperal blood. Another tool in the men’s arsenal is the use of “secrets,” including sacred terms, rituals, locations, and objects such as masks. These “secrets” are denied to women on pain of death. For the Arapesh (Sepik Region), “initiation ceremonies [include] an ordeal followed by the novices being shown the secret paraphernalia … flutes, frims, paintings, statues, bullroarers” (Tuzin 1980: 26). Denying female access to powerful spirit forces aids in maintaining male hegemony. A Mehinacu girl “cannot learn the basic myths because the words ‘will not stay in her stomach’” (Gregor 1990: 484). Wagenia “women and girls belong to the social category of the non-initiated, from whom the secrets of initiation were carefully concealed” (Droogers 1980: 78).”

“Immediately following [the ordeal], the initiators drop their razors, spears, cudgels or what have you, and comfort the boys with lavish displays of tender emotion. What resentment the latter may have been harboring instantly dissipates, replaced by a palpable warmth and affection for the men who, moments before, had been seemingly bent on their destruction. As their confidence recovers itself, the novices become giddy with the realization that they have surmounted the ordeal. (Tuzin 1980: 78)”

“The Hitler Youth and the Soviet Young Pioneers both capitalized on the idealism and fanaticism characteristic of adolescence (Valsiner 2000: 295; see also Kratz 1990: 456). During the Cultural Revolution, Chinese authorities used the naturally “anti-social,” rebellious nature of adolescents in recruiting, training, and then setting them loose as “Red Guards” to destroy bourgeois, Western, or intellectual elements of Chinese society (Lupher 1995). Today, Muslim terrorist organizations easily recruit male and female adolescents to serve as suicide bombers. Again, there are fundamental biological and psychological aspects of adolescence that render them susceptible to group-think mentality. Normal standards of human decency are suspended, allowing them to commit crimes in the name of the group.”

Neither here nor there

The author describes the plight of young people who have been socialized away from their traditional cultures but not given anything good in exchange:

“Christian missions offer them the opportunity to escape the restrictions imposed by traditional rites associated, in the Sepik area, with the men’s Haus Tambaran, without successfully socializing them to embrace Western/Christian values. Similarly, in attending government schools, young males signal their abandonment of the traditional agrarian economy without actually learning enough to secure a job in the modern economy. In short, they have been led to believe they are superior to the senior men, yet bring no significant resources to the community”

“Disaffected African students, their hopes for white-collar jobs dashed by stagnant economies, are easily recruited as “rebels” (Lancy 1996: 198) and street rioters (Durham 2008: 173). Terrorists and rebel armies capitalize on the peculiarities of adolescent psychology, brought on in part by “living in limbo,” to create pliable fanatics (Rosen 2005: 157). Rosen also notes the continuity between traditional Mende warrior training, described earlier in this chapter, and the recruitment and training of child soldiers.”

The decades-long Salvadoran Civil War raised a generation of men with no livelihood other than war:

“Initiation rites in the socialization of young rebels, unlike traditional rites, do “not facilitate their social transition into responsible adulthood” (Honwana 2006: 63). Similarly, in the Salvadorian civil war, young soldiers “were not given a chance to practice and learn how to be campesinos, dedicated to subsistence agriculture … and the lack of preparation for a new, adult peacetime identity led many youth to choose the negative identity of … marero [delinquent/gang member]. (Dickson-Gómez 2003: 344–345)”

“Similarly, adolescent males living on Indian reservations suffer mortality and suicide rates three times the national average.”

Traditional cultures meet Western schools

Western schools were historically places where knowledge is crammed and beaten into children.

4000 years ago a Sumerian student described his day: “My headmaster read my tablet, said: ‘There is something missing,’ caned me. ‘Why didn’t you speak Sumerian,’ caned me. My teacher said: ‘Your hand is unsatisfactory,’ caned me.’ And so I began to hate the scribal art” (Kramer 1963: 238–239).”

“Until fairly the 1970s, elite English boarding schools (and their US counterparts) for males weren’t all that different in terms of the constant hazing of younger by older boys, the emphasis on physical deprivation and removal from family, and daily engagement in team sports. This is probably what prompted Arthur Wellesley, the duke of Wellington, to remark: 'The battle of Waterloo was won on the playing-fields of Eton.'"

“The lamentations of passionate critics provide another window on the nature of schooling. These critics believed that the reluctant scholar problem could be solved by making schooling more like the experiences of the unschooled child, mixing in play, letting the child make choices, rewarding curiosity and independent learning. The fact that these pleas continue to appear over nearly two millennia suggests how enduring and intractable were the earliest ideas about the nature of schooling.”

“The idea that school should interest children was considered a radical new pedagogical philosophy in the United States of the 1840s”

But although the West has moved into a more child-centered mode, schools in the developing world remain on an old-fashioned model:

“As schools are introduced to formerly school-less communities, they much more closely resemble medieval schools than they do modern, progressive institutions. Bare, drafty classrooms, rote memorization, a scarcity of teaching materials, corporal punishment, unintelligible teachers, menial labor by students, the underrepresentation and exploitation of girls – all harken back to the dawn of schooling in the West.”

