Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: How to kick-start 10 university groups in 6 months, published by Amarins on June 9, 2022 on The Effective Altruism Forum.

Okay, so the title is a bit clickbait-y. But over the past months, EA Netherlands really has been trying to seed groups at all 12 universities in the country. Many people have asked us how we're going about this, so we did a write-up of the steps we took and why we think this is worth our time. We hope this inspires other national community builders to start incubating groups as well!

A big thank you to Rob Gledhill, Jessica McCurdy, Jesse Rothman, James Herbert, Robert Praas and Joris Pijpers for providing feedback on this post!

Why do we want to do this in the first place?

The first Dutch university group (PISE) was quite successful. Since its founding two years ago, more than a hundred students have completed fellowships and more than twenty attended EAGx conferences. In addition, over a dozen members are currently truly enthusiastic about EA-careers. This showed us that Dutch universities are fertile ground for EA groups, and we wanted to replicate that success eleven more times.

Now, if you’re already familiar with why university groups are great, please skip over the list that follows. But if you’re not convinced of this idea yet, here are some reasons why launching university groups might be particularly impactful:

Universities are dense clusters of talented, flexible people. Historically, most EAs also first heard about EA during their early twenties. Furthermore, local groups in general are an important way for people to first hear about EA and to stay engaged thereafter.

Recent research suggests that most students who might like EA ideas haven’t heard of EA yet (spoiler: only 14.5% of EA-sympathetic students knew what EA is). Starting university groups that do outreach to their peers seems like a great way to fix this!

Over the past year, some amazing resources for running university groups have been created (e.g. GCP’s Handbook, Resource Center, OpenPhil). However, one of the main bottlenecks seems to be that many students who find EA interesting don’t know of any other EAs in their area. National and regional community builders are uniquely positioned to find and connect multiple of those EA-interested students, so they can start a group together - thereby complementing the existing services to launch and run university groups.

To this end, EA Netherlands set out to seed groups at all universities and prepare them for CEA’s University Group Accelerator Program (UGAP). Just to refresh your memory: UGAP is a program that provides new groups with a mentor, a stipend and game plan for their first semester. Handing the newly seeded groups over to UGAP after a few months ensures that they get specialized support during the crucial first year, while freeing up our time as national community builders to do other things!

So what’s the situation in the Netherlands?

Almost all Dutch universities are in the top 200 worldwide and most of them are even in the top 100. In addition, there is no university that is clearly more prestigious than the others (as their relative ranking often changes and is subject-dependent). As such, we believe that there is significant value in establishing EA groups at all Dutch universities, rather than at just a few.

In addition, student-run organizations are an important part of student life in the Netherlands. Being part of a board or subcommittee is very common, and is often viewed as an important part of your personal development. This means that there is a very good chance that groups will be able to continue to thrive after their founders graduate.

So this is where we are at now: at the end of 2021, there was only one university group in the Netherlands (PISE). Less than half a year later, there are ten budding n...

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: You Only Get One Shot: an Intuition Pump for Embedded Agency, published by Oliver Sourbut on June 9, 2022 on The AI Alignment Forum.

This is a short attempt to articulate a framing which I sometimes find useful for thinking about embedded agency. I noticed that I wanted to refer to it a few times in conversations and other writings.

A useful stance for thinking about embedded agents takes as more primitive, or fundamental, 'actor-moments' rather than (temporally-extended) 'agents' or 'actors'. The key property of these actor-moments is that they get one action - one opportunity to 'do something' - before becoming simply part of the history of the world: no longer actual.

This is just one of the implications of embedded agency, but sometimes pulling out more specific consequences helps to motivate progress on ideas. It is an intuition pump, and, as with the exemplar archetype for intuition pumps, it does not tell the whole story and should be used with caution.

The Cartesian picture

It is often convenient to consider a decision algorithm to persist through time, separated from its environment by a Cartesian boundary. The agent receives (perhaps partial) observations from the environment, performs some computation, and takes some action (perhaps updating some internal state, learning from observations as it goes). The resulting change in the environment produces some new observation and the process continues.

