Harley-ml/lesswrong huggingface dataset:
# Spaced Repetition Systems for Intuitions?

I often see discussion here of [Anki](https://www.lesswrong.com/posts/cumc876woKaZLmQs5/lessons-i-ve-learned-from-self-teaching) or other [Spaced](http://cognitivemedium.com/srs-mathematics) [Repetition](http://augmentingcognition.com/ltm.html) [Systems](https://www.lesswrong.com/tag/spaced-repetition) for learning.  To me, these are great for "higher levels" of knowledge -- things more closely associated with System 2 than System 1.

*Are there similar advantages to be had (and systems that exist for) "lower levels" of knowledge?  *I think this would apply to things that are [implicit learning](https://en.wikipedia.org/wiki/Implicit_learning), [intuitions](https://en.wikipedia.org/wiki/Intuition), as well as System-1 level knowledge.

I want to distinguish this from "regular practice", which I don't think has spaced repetition qualities.

*   For example, meditation (to me) includes regular practice in equanimity -- I (so far) don't know of an effect where I can exponentially spread out my meditation practice to make it "last longer"
*   Running is another example, where regular practice makes me better, but I don't feel like I would get much out of exponentially spacing it (I think it could be argued that skill at running is only a small part "knowing" and largely other things like musculature, which would make this a bad example)

I would greatly value contributions of:

*   Studies looking at spaced repetition for intuitions/implicit learning/etc
*   Reasons why these might be possible or exist
*   Reasons why these might be impossible
*   Proposals to how to design experiments to test this
# Extracting Money from Causal Decision Theorists

My paper with my Ph.D. advisor Vince Conitzer titled "Extracting Money from Causal Decision Theorists" has been [formally published](https://doi.org/10.1093/pq/pqaa086) (Open Access) in *The Philosophical Quarterly*. Probably many of you have seen either earlier drafts of this paper or similar arguments that others have independently given on this forum (e.g., Stuart Armstrong [posted](https://www.alignmentforum.org/posts/Kr76XzME7TFkN937z/predictors-exist-cdt-going-bonkers-forever) about an almost identical scenario; Abram Demski's post on [Dutch-Booking CDT](https://www.alignmentforum.org/posts/X7k23zk9aBjjpgLd3/dutch-booking-cdt-revised-argument) also has some similar ideas) and elsewhere (e.g., [Spencer (forthcoming)](http://www.jackspencer.org/uploads/1/4/0/3/14038590/anaa037.pdf)  and [Ahmed (unpublished)](https://www.academia.edu/36270656/Sequential_Choice_and_the_Agents_Perspective?email_work_card=title) both make arguments that resemble some points from our paper).

Our paper focuses on the following simple scenario which can be used to, you guessed it, extract money from causal decision theorists:

> Adversarial Offer: Two boxes, $B_1$ and $B_2$, are on offer. A (risk-neutral) buyer may purchase one or none of the boxes but not both. Each of the two boxes costs $\$1$. Yesterday, the seller put $\$3$ in each box that she predicted the buyer not to acquire. Both the seller and the buyer believe the seller's prediction to be accurate with probability $0.75$.

At least one of the two boxes contains money. Therefore, the average box contains at least $\$1.5$ in (unconditional) expectation. In particular, at least one of the two boxes must contain at least $\$1.5$ in expectation. Since CDT doesn't condition on choosing box $B_i$ when assigning an expected utility to choosing box $B_i$, the CDT expected utility of at least one of the two boxes is at least $\$1.5$. Thus, CDT agents buy one of the boxes, to the seller's delight.

Most people on this forum are probably already convinced that (orthodox, two-boxing) CDT should be rejected. But I think the Adversarial Offer is one of the more convincing "counterexamples" to CDT. So perhaps the scenario is worth posing to your pro-CDT friends, and the paper worth sending to your pro-academic peer review, pro-CDT friends. (Relating their responses to me would be greatly appreciated – I am quite curious what different causal decision theorists think about this scenario.)
# AMA on EA Forum: Ajeya Cotra, researcher at Open Phil

Hi all, I'm [Ajeya](https://www.openphilanthropy.org/about/team/ajeya-cotra), and I'll be doing an AMA on the EA Forum (this is a linkpost for my announcement there). I would love to get questions from LessWrong and Alignment Forum users as well -- please head on over if you have any questions for me!

I’ll plan to start answering questions **Monday Feb 1 at 10 AM Pacific**. I will be blocking off much of Monday and Tuesday for question-answering, and may continue to answer a few more questions through the week if there are ones left, though I might not get to everything.

About me: I’m a Senior Research Analyst at [Open Philanthropy](https://www.openphilanthropy.org/), where I focus on cause prioritization and AI. 80,000 Hours released a [podcast episode with me](https://80000hours.org/podcast/episodes/ajeya-cotra-worldview-diversification/) last week discussing some of my work, and last September I put out a [draft report on AI timelines](https://www.lesswrong.com/posts/KrJfoZzpSDpnrv9va/draft-report-on-ai-timelines) which is discussed in the podcast. Currently, I’m trying to think about AI threat models and how much x-risk reduction we could expect the [“last long-termist dollar”](https://80000hours.org/podcast/episodes/ajeya-cotra-worldview-diversification/#last-dollar-project-022528) to buy. I joined Open Phil in the summer of 2016, and before that I was a student at UC Berkeley, where I studied computer science, co-ran the Effective Altruists of Berkeley student group, and taught a student-run course on EA.