“Schools have encountered resistance from pupils who struggle to “sit still” or to meet the teacher’s gaze; from parents who’d prefer their children to be working and who reject their assigned role as “under-teacher,” prepping and supporting their child’s schooling; from patriarchal societies that impose limits on the choices available to women; and from the general public because of the very poor quality of instruction and the coercive atmosphere.”

“In a survey of childhood across history and culture, the suite of practices and teaching/learning abilities associated with modern schooling is largely absent”

An anthropologist “marvels at how facile and active the Matses children are in the natural environment, compared to what she feels is her own ineptitude. She is cowed by three- and four-year-olds who competently paddle and maneuver canoes on the wide river. She observes young boys nimbly catching and handling enormous catfish (Figure 28). And then she is struck by the painful contrast between the children’s mastery of their natural surroundings and the great discomfort and incompetence they display in the classroom. She summarizes the dilemma as 'learning to sit still.'"

The demographic transition

400 years ago, a change began to happen in the Netherlands:

“In the seventeenth century, foreigners were already recording their astonishment at the laxity of Dutch parents … they preferred to close their eyes to the faults of their children, and they refused to use corporal punishment … foreigners remarked on something else: since the sixteenth century, most Dutch children – girls as well as boys – had been going to school. (Kloek 2003: 53)”

“John Locke – exiled to Holland in 1685–1688 – was profoundly influenced by what he saw. His treatise on childrearing, published in 1693, brought Dutch ideas on childcare to England (Locke 1693/1994). At the end of the eighteenth century, the Quakers also embraced population control and used various means to reduce their fertility. “The drop in the birth rate also reflected … a rejection of the view that women were chattels who should devote their adult lives to an endless cycle of pregnancy and childbirth” (Mintz 2004: 78).”

Dutch paintings of this era are no longer only stiff portraits, but depict families enjoying time together (though I'm not sure how much the cat is enjoying this experience.)

"Teaching a cat to read", Jan Steen, 1660s. Note the young teacher holds a switch - this is how lessons work even in the relaxed Netherlands.

In developing countries, traditional methods of spacing births may be discouraged, resulting in a baby boom:

“For example, from Malaita Island in the South Pacific, traditional Kwara’ae practice was to keep men separated from their nursing wives for at least a year. However, the “abolition of the tabu system and the ascendance of Christianity has meant that … ritual separation [is] no longer practiced” (Gegeo and Watson-Gegeo 1985: 240–241). As a result, fertility has jumped and families with ten to thirteen children are not uncommon.”

Western intervention has addressed one aspect of population but not another: “The agencies that intervened to reduce infant mortality were not as ready with contraception and family-planning interventions, and the result has been masses of humanity living on the ragged edge of poverty.”

Even where it's available, people may not be interested in birth control, despite the practical difficulties of raising lots of children. In Burkina Faso:

"There are no perceived disadvantages in having lots of children. Children are never seen as a drain on resources. The availability of food is believed to be purely a product of the God-given fortune of the child, and nothing to do with the level of resources available within the household or the number of mouths to feed [because] 'every child is born with its own luck.' (Hampshire 2001: 115)"

The author gets editorial at times, quipping "The rich get richer, and the poor get lots of sickly children."

“Unfortunately, the ubiquity of infant death along with well-established coping mechanisms inures people to a phenomenon that, given the state of medical knowledge and a pharmacopeia adequate to the task, shouldn’t be happening. The wastage of young human life and the debilitating impact this has on mothers are staggering and cannot possibly be justified. And, in the West, we remain largely oblivious of the problem of child malnutrition and death in the Third World until it reaches such proportions that the story becomes newsworthy.”



Discuss

Preface to the sequence on economic growth

27 августа, 2020 - 18:37
Published on August 27, 2020 3:37 PM GMT

On Lesswrong, when we talk about artificial intelligence, we tend to focus on the technical aspects, such as potential designs, specific developments, and future capabilities. From an engineering perspective, this focus makes sense. But most people here aren't interested in artificial intelligence because they want to know how AI will be designed; the reason we're here is because AI has the potential to radically reshape the world around us.

Longtermists have often emphasized the role economic growth plays as perhaps the most important phenomena of human history. In a quite real sense, economic growth is what distinguishes 21st century humanity from our distant ancestors who had no technology or civilization. Nick Bostrom summarizes this point well,

You could argue that if we look back over history, there have really only been two events that have fundamentally changed the human condition, the first being the Agricultural Revolution some 10,000 or 12,000 years ago in Mesopotamia, where we transitioned from being hunter-gatherers, small bands roaming around, to settling into cities, growing, domesticating crops and animals. [...]The second fundamental change in the human condition, Industrial Revolution, where for the first time, you have the rate of economic and technological growth outstripping population growth, and so only when this happens can you have an increase in average income. Before that, there was technological growth and economic growth, but the economy grew 10%, the population grew 10%, everybody's still in a Malthusian condition.