This is convenient because it is often empirically approximately true for the actors we encounter[1].

Only one shot

In contrast, in reality, any act, and the concomitant changes in the environment, impinge on the actor (which is after all part of the environment), even if only in a minor way[2].

Taking an alternative stance where we imagine an actor only existing for a moment - having a single 'one shot' at action - can prompt new insights. In this framing, a 'state update' is just a special case of the more general perspective of 'self modification', which is itself a special case of 'successor engineering'. And all of these are part of the larger picture implied by the stance taking as more fundamental not 'actor' but 'actor-moment': wherein an actor makes a decision and so unfolds a particular future world trajectory, which may - or may not - contain relevantly-similar actor-moments.[3]

This stance is somewhat unnatural for many actors we encounter (and consider worthy of attention and conversation investment), because for the most part these have been selected for a semblance of self-integrity and durability, and so the Cartesian abstraction is a workable approximation. But departures from these modes, or attraction to additional modes of influence over subsequent actor-moments, may be more accessible to future agents, especially artificial ones[4].

Further, I have found this a useful stance for analysing existing and hypothetical systems, because it can prevent leaking intutions, and it provides an alternate framing to better understand systems-building-systems (some which already exist, and some which might some day exist).

Finally, as embedded agents ourselves, humans can sometimes get useful insights from taking this stance.

Related

Scott Garrabrant discusses Cartesian Frames which I think are a related (and more fleshed out) conceptual tool.

Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: How Do Selection Theorems Relate To Interpretability?, published by johnswentworth on June 9, 2022 on The AI Alignment Forum.

One pretty major problem with today’s interpretability methods (e.g. work by Chris Olah & co) is that we have to redo a bunch of work whenever a new net comes out, and even more work when a new architecture or data modality comes along (like e.g. transformers and language models).

This breaks one of the core load-pillars of scientific progress: scientific knowledge is cumulative (approximately, in the long run). Newton saw far by standing on the shoulders of giants, etc. We work out the laws of mechanics/geometry/electricity/chemistry/light/gravity/computation/etc, and then reuse those laws over and over again in millions of different contexts without having to reinvent the core principles every time. Economically, that’s why it makes sense to pump lots of resources into scientific research: it’s a capital investment. The knowledge gained will be used over and over again far into the future.

But for today’s interpretability methods, that model fails. Some principles and tools do stick around, but most of the knowledge gained is reset when the next hot thing comes out. Economically, that means there isn’t much direct profit incentive to invest in interpretability; the upside of the research is mostly the hope that people will figure out a better approach.

One way to frame the Selection Theorems agenda is as a strategy to make interpretability transferable and reusable, even across major shifts in architecture. Basic idea: a Selection Theorem tells us what structure is selected for in some broad class of environments, so operating such theorems “in reverse” should tell us what environmental features produce observed structure in a trained net. Then, we run the theorems “forward” to look for the analogous structure produced by the same environmental features in a different net.

How would Selection Theorems allow reuse?

An example story for how I expect this sort of thing might work, once all the supporting pieces are in place:

While probing a neural net, we find a circuit implementing a certain filter.

We’ve (in this hypothetical) previously shown that a broad class of neural nets learn natural abstractions, so we work backward through those theorems and find that the filter indeed corresponds to a natural abstraction in the dataset/environment.

We can then work forward through the theorems to identify circuits corresponding to the same natural abstraction in other nets (potentially with different architectures) trained on similar data.

In this example, the hypothetical theorem showing that a broad class of neural nets learn natural abstractions would be a Selection Theorem: it tells us about what sort of structure is selected for in general when training systems in some class of environments.

More generally, the basic use-case of Selection-Theorem-based interpretability would be:

Identify some useful interpretable structure in a trained neural net (similar to today’s work).

Work backward through some Selection Theorems to find out what features of the environment/architecture selected for that structure.