I’m most excited about answering questions related to AI timelines, AI risk more broadly, and cause prioritization, but feel free to ask me anything!
# Less Wrong Poetry Corner: Coventry Patmore's "Magna Est Veritas"

[(Previously)](https://www.lesswrong.com/posts/trb9HPWFk8Gy9MBdN/less-wrong-poetry-corner-walter-raleigh-s-the-lie)

[This is my favorite poem that's](https://www.poemtree.com/poems/MagnaEstVeritas.htm) secretly about the necessity of _revealing information about deception!_

> Here, in this little Bay,  
> Full of tumultuous life and great repose,  
> Where, twice a day,  
> The purposeless, glad ocean comes and goes,  
> Under high cliffs, and far from the huge town,  
> I sit me down.  
> For want of me the world's course will not fail:  
> When all its work is done, the lie shall rot;  
> The truth is great, and shall prevail,  
> When none cares whether it prevail or not.  

Truth will win out in the end—_after_ no one has any remaining incentive to lie, because the liars have already gotten everything they wanted? Is that supposed to be comforting? I'm going to assume the contented tone is ironic, and that this is really a coded plea for the importance of _speed_. The truth is great and shall prevail ... and the work of rationality is to get it to prevail _faster_—the need of us to make the world's course fail.
# Play with neural net

I found [Tensorflow Playground](https://playground.tensorflow.org/) pretty cool to play with, in case anyone is looking for the kind of intuitive understanding of neural nets that futzing with a thing with one’s hands contributes to.

[![Tensorflow playground](https://hosting.photobucket.com/images/i/katjasgrace/Screen_Shot_2021-01-30_at_2.20.31_AM.png)](https://playground.tensorflow.org/)

One game you can play is pretending to be a training algorithm. How would you adjust the weights, if you wanted to classify which of two spirals a point comes from?
# Limiting Causality by Complexity Class

The standard account of causality depends on the idea of intervention:  The question of what follows if X not just naturally occurs, but we bring it about artificially independently of its usual causes. This doesn't go well with embedded agency. If the agent is part of the world, then its own actions will always be caused by the past state of the world, and so it couldnt know if the apparent effect of its interventions isn't just due to some common cause. There is a potential way out of this if we limit the complexity of causal dependencies.

Classically, X is dependent on Y iff the conditional distribution of X on Y is different from the unconditional distribution on X. In slightly different formulation, there needs to be a program that takes Y as an input and outputs adjustments to our unconditional distribution on X, and where those adjustments improve prediction.

Now we could limit which programms we consider admissible. This will be by computational complexity of the program with respect to the precision of Y. For example, I will say that X is polynomially dependent on Y iff there is a programm running in polynomial time that fullfills these conditions. (Note that dependence in this new sense needn't be symmetrical anymore.)

Unlike with the unlimited dependence, there's nothing in principle impossible about the agents actions being polynomially independent from an entire past worldstate. This can form a weakened sense of intervention, and the limited-causal consequences of such interventions can be determined from actually observed frequencies.

Now, if we're looking at things where all dependencies are within a certain complexity class, and we analyse it with something stronger than that, this will end up looking just like ordinary causality. It also explains the apparent failure of causality in Newcombs problem: We now have a substantive account of what it is to act in intervention (to be independent in a given complexity class). In general, this requires work by the agent. It needs to determine its actions in such a way that they dont show this dependence. Omega is constructed to make its computational resources insufficient for that. So the agent fails to make itself independent of Omega's prediction. The agent would similarly fail for "future" events it causes where the dependence is in the complexity class. In a sense, this is what puts the events into its subjective future - that it cannot act independently of them.
# AISU 2021

Welcome to the 3rd international **AI Safety Unconference**, which will take place **online, April 23rd - 28th**.

To learn more about this event and to register, head over to the official event webpage.

[**Click Here**](https://www.aisu.io/)
======================================

... or you can just keep reading I guess ...

### **Scope**

We are seeking to mitigate harm and risk from Artificial Intelligence, in the near term, the medium term, and the far future. AISU is a solution-focused event. We are gathering to solve these problems, with an open mind as to what the solution may be, and a willingness to engage with diverse suggestions.

Although the focus on the gathering is primarily technical, related topics such as safe human-AI interaction and policy considerations for AI Safety are also welcome.

### **What is an Unconference?**

An unconference is a participant driven symposium, designed to give you only the conversations that you are actually interested in. Instead of the program being decided by a committee, what happens will be chosen by the participants. Furthermore, to make sure to keep the focus on whatever is alive for you and the other participants, the program is decided right at the start of the unconference.