Many theorists anticipate that there will be a third fundamental change in the human condition, roughly timed with the development of advanced artificial intelligence. In line with these predictions, economic growth is the primary specific benchmark people have used to characterize potential future AI takeoff.

If economic growth is the essential variable we should pay most attention to when it comes to AI, then our understanding of AI takeoff will be woefully incomplete without a grasp of what drives economic growth in the first place. To help mitigate this issue, in this sequence I will explore the underpinnings of modern economic growth theory, and then try to relate economic theory to AI developments. In doing so, I aim to identify crucial pieces of information that may help answer questions like,

  • How much technological progress in the past has been bottlenecked by investment as compared to insights?
  • How soon after advanced AI is created and turned on should we expect rapid economic progress to follow? Is there typically a large lag between when technologies are first demonstrated and when they heavily impact the economy?
  • What are the key factors for why AI is different from other technologies in its ability to induce rapid growth? Is it even different at all?

To provide one specific example of how we can import insights from economic growth theory into our understanding of AI, consider the phenomenon of wealth inequality between nations in the world. Wealth inequality between nations is ultimately the result of historical economic growth inequality, but things weren't always so unequal. Before the industrial revolution, per-capita wealth was approximately equal for all civilizations--at subsistence level. This state of affairs only changed when economic growth began to outstrip population growth in some nations during the industrial revolution.

AI takeoff can also be described in terms of growth inequality. A local (foom) intelligence explosion could be defined as an extremely uneven distribution of economic growth following the creation of superintelligent AI. A global (multipolar) takeoff could therefore be defined as the negation of a local intelligence explosion, where economic growth is distributed more evenly across projects, nations, or people.

Before we answer the important question of which version of AI takeoff is more likely, it’s worth recognizing why historically, growth inequality began after the industrial revolution. The factors that drove growth in the past are likely the best keys for understanding what will drive it in the future.

Organization of the sequence

Below, I have included a rough sketch of this sequence. It is organized into three parts.

The first part will provide the basic mechanics behind models of economic growth, and some standard results, with an emphasis on the factors driving technological innovation. Upon some research, and a recommendation from Alex Tabarrok’s blog, I have chosen to summarize the first several chapters of The Economics of Growth by Philippe Aghion and Peter Howitt.

The second part will dive into a recently developed economic model under the name Unified Growth Theory which the creator Oded Galor claims is the first major attempt to model the deep underlying factors driving economic growth throughout human history, cohesively explaining the onset of the industrial revolution and the emergence of the modern growth era. To provide some credibility here, the book introducing the theory has been reviewed favorably by top growth researchers, and Oded Galor is the editor in chief of the Journal of Economic Growth.

The third part will connect economic growth theory to artificial intelligence. Little research has been done so far examining the key economic assumptions behind the AI takeoff hypothesis, and thus it is possible to get a comprehensive survey of the published work so far. I will review and summarize the main papers, hopefully distilling the main insights generated thus far into a few coherent thoughts.

Other ways economic growth is relevant

Besides being a fixture of how people characterize AI takeoff, economic growth is potentially important for effective altruists of all backgrounds. For instance, in an effective altruism forum post, John Halstead and Hauke Hillebrandt argue that effective altruists have given short shrift to evidence that the best way to reduce poverty is to spur economic growth, rather than to distribute medicine or cash directly.

Economists have characterized the impacts of climate change primarily by its effects on growth, which has important implications for how much we should prioritize it in our longtermist portfolio. Similar statements can be made about the relative priority of pandemics, recessions, and in general a wide variety of global issues.

Economic growth is also just a critical piece of the human story. Without a basic understanding of growth, one's understanding of history is arguably horrible. From Luke Muehlhauser,

Basically, if I help myself to the common (but certainly debatable) assumption that “the industrial revolution” is the primary cause of the dramatic trajectory change in human welfare around 1800-1870 then my one-sentence summary of recorded human history is this:"Everything was awful for a very long time, and then the industrial revolution happened."Interestingly, this is not the impression of history I got from the world history books I read in school. Those books tended to go on at length about the transformative impact of the wheel or writing or money or cavalry, or the conquering of this society by that other society, or the rise of this or that religion, or the disintegration of the Western Roman Empire, or the Black Death, or the Protestant Reformation, or the Scientific Revolution.But they could have ended each of those chapters by saying “Despite these developments, global human well-being remained roughly the same as it had been for millennia, by every measure we have access to.” And then when you got to the chapter on the industrial revolution, these books could’ve said: “Finally, for the first time in recorded history, the trajectory of human well-being changed completely, and this change dwarfed the magnitude of all previous fluctuations in human well-being.”

Discuss

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