Work forward through the theorems to identify corresponding internal structures in other nets.

Assuming that the interpretable structure shows up robustly, we should expect a fairly broad class of environments/architectures will produce similar structure, so we should be able to transfer structure to a fairly broad class of nets - even other architectures which embed the structure differently. (And if the interpretable structure doesn’t show up robustly, i.e. the structure is just an accident of this particular net, then it probably wasn’t going to be useful for future nets anyway.)

Other Connections

This picture connects closely to the converge...

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Thoughts on naming EA conferences, published by Kaleem on June 9, 2022 on The Effective Altruism Forum.

TLDR: We should revise our events naming strategy because the way we do it now does not adequately convey important info.

This is a short post expressing an opinion I hold having organised EAGxBoston, attended CEA's events retreat, and continue on providing advice to other EAGx organisers.

EAG vs EAGx:

It is worth having a discussion or getting some clarification about what the “x” in EAGx stands for.

In the past, it seems like the community has typically considered EAGxs to be an event which is smaller in scale, less professionally organized, and aimed at a different audience compared to EAGs (maybe EAGs are for highly engaged and/or experienced members of the community, whereas EAGxs are for those who are newer to EA, like people who had just completed an intro fellowship).

However a different interpretation of the distinction between the two might be seen similarly to the distinction between TED and TEDx events, where the “x” just denotes that the event is independently organized by people not employed by TED.

It is worth sorting this out because if we plan on having a lot more EA conferences and events in the coming years, we should make it clear to potential organizers and attendees what their options are.

Experience Level

If the “x” is to denote non-CEA organized events, then we should create a signal for the level of engagement of the event (if that should continue to be a thing) – maybe EAGxSummit for highly engaged/experienced members, and EAGxConference for newer members.

Cause Area specificity

Another thing to probably start thinking about is a list of topic tags which can be affixed to the end of conference names, now that members of the community are thinking about cause-area-specific events – e.g. The 2024 EAGx Bio Summit, The 2030 EAGx AI Conference.

I hope that the level of professionalism and polish of EAGxBoston 2022 will reset the EA community’s expectation/understanding of the “x” in EAGx, and that EAs of all levels of experience and professionalism will be more excited to attend EAGxs in the future.

Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: AI Could Defeat All Of Us Combined, published by HoldenKarnofsky on June 9, 2022 on LessWrong.

I've been working on a new series of posts about the most important century.

The original series focused on why and how this could be the most important century for humanity. But it had relatively little to say about what we can do today to improve the odds of things going well.

The new series will get much more specific about the kinds of events that might lie ahead of us, and what actions today look most likely to be helpful.

A key focus of the new series will be the threat of misaligned AI: AI systems disempowering humans entirely, leading to a future that has little to do with anything humans value. (Like in the Terminator movies, minus the time travel and the part where humans win.)

Many people have trouble taking this "misaligned AI" possibility seriously. They might see the broad point that AI could be dangerous, but they instinctively imagine that the danger comes from ways humans might misuse it. They find the idea of AI itself going to war with humans to be comical and wild. I'm going to try to make this idea feel more serious and real.

As a first step, this post will emphasize an unoriginal but extremely important point: the kind of AI I've discussed could defeat all of humanity combined, if (for whatever reason) it were pointed toward that goal. By "defeat," I don't mean "subtly manipulate us" or "make us less informed" or something like that - I mean a literal "defeat" in the sense that we could all be killed, enslaved or forcibly contained.

I'm not talking (yet) about whether, or why, AIs might attack human civilization. That's for future posts. For now, I just want to linger on the point that if such an attack happened, it could succeed against the combined forces of the entire world.

I think that if you believe this, you should already be worried about misaligned AI,1 before any analysis of how or why an AI might form its own goals.

We generally don't have a lot of things that could end human civilization if they "tried" sitting around. If we're going to create one, I think we should be asking not "Why would this be dangerous?" but "Why wouldn't it be?"