An unconference seeks to drive forward research and innovation by collaborating in ways that are beyond that which is offered in more traditional settings. Participants can share their own work and ideas, or make requests for what they want to learn about. These requests can then be filled by other participants. Sessions might be something like a brainstorming conversation, launching new project, discussing a contentious topic, or a technical review of completed research. All session formats are invited.

The most impactful breakthroughs in the history of science have come about through interactions such as these described above. Come to the Unconference to engage with your community in a meaningful way, without pretense, and full of energy.

### **Learn more and register**

As I said, head over to the official event webpage, it has a schedule, an FAQ page and everything.

[**Click Here**](https://www.aisu.io/)
======================================
# For those who advocate Anki

I just read the start of TurnTrout's Lessons from his self-teaching efforts and his mention of Anki made me wonder about something.

Spaced repetition is a bit of a take away from real life experience. Typically we don't use everything we're learned every day, we get a form a natural spaced repetition (albeit somewhat biased in what is repeated by our own lives).

I've been (perhaps more pretending here) studying Korean for a while but in many ways not really accomplishing much. I've got a very limited vocabulary that I can recall in a "study" type setting (flash cards, reading the specific lesson dialogue...), understand common verb conjugation, various particle markers the language uses, know the character set and okay at making the right sound.  But suggesting I have anything related to a working command of the language is a rather humorous fantasy in my view.

One challenge I have is I really don't know any Koreans so opportunities to practice in real life settings are very limited. I've decided that I will start using some of the online tutors to start making my self actualy **use** and so start really thinking and developing the "muscle" memory rather than just study, repeat saying, flashcards, online audio or Korean language shows.

Does anyone think that Anki is better than real life use for learning? Or is it perhaps more of a (possibly imperfect) substitute for when one cannot avail themself of a real life usage setting to apply what they have learned?
# Clarifications on tech stagnation

Five points of clarification regarding the “[technology stagnation](https://www.lesswrong.com/posts/gMszBSAX23uqYhytR/technological-stagnation-why-i-came-around)” hypothesis:

**It posits a slowdown relative to peak growth rates of ~100 years ago.** It doesn’t mean growth has gone to zero, and it doesn’t even mean that growth has slowed to where it was before the Industrial Revolution. (I said this in the original post but it bears repeating.)

**It is about the technological frontier and economic development in advanced countries.** It’s not about global development, which has not, as far as I know, been stagnating. The last fifty years have been [fantastic for India and China](https://ourworldindata.org/grapher/average-real-gdp-per-capita-across-countries-and-regions?time=1920..2016&country=CHN~IND), for example.

**It is about technology and economics, not science.** Or at least, scientific stagnation is a separate question, and one that I have a much less informed opinion about, and have not weighed in on. There is widespread discussion about physics being “stuck”, but biology seems to be making progress from what I can tell.

**It is descriptive and backwards-looking.** It is a hypothesis about the past, not a prediction for the future. And it is unrelated to optimism or pessimism. It is compatible with believing that slow growth is:

*   inevitable and permanent ([Gordon](https://rootsofprogress.org/summary-the-rise-and-fall-of-american-growth))
*   a phase we’re muddling through, and will soon get out of (which is how I interpret [Cowen](https://www.amazon.com/Great-Stagnation-Low-Hanging-Eventually-eSpecial-ebook/dp/B004H0M8QS) and [others](https://noahpinion.substack.com/p/techno-optimism-roundup))
*   a failing on the part of our culture that we need to correct (which is the impression I get from [Thiel](https://www.lesswrong.com/posts/Xqcorq5EyJBpZcCrN/thiel-on-progress-and-stagnation))

**It does not posit a cause, and certainly not a single, central, grand cause.** It’s just descriptive: has progress slowed? There could be multiple causes. I tend to think it is [a combination of](https://rootsofprogress.org/where-is-my-flying-car) the centralization and bureaucratization of research funding, over-regulation, and cultural attitudes turning against progress (not that these are unrelated).
# Oceans of snails

Somehow while knowing that a) ‘sea snail’ was a concept, and b) beaches were strewn with sea shells, which involve various snail-reminiscent spirals, I failed to reach the stunning conclusion that the oceans are substantially inhabited by these kinds of characters:

![land snail](https://hosting.photobucket.com/images/i/katjasgrace/krzysztof-niewolny-OxK32aLJXWU-unsplash.jpg)

But its true. And it seems that not only are the spiral-looking shells from snails, but various flat and non-spiral ones are too.

![Abalone](https://hosting.photobucket.com/images/i/katjasgrace/Abalone_OCA.jpg)

[Little Mountain 5](https://commons.wikimedia.org/wiki/File:Abalone_OCA.jpg), [CC BY-SA 3.0](https://creativecommons.org/licenses/by-sa/3.0), via Wikimedia Commons

![Julia exquisita](https://hosting.photobucket.com/images/i/katjasgrace/1024px-Julia_exquisita.jpg)

[Alexandre Laporte](https://commons.wikimedia.org/wiki/File:Julia_exquisita.jpg), [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0), via Wikimedia Commons

![snail](https://hosting.photobucket.com/images/i/katjasgrace/Truncatella_subcylindrica.jpg)

Image: Malcolm Storey, BioImages - the Virtual Fieldguide (UK) through the Encyclopedia of Life and the creative commons [CC BY-NC-SA](https://creativecommons.org/licenses/by-nc-sa/3.0/) license.

![Cowrie snail](https://hosting.photobucket.com/images/i/katjasgrace/1024px-Cypraea_caputserpentis.jpg) [NOAA (Photo Collection of Dr. James P. McVey, NOAA Sea Grant Program)](https://commons.wikimedia.org/wiki/File:Cypraea_caputserpentis.jpg), Public domain, via Wikimedia Commons

This is a meaningful update because snails are a particular kind of thing I’m familiar with, and furthermore I like them.
# Feedback for learning

I wish there were better (or more known to me) quantitative tests of skills that are good for me to have. I often find learning things when there is tight feedback pretty fun. For instance, I play [geography](https://www.sporcle.com/games/g/world) and [history](https://www.sporcle.com/games/kfastic/50-most-important-events-in-human-history) quizzes on [Sporcle](https://www.sporcle.com/) with an addictive vigor, and enjoy learning various languages on [Duolingo](https://www.duolingo.com/), and various facts via [Anki](https://apps.ankiweb.net/). I used to memorize poetry from the bathroom walls. But none of these seems that useful (in Anki I mostly learn about famous art and art movements). And meanwhile, I fail to know all manner of things that would be good to know, and forget most of what I read. (For instance, I’d like to know many more details of machine learning, how the US government works, and what happened in most of history, and I wish I remembered the details of _The Precipice_ or _The Better Angels of our Nature_ or even _War and Peace_—which I haven’t read much of, substantially because I keep losing track of what is going on or who the characters are.)

I feel like the situation was better in high school: there were contests and exams for all kinds of stuff that seemed decently useful, like math and chemistry. I guess one problem with my current situation is that because I learn things in a more distributed way, they don’t tend to come with a well matched test. A couple of times I have learned some math for instance, then looked for a suitable exam, but most exams don’t match the exact math that I learned. I suppose a solution might be to only learn things from places that also offer tests, but somehow this doesn’t sound great. Perhaps it is that the tests I found before didn’t seem that promising for rapid feedback anyway - you had to turn to a different page of a pdf or book and search through and check your own solutions. Imagine how much less fun Sporcle would be if instead of instantaneously responding to your touch, nothing happened until the end of a quiz, at which point it emailed you a pdf of the answers.

Some of this seems like it might have an easy solution that someone else knows about, at least for areas that are readily quantitatively examinable, such as math. So if I seem to be wrong, please correct me!

Do you know of well-gamified learning opportunities or tests for things that are worth studying?

I had fun practicing [calibration of predictions](https://www.openphilanthropy.org/calibration), which seems useful, until the app idiosyncratically broke for my account in a permanent way. I also recently noticed the existence of [Quantum Country](https://quantum.country/), which apparently teaches about quantum mechanics via essays with built in spaced repetition, so I’m also excited to try that.
# Lean Startup Reading Comprehension Quiz

Some colleagues and I recently read the [Lean Startup](http://theleanstartup.com/) together, and thought it'd be nice to have some reading comprehension questions to check if we took away the same things. Jacob made some questions, and I thought they might make an interesting LW post for other people who had read Lean Startup.

**Feel free to reply with spoiler-blocked (Begin a line with** `**>!**`**) answers.**

1\. What is the difference between learning and validated learning?

2\. True or false: "According to the author, a startup with exponential growth in metrics like revenue and number of customers is doing well." Explain your answer.

3\. Finish the sentence: "almost every lean startup technique we've discussed so far works its magic in two ways:"

4\. Ries argues that startups should pay more attention to innovation accounting than traditional accounting. Name two ways in which startups can change their financial metrics to accomplish innovation accounting.

5\. Describe, concretely, what a car company's supply chain would look like if it used push vs pull inventory.

6\. Ries applies the pull inventory model to startups. But what is the unit that is being pulled, and where does it obtain the "pull signal"?

7\. True or false: "Lean manufacturing is meant to give manufacturers an advantage in domains of extreme uncertainty". Explain your answer.

8\. True or false: "Lean manufacturing is about harnessing the power of economies-of-scale."

9\. Ries discusses an anecdote of a family folding letters. The dad folds, stamps, and seals one letter at a time; whereas the kids begin by folding all letters, then stamping all, etc. Name two reasons Ries' considers the dad's method superior.

10\. True or false: "A consequence of lean manufacturing is that the performance of each employee as an isolated unit, in terms of output per unit of time, might \*decrease\*." Explain your answer.

11\. Give an example of what a “large batch death spiral” might look like in practice. 

12\. According to Ries, the “Five why’s” method is a control system (though he doesn’t say so explicitly). What does it control, and how? 