By contrast, if you don't believe that AI could defeat all of humanity combined, I expect that we're going to be miscommunicating in pretty much any conversation about AI. The kind of AI I worry about is the kind powerful enough that total civilizational defeat is a real possibility. The reason I currently spend so much time planning around speculative future technologies (instead of working on evidence-backed, cost-effective ways of helping low-income people today - which I did for much of my career, and still think is one of the best things to work on) is because I think the stakes are just that high.

Below:

I'll sketch the basic argument for why I think AI could defeat all of human civilization.

Others have written about the possibility that "superintelligent" AI could manipulate humans and create overpowering advanced technologies; I'll briefly recap that case.

I'll then cover a different possibility, which is that even "merely human-level" AI could still defeat us all - by quickly coming to rival human civilization in terms of total population and resources.

At a high level, I think we should be worried if a huge (competitive with world population) and rapidly growing set of highly skilled humans on another planet was trying to take down civilization just by using the Internet. So we should be worried about a large set of disembodied AIs as well.

I'll briefly address a few objections/common questions:

How can AIs be dangerous without bodies?

If lots of different companies and governments have access to AI, won't this create a "balance of power" so that no one actor is able to bring down civilization?

Won...

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Paths to Impact for EA Working Professionals, published by High Impact Professionals on June 9, 2022 on The Effective Altruism Forum.

Intro

The EA movement needs several career paths which can absorb a large number of people (as described in this recent forum post), that have clear paths to impact and are highly regarded by the community. We also believe that having support for those career paths can lead to EA having a bigger tent and generally allowing healthier community norms.

We believe that the for-profit career path done right can be one of those, as it can definitely absorb a lot of people and has many possible paths to impact as we will discuss below. However, for-profit careers are no longer so highly regarded in EA as they were in the past.

The goal of this post is to provide some inspiration to people in the private sector on possible ways to make a difference and support them on their journey to maximize their impact.

Our views on the best way to have an impact as an EA working in the private sector are bound to evolve as we get more data, however we believe the paths described below represent a good starting point for discussion.

Paths to impact

The diagram below shows several paths to impact available to EAs working in the private sector.

Let's briefly review each of them from left to right.

Money

This path is similar to the traditional earning to give, where part of one’s salary is donated to an effective organization. Strictly speaking, earning to give requires people to maximize their income and donate as much as possible, however according to the EA survey it seems much more common to donate a smaller portion like 10% and we believe that this can be done in any job, not only very high paying ones. Of course more is better, but more importantly something is better than nothing and it seems reasonable for people to start small and then increase over time.

Small donors might have a competitive advantage when it comes to funding new projects, which are still too small to attract bigger donors and would not take off otherwise. HIP is a good example, as half of our seed funding came from a private donor. The same holds true for many charities out of the CE incubation program and seems likely to be true in a number of cause areas for smaller charities.

We don’t see money and donations as the end game but more as a starting point, a stepping stone in the journey to increasing our impact.

Time/Skills

Professionals usually learn a range of skills in their job, skills that can be useful for EA organizations like management, communication, web development, how to scale an organization, etc. In fact many of the most reported gaps needed are directly connected to skills that are often built in the private sector. Therefore another way to contribute is by using our time and skills effectively, ranging from volunteering a few hours a week as an advisor or pro-bono worker in a specific domain, up to a more substantial side project and potentially shifting your career to an EA-aligned job. Later stage professionals who bring many of these skills to the table can benefit from volunteering as a stepping stone for a career shift, allowing people to “try before buying”, building credentials before making the jump and getting the psychological stamp of approval that indeed they are good enough to apply for an EA job.

We experienced that in several occasions both with people volunteering directly for HIP or other EAR organizations

Professional Influence

In EA using your influence is usually used in the context of influencing a government or policies. As an employee you also have influence over your company and this influence can be converted to impact in a few different ways.

Money

The first path is money again, this time the company’s money instead of your personal money...