13\. Explain the meaning of Toyota proverb “Stop production so that production never stops”
# Deepmind has made a general inductor ("Making sense of sensory input")

> Our system \[the Apperception Engine\] is able to produce interpretable human-readable causal theories from very small amounts of data, because of the strong inductive bias provided by the unity conditions. A causal theory produced by our system is able to predict future sensor readings, as well as retrodict earlier readings, and impute (fill in the blanks of) missing sensory readings, in any combination.

> We tested the engine in a diverse variety of domains, including cellular automata, rhythms and simple nursery tunes, multi-modal binding problems, occlusion tasks, and sequence induction intelligence tests. In each domain, we test our engine's ability to predict future sensor values, retrodict earlier sensor values, and impute missing sensory data. The Apperception Engine performs well in all these domains, significantly out-performing neural net baselines. We note in particular that in the sequence induction intelligence tests, our system achieved human-level performance. This is notable because our system is not a bespoke system designed specifically to solve intelligence tests, but a *general-purpose* system that was designed to make sense of *any* sensory sequence.

If we were to take AIXI literally, we'd be concerned that induction (the generation of predictive models from observation) appears to provide about half of general intelligence (the rest is decision theory). It also seems noteworthy that the models that the apperception engine produces are reductive enough to be readable to humans, a quality similar to being analyzable, classifiable, generally comprehensible enough to be intelligently worked as components in an intellectual medium, that is to say, they may be amenable to a process of self-improvement that is informed by consciously applied principles and meta-knowledge, which in turn might be improved in similar ways. So, we should probably pay attention to this sort of thing.
# OpenAI: "Scaling Laws for Transfer", Hernandez et al.

OpenAI has released a paper on scaling laws for transfer learning from general English text to python code. [Author's tweet summary](https://twitter.com/Hernandez_Danny/status/1357035777406853128).

Abstract: "We study empirical scaling laws for transfer learning between distributions in an unsupervised, fine-tuning setting. When we train increasingly large neural networks from-scratch on a fixed-size dataset, they eventually become data-limited and stop improving in performance (cross-entropy loss). When we do the same for models pre-trained on a large language dataset, the slope in performance gains is merely reduced rather than going to zero. We calculate the effective data "transferred" from pre-training by determining how much data a transformer of the same size would have required to achieve the same loss when training from scratch. In other words, we focus on units of data while holding everything else fixed. We find that the effective data transferred is described well in the low data regime by a power-law of parameter count and fine-tuning dataset size. We believe the exponents in these power-laws correspond to measures of the generality of a model and proximity of distributions (in a directed rather than symmetric sense). We find that pre-training effectively multiplies the fine-tuning dataset size. Transfer, like overall performance, scales predictably in terms of parameters, data, and compute."

​

![image](https://pbs.twimg.com/media/EtUoeTyU4AA6GjO?format=jpg&name=medium)

The power law they find is $D_T = k(D_F)^\alpha (N)^\beta$ with coefficients

![](https://39669.cdn.cke-cs.com/rQvD3VnunXZu34m86e5f/images/cee03386b9638e19c6a31a8f47d300721ba4eb01f4ab5479.png)
# Why are clinical trials so expensive?

While I know that clinical trials such as the trials for vaccines cost hundreds of millions of dollar, I have a hard time understanding why they are so expensive. I read about clinical trials for a vaccine costing 10,000/study participant. Given that the trials are so expensive they seem to be the bottleneck for medical progress. If we find a way to run them cheaper that would massively accelerate medical progress.

What resources do a good job at documenting the costs of clinical trials and how those high costs come about?
# Any layperson-accessible reference posts on how to operationalize beliefs ?

I'd like to find a shortish collection of advice, "do"s/"don't"s, aimed at... rationalist-adjacent folk?... for operationalizing beliefs into concrete anticipated experiences. My searches so far have been fruitless; I'd be grateful for any pointers!

(Context: I'm toying with a project aimed at encouraging people to operationalize their beliefs, i.e. turning vague beliefs like "Covid B117 will be disastrous" into relatively concrete predictions like "If the CDC publishes Covid sequencing data for any time period after June 1, it will show >70% of infections being B117 or a derivative." I would like to have one or more links handy to help people do it well.)

(Things that are _almost_ what I want: [Making Beliefs Pay Rent](https://www.lesswrong.com/posts/a7n8GdKiAZRX86T5A/making-beliefs-pay-rent-in-anticipated-experiences) is great, but is more of an exhortation than a how-to; [Keep Your Beliefs Cruxy](https://www.lesswrong.com/posts/BmyoYkr7u2oas4ukn/keep-your-beliefs-cruxy) likewise; [many](https://www.lesswrong.com/posts/exa5kmvopeRyfJgCy/double-crux-a-strategy-for-resolving-disagreement) [LW](https://www.lesswrong.com/posts/mQmx4kQQtHeBip9ZC/internal-double-crux) [posts](https://www.lesswrong.com/posts/Z7Sk29PDYTooipXMS/internalizing-internal-double-crux) assume familiarity with double-crux; and [Wikipedia:Operationalization](https://en.wikipedia.org/wiki/Operationalization) is aimed at scientists.)
# Meetup: Daniel Kokotaljo on Commitment Races (Sunday Feb 7th, 12pm PT)

This Sunday at noon PT, Daniel Kokotaljo will be running a meetup focused on the [commitment races](lesswrong.com/posts/brXr7PJ2W4Na2EW2q/the-commitment-races-problem) problem in AI. What is it? How does it relate to broader issues like equilibrium selection, bargaining, and multi-multi alignment? How dire is it? How should we go about trying to solve it?

From Daniel's post:

*Consequentialists* *can get caught in commitment races, in which they want to make commitments as soon as possible. When consequentialists make commitments too soon, disastrous outcomes can sometimes result. The situation we are in (building AGI and letting it self-modify) may be one of these times unless we think carefully about this problem and how to avoid it.*

This will be an online meetup, held in LessWrong's Walled Garden in Bayes Hall.

[http://garden.lesswrong.com?code=CBjh&event=daniel-kokotaljo-on-commitment-races-in-ai](http://garden.lesswrong.com?code=CBjh&event=daniel-kokotaljo-on-commitment-races-in-ai)

February 7th, 12pm PT
# Open & Welcome Thread – February 2021

If it’s worth saying, but not worth its own post, here's a place to put it.

If you are new to LessWrong, here's the place to introduce yourself. Personal stories, anecdotes, or just general comments on how you found us and what you hope to get from the site and community are invited. This is also the place to discuss feature requests and other ideas you have for the site, if you don't want to write a full top-level post.

If you want to explore the community more, I recommend [reading the Library,](https://www.lesswrong.com/library) [checking recent Curated posts](https://www.lesswrong.com/?view=curated), [seeing if there are any meetups in your area](https://www.lesswrong.com/community), and checking out the [Getting Started](https://www.lesswrong.com/posts/2rWKkWuPrgTMpLRbp/lesswrong-faq-1#Getting_Started) section of the [LessWrong FAQ](https://www.lesswrong.com/posts/2rWKkWuPrgTMpLRbp/lesswrong-faq-1). If you want to orient to the content on the site, you can also check out the new [Concepts section](https://www.lesswrong.com/tags/all).

The Open Thread tag is [here](https://www.lesswrong.com/tag/open-threads?sortedBy=new). The Open Thread sequence is [here](https://www.lesswrong.com/s/yai5mppkuCHPQmzpN).
# Current cryonics impressions

People around me often sign up for cryonics, and say that it is very important. My guess is that this argument for it, heavily inspired by [Waitbutwhy](https://waitbutwhy.com/2016/03/cryonics.html)’s much longer piece, as well as years of talking to people around me and reading [their](https://www.lesswrong.com/) [blogs](https://www.overcomingbias.com/), is correct:

**1\. One day people will probably live much longer than they do now.**

Probably we will work out how to beat the diseases of aging, as we have many of the infectious diseases. Eventually dying at age 90 of heart disease will seem as much of a needless tragedy as dying of an infection at age 45 does to us now.

**2\. One day we will probably be able to ‘freeze’ and usefully thaw organs like brains using vitrification.**

We can already do this with other organs. For instance [a rabbit kidney can apparently already be vitrified then warmed up and put back in a rabbit and work](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2781097/).

**3\. People can start to successfully evade the diseases of aging as soon as science reaches the freezing part of 2, even if it hasn’t got to the thawing part or to 1 yet.**

Because once you are vitrified, you can wait quite a long time for further developments.

There is a decent chance that we are already at the freezing part of 2. For instance, [a defrosted vitrified rabbit brain apparently appeared to be in good order](https://www.rt.com/news/332074-cryonics-rabbit-brain-regenerated/), though I assume we don’t know how to reattach brains to rabbits, alas.

The chance that we are there on the freezing is high enough that people dying soon (by our current standards of irrevivability) should generally be vitrified instead of burned or buried, if the chance to survive longer is worth the price to them.

You can sign up for something like this at the cost of a not-super-expensive life insurance policy, though I think the more promising techniques at the moment aren’t available yet to purchase.

I haven’t actually signed up for this, but I might, and if I thought there was a higher chance of me dying sooner, I would get around to figuring it out more urgently. So I thought I’d point it out to others older than me, who might want to think about it more promptly.

I found [Waitbutwhy](https://waitbutwhy.com/2016/03/cryonics.html)’s essay on these topics pretty good.
# Bring Back Free-Flow Valves

Over the past ~30y, manufacturers of small inflatables have switched to non-reflow valves. They should switch back to free-flow ones.

Here's what I'm talking about:

[![](https://www.jefftk.com/oral-inflation-bite-valve.jpg)](https://www.jefftk.com/oral-inflation-bite-valve-big.jpg)

See that little line on the valve, on the inside of the ball? In a resting position it's closed. If you squeeze it or bite it, it opens. You might see it called a "[check valve](https://en.wikipedia.org/wiki/Check_valve)", "bite valve", or "non-return valve". The goal is to make it easier to blow up, because when you're taking a breath the air mostly doesn't leak out.