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Has anyone actually tried to convince Terry Tao or other top mathematicians to work on alignment?, published by P. on June 8, 2022 on LessWrong.

This has been discussed several times in the past, see:

Have You Tried Hiring People?, a LW post

It talks about this ACX comment thread

Greg Coulbourn’s “Mega-money for mega-smart people to solve AGI Alignment”

Google Docs document

LW comment about the document

Short discussion on MIRI’s Facebook page

Thread on the EA forum

Comments arguing for Terence Tao specifically

Comment 1

Comment 2 with replies worth reading

But I’m not aware of anyone that has actually even tried to do something like this.

Of special interest is this comment by Eliezer about Tao:

We'd absolutely pay him if he showed up and said he wanted to work on the problem. Every time I've asked about trying anything like this, all the advisors claim that you cannot pay people at the Terry Tao level to work on problems that don't interest them. We have already extensively verified that it doesn't particularly work for eg university professors.

So if anyone has contacted him or people like him (instead of regular college professors), I’d like to know how that went.

Otherwise, especially for people that aren’t merely pessimistic but measure success probability in log-odds, sending that email is a low cost action that we should definitely try.

So you (whoever is reading this) have until June 23rd to convince me that I shouldn’t send this to his @math.ucla.edu address:

Title: Have you considered working on AI alignment?

Body:

It is not once but twice that I have heard leaders of AI research orgs say they want you to work on AI alignment. Demis Hassabis said on a podcast that when we near AGI (i.e. when we no longer have time) he would want to assemble a team with you on it but, I quote, “I didn’t quite tell him the full plan of that”. And Eliezer Yudkowsky of MIRI ([email protected]) said in an online comment “We'd absolutely pay him if he showed up and said he wanted to work on the problem. Every time I've asked about trying anything like this, all the advisors claim that you cannot pay people at the Terry Tao level to work on problems that don't interest them.”, so he didn’t even send you an email. I know that to you it isn't the most interesting problem to think about but it really, actually is a very very important and urgent completely open problem.

It isn’t simply a theoretical concern, if Demis’ predictions of 10 to 20 years to AGI are anywhere near correct, it will deeply affect you and your family (and everyone else).

If you are ever interested you can start by reading the pages linked in EA Cambridge’s AGI Safety Fundamentals course or the Alignment Forum.

Best of luck,

P.

You can do any of:

Reporting your past results.

Convincing me that this is a net negative on expectation.

The worst thing I can think of that can realistically happen is this leading to something like the Einstein-Szilard letter. But considering that Elon Musk has already tried to warn governments, I don’t think it would change much.

Arguing that it is important to wait until we have the results of the AI Safety Arguments Competition or something similar. I currently don’t think so, he should be convinced for the same reasons we are convinced.

Suggesting changes to the email or a new email altogether. If you think it is terrible, say so!

He declines many kinds of email requests, see points 5 and 12 here.

If you have more social capital than me (e.g. if you know him) or you work at an alignment organisation, volunteering to send the email yourself. He could think “If they actually care about hiring me, why aren’t they contacting me directly?”.

Saying under what conditions your organisation would be willing to hire him, so I can add it to the email.

What you probably shouldn’t do is ...

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Two Tiny Requests from HIA, Two Mins of your Time, published by Marcus Daniell on June 8, 2022 on The Effective Altruism Forum.

High Impact Athletes’ theory of change relies on using the collective athlete megaphone to convince a large percentage of the world’s high-income population to donate to cost-effective charities. Using our athletes’ voices and platforms we aim to raise the global profile of these giving opportunities and the philosophies behind them.

Sports fans are numerous, and the cultural clout of athletes has grown rapidly over the last century. According to MIT Media Lab, athletes made up 50% of all “historical cultural figures” between 1950 - 2000. We can use this influence to spread EA-aligned ideas.

In 18 months, HIA has grown from zero to over 110 athletes, with 46 of those athletes making at least a 1% pledge. Our second order audience (the amount of people we can reach through our athletes) is over 10.7 million, and we’re growing those numbers weekly.