The alternative is a free-flow valve, where the air goes in easily, and comes out just as easily. These require a small amount of technique: when you take a breath, you need to push your tongue gently against the opening, to keep the air from escaping.

I will admit, if you haven't learned this technique, the new way is easier. But even if you have the valve fully opened, it provides far more resistance to your breath than a free-flow.

Luckily, in many cases it is possible to remove the flap, converting it to flow freely. If you reach in with a pair of needle nose pliers, you may be able to grab the flap, twist it, and rip it free. I haven't ruined a valve doing this yet, though it is a risk, and I wouldn't do it on anything especially expensive.

For larger inflatables it's worth using a pump, but in my experience, for a given amount of effort I can blow up something up about four times bigger with a free-flow valve.

*Comment via: [facebook](https://www.facebook.com/jefftk/posts/10100205062295352)*
# Massive consequences

Hypothesis: whenever you make a choice, the consequences of it are almost as likely to be bad as good, because the scale of the intended consequences is radically smaller than the scale of the chaotic unintended effects. (The expected outcome is still as positive as you think, it’s just a small positive value plus a very high variance random value at each step.)

This seems different from how things are usually conceived, but does it change anything that we don’t already know about?

Could this be false?
# How do you optimize productivity with respect to your menstrual cycle? 

As the question asks, I am looking for productivity advice directly or indirectly related to one's menstrual cycle. 

**Motivation:** This may seem like a gross or weirdly personal question but I think it's actually quite important. For example, for the first four hours of my period, I am unable to do anything besides lie down, be in pain, and (sometimes) vomit for about 4 hours. Not accounting for all of the other ways my period negatively affects me, this is already 4 hours * 12 = 48 hours = **2 full days lost per year**. That being said, there can be menstruation related hormonal fluctuations which positively influence productivity. During ovulation, I can sometimes reach almost manic levels of mental and social energy and (I'm less sure about this) I require a bit less sleep to function. 

**What the question is asking:** This is a very open-ended and personal question so I am expecting similarly open-ended and personal answers. For example, stuff I'm interested in:

*   Generally speaking, how does your menstrual cycle affect your productivity? 
*   What effects has the pill had? Which kind of pill?
*   Have you experimented with varying your cycle length? (I had a 3 month cycle some number of years ago, and enjoyed the decreased frequency and intensity of my periods.)
*   Have you noticed fluctuations in energy level caused by your menstrual cycle? Any way to make the high energy phases longer and the low energy phases shorter? Do phases of high energy correspond to a certain hormone which I could get through the pill?
*   Are there dietary changes that mitigate the bad effects of menstruation / enhance the good effects? (For example, is it "helpful" to give in to cravings?)
*   Are there sleep schedule choices that can be made which synergize with your menstrual cycle?
*   Are there points in your cycle where you are best at detail-oriented work / creative work / socializing / writing / anything else relevant?

It's possible that your answers to many of these questions are "my menstrual cycle is irrelevant here because other inputs have way stronger effects". Insofar as your menstrual cycle has a sizeable effect on any of these points (or other points I haven't mentioned), I would be really interested in hearing your thoughts.
# Quadratic, not logarithmic

I recently realized a very simple, almost obvious bias, that I had because I never thought more about it. Moreover, quite a lot of people have this bias too.

What is worse in time of pandemic - to increase the number of your contacts from 0 to 1 or from 99 to 100? Intuitively, since we perceive many quantities on a logarithmic scale, the first thing is much worse. I heard multiple times something like: "I am already doing this and this and that because I have to, so it does not make sense for me to decrease my shopping", or "My roommate (spouse, child...) does not care about this at all, so it does not make sense for me either". 

However, this is simply not true. If I care solely about myself, increasing the number of contacts increases the probability to get sick linearly - no logarithmic scale. But if I also care about other people (my contacts, yes), then we have linear growth of probability to become a spreader, and linear growth of the group to whom I can spread, thus leading to *quadratic* growth of the total expected damage to society.

So, if I have quite a lot of contacts already, I should be much more cautious about adding more than if I have almost none. It sounds so trivial right now - yet so many times I have heard the opposite advice.
# The distinction distance

People have a strong tendency to be different from one another (e.g. are horrified to be caught in the same dress, find it weird to order the same dishes as their companion without comment or to choose the same art for their living room). Yet they also have a strong tendency to conform.

These are even in the same areas, and the best behavior seems to be balancing on an edge between the two forces. You don’t want to wear either a dress that someone else is wearing, nor a dress in a style that hasn’t been worn since the 1600s.

I have [noticed](https://meteuphoric.com/2017/12/08/rules-of-variety/) both of these human forces before, but I hadn’t seen them so vividly as acting in the same realm. You don’t want your essay to be on an identical topic to another student’s, but you also don’t want it to be outside the bounds of what the professor thinks of as an essay, or expressing views beyond a short hop from those others would endorse.

This makes me imagine the curlicues of culture as growing in the fertile interstitial zone between options too conformist to consider and options too wild to consider. Kind of like a Mandelbrot set or a tidal flat or a cellular automaton. There’s a similar pattern in the space of ways the whole of culture could have been: if everyone was very conformist about everything, it would be monotony, and if everyone immediately flung themselves as far away from anyone else as they could on every axis, it would be another kind of monotony. But with this balance of effects as it is, we get some complicated spiraling evolution of art movements and attitudes, trousers and tools. Each idea bringing forth riffs of of it in every direction.

Inspired by a conversation with Robin Hanson, where he probably basically said the main point here, that these two forces act in opposition.
# What metrics should I track when experimenting with sleep?

I used to sleep very little (6 hours or so) and function well with extremely good academic achievement. Instead of sleeping 8 hours now, I would love those extra 2 hours each day again but I'm not sure it won't affect my cognitive ability in the short term. I don't trust my impressions and would love to have some quantitative data.

*   What are areas that might be affected the most (e.g., long-term memory, working memory, speed of arithmetic calculations, vocabulary, reasoning, mood, etc.)?
*   What are some tasks that would measure my performance in those areas? Ideally those tasks should be:
    *   quick to perform
    *   easy to implement (I could write a quick program to run those but if there is a web app somewhere that does that already, that would be ideal)
    *   fine with the subject knowing what is being measured (I'm going to apply them to myself, after all)
    *   produce similar results regardless of how much experience I have with them (I don't want to wonder whether improvement/regression is due to the changes in my sleep or getting better/tired with the task.) It's ok if the skill builds over a week or so and then stays constant.

 I'm not attempting to prevent long-term negative consequences since AFAICT nobody knows what those might be. Besides, there are significant changes in my lifestyle every month or so and so there would be too much noise in the data.
# How would free prediction markets have altered the pandemic?

In [WebMD and the Tragedy of Legible Expertise](https://astralcodexten.substack.com/p/webmd-and-the-tragedy-of-legible), Scott Alexander ends by saying that we should be grateful for the experts we have, but that prediction markets would still be better.

Is he right? If so, *how much* better would prediction markets be? Let's do some counterfactual history. Conditional on large, liquid, free prediction markets being made suddenly available to the public in Nov 2019 (or April 2020, or any other date), what would have been the most likely pandemic outcomes? I'm interested in both vague and specific answers. Even better if you can estimate a quantity of money or life-years saved.
# We Need Browsers as Platforms

It's fashionable to say that the web is bloated, and that the features built to support webapps make it too complex. You [can divide](https://ar.al/notes/the-documents-to-applications-continuum/) [the web](http://theappslab.com/2010/11/12/website-vs-web-app/) into:

*   Documents: providing information. News, blog posts, documentation.
    
*   Apps: doing things. Email, spreadsheets, games.
    

(This is really a continuum, where a blog post with a comment section is pretty documenty but also a bit appy.)

On one hand, I completely agree that supporting apps makes the platform complex: browsers are incredibly complicated to build and work on, with such a high ongoing maintenance cost that we only have three rendering engines: Firefox's Gecko, Chrome's Blink, and Safari's Webkit (Blink is a fork of Webkit). On the other, supporting apps is much better than the alternatives.

Outside of a browser, there are essentially two models for getting applications:

*   Independent installation. You download the program for the manufacturers website, or loaded off a CD. The desktop model.
    
*   App store. Your OS has a list of programs that can be installed, and which have gone through some amount of review. The smartphone model.
    

Independent installation is decentralized, but also a security nightmare. Random users installing random software gives you botnets. App stores are centralized, which puts their operators in a position of enormous power over what users can run on their devices, and means governments can require them to [take down apps](https://www.buzzfeednews.com/article/meghara/pakistan-forced-down-ahmadiyya-apps).

The web has developed with the principle that it should always be [safe to visit a site](https://w3ctag.github.io/design-principles/#safe-to-browse). As new capabilities have been added this has been critical to maintain. This means you don't need an app store, with power to reject your app.

Ten years ago Mozilla [posted](https://groups.google.com/g/mozilla.dev.platform/c/dmip1GpD5II/m/CzJSSUMq5HsJ) [Booting to the Web](https://wiki.mozilla.org/Booting_to_the_Web):

> Mozilla believes that the web can displace proprietary, single-vendor stacks for application development. To make open web technologies a better basis for future applications on mobile and desktop alike, we need to keep pushing the envelope of the web to include—and in places exceed—the capabilities of the competing stacks in question.  
> ...  
> We want to take a bigger step now, and find the gaps that keep web developers from being able to build apps that are—in every way—the equals of native apps built for the iPhone, Android, and WP7.

The web platform has come so far in supporting apps over this decade; we couldn't have made [Bucket Brigade](https://echo.jefftk.com/) without [Web Audio](https://www.w3.org/TR/webaudio/) or [WebRTC](https://www.w3.org/TR/webrtc/). A web developer should be able to do anything native app developers can, making apps for any device, free from vendor veto.