The more big (popular) athletes we have on the HIA athlete roster, the louder the athlete megaphone, and the more people we can influence towards EA ideas.

To recruit bigger athletes we need standalone credibility as an organisation, particularly if we don’t have an existing personal connection. A large part of being credible in the athlete/influencer space is how big your social media following is.

This is where we’d love the EA community’s help.

Task 1Please take 30 seconds out of your day to follow our Instagram, Twitter and Facebook accounts. Then if you’re feeling particularly generous please take another 60 seconds to ask your friends to do the same!

More followers means more algorithm love, which might be the push that gets our posts noticed by prospective athletes. This is a low cost but potentially impactful action that each of you can take today!

Potential Questions:

Why don’t you just buy followers?We could, but these accounts are easy to spot and so the risk to our credibility/reward ratio isn’t great. We also want engagement with our account, and bought followers don’t engage the same way that organic ones do. We haven’t completely ruled this out (the ends might justify the means) but we want to see how far we can get organically first.

Why does social media matter?It’s the most common place where athletes interact with their fans - particularly Instagram. This interaction is where we have the largest potential to create change. Influencing 1% of 1 big athlete’s following could mean tens of thousands of people introduced to EA ideas for the first time.

Do you have growth plans other than asking individuals to follow your channels?In short, yes. We are working hard to increase engagement on our own channels and also build our second-order audience. However a small nudge from this supportive community would help a bunch.

Task 2Spend some time thinking if you, or anyone you know, knows any professional athletes or employees working in the sporting space. If you do, please introduce them to me at [email protected] - warm introductions are the fastest and most organic way to grow, and each athlete adds momentum to the HIA snowball.

I want to shout out 80,000 Hours and their employees for having passed on some athletes from their career advising program.

Cheers, Marcus and the HIA team.

Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Comparison between the hedonic utility of human life and poultry living time, published by Vasco Grilo on June 8, 2022 on The Effective Altruism Forum.

Summary

This analysis estimates the negative utility of poultry living time as a fraction of the utility of human life, under total hedonic utilitarianism (classical utilitarisnism).

The results are presented by country in this spreadsheet (see tab "TOC").

The conclusions are very sensitive to the moral weight of poultry birds relative to humans, and the quality of their living conditions in factory farms relative to fully healthy life. However:

In expectation, the (mean) negative utility of poultry living time seems much larger than that of human life.

Realistically, the (median) negative utility of poultry living time seems comparable to that of human life.

You can use this Guesstimate model to select your preferred inputs.

Acknowledgements

Thanks to Cynthia Schuck-Paim, Jason Schukraft, Lewis Bollard, Matt Sharp, Michael St. Jules and Scott Smith for feedback.

Methodology

The logic of the calculations is illustrated in this Guesstimate model. The tabs mentioned throughout the following sections refer to this spreadsheet.

Utility of human life

The utility of human life (QALY/person/year) was determined from the ratio between the healthy and full life expectancy. This is imperfect, but allows to estimate the utility of human life via a linear regression on life expectancy at birth:

The utility of human life was calculated through the mean life expectancy at birth of the years between 2025 and 2100 (see tab "Future utility of human life").

Data about the future life expectancy at birth was taken from OWID, and is in tab "Future life expectancy".

The linear regression coefficients were calculated based on data about the healthy and full life expectancy at birth from 1990 to 2016 (see tabs "Utility of human life and life expectancy" and "Past utility of human life").

Data about the past healthy life expectancy at birth was taken from OWID, and is in tab "Past healthy life expectancy".

Data about the past life expectancy at birth was taken from OWID, and is in tab "Past life expectancy".

Utility of poultry living time

The utility of poultry living time per capita (-QALY/person/year) is the product of:

The poultry living time per capita (pyear/person/year), which is the product between:

The poultry production per capita (kg/person/year).

The ratio between poultry living time and production (pyear/kg).

Moral weight of poultry (QALY/pQALY).

Quality of the living conditions of poultry (-pQALY/pyear).

The factors defining the poultry living time per capita were modelled as constants, and the ones regarding the moral weight and quality of the living conditions of poultry as distributions. The following sections provide further details.

The calculations of the utility of poultry living time per capita by country were performed in this Google Colab program, and the respective results uploaded to the tab "Utility of poultry living time per capita".

Poultry production per capita

The poultry production per capita between 2025 and 2100 (kg/person/year) was determined from the time-weighted average of those of the following periods:

2025 to 2050: mean between the poultry production per capita in 2025 and 2050.

2050 to 2100: half of the poultry production per capita in 2050.

The poultry production per capita in 2025 and 2050 was estimated from the ratio between the poultry production and population. The poultry production was calculated considering:

The poultry production by country in 2018 from OWID (see tab "Poultry production").

The poultry production annual growth rate by region, which was estimated by adding the following (see tab "Poultry production annual growth rate"):

Poultry population annual growth rate between 2005/2007 an...

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Comment reply: my low-quality thoughts on why CFAR didn't get farther with a "real/efficacious art of rationality", published by AnnaSalamon on June 9, 2022 on LessWrong.

Hi! I was writing this originally as a comment-reply to this thread, but my reply is long, so I am factoring it out into its own post for easier reading/critique.

This is more comment-reply-quality than blog post quality, so read at your own risk. I do think the topic is interesting.

Short version of my thesis: It seems to me that CFAR got less far with "make a real art of rationality, that helps people actually make progress on tricky issues such as AI risk" than one might have hoped. My lead guess is that the barriers and tricky spots we ran into are somewhat similar to those that lots of efforts at self-help / human potential movement / etc. things have run into, and are basically "it's easy and locally reinforcing to follow gradients toward what one might call 'guessing the student's password', and much harder and much less locally reinforcing to reason/test/whatever one's way toward a real art of rationality. Also, the process of following these gradients tends to corrupt one's ability to reason/care/build real stuff, as does assimilation into many parts of wider society."

Epistemic status: “personal guesswork”. In some sense, ~every sentence in the post deserves repeated hedge-wording and caveats; but I’m skipping most of those hedges in an effort to make my hypotheses clear and readable, so please note that everything below this is guesswork and might be wrong. I am sharing only my own personal opinions here; others from past or current CFAR, or elsewhere, have other views.

Conversational context, leading up to this post-length comment-reply:

I wrote:

In terms of whether there is some interesting thing we [at CFAR] discovered that caused us to abandon e.g. the mainline [workshops, that we at CFAR used to run]: I can't speak for more than myself here either. But for my own take, I think we ran to some extent into the same problem that something-like-every self-help / hippy / human potential movement since the 60's or so has run into, which e.g. the documentary (read: 4-hour somewhat intense propaganda film) Century of the Self is a pretty good introduction to. I separately or also think the old mainline workshops provided a pretty good amount of real value to a lot of people, both directly (via the way folks encountered the workshop) and via networks (by introducing a bunch of people to each other who then hit it off and had a good time and good collaborations later). But there's a thing near "self-help" that I'll be trying to dodge in later iterations of mainline-esque workshops, if there are later iterations. I think.

If you like, you can think with some accuracy of the small workshop we're running this week, and its predecessor workshop a couple months ago, as experiments toward having a workshop where people stay outward-directed (stay focused on inquiring into outside things, or building stuff, or otherwise staring at the world outside their own heads) rather than focusing on e.g. acquiring "rationality habits" that involve a conforming of one's own habits/internal mental states with some premade plan.

gjm replied:

You refer to "the same problem that something like every self-help / hippy / human potential movement since the 60s has run into", but then don't say what that problem is (beyond gesturing to a "4-hour-long propaganda film").

I can think of a number of possible problems that all such movements might have run into (or might credibly be thought to have run into) but it's not obvious to me which of them, if any, you're referring to.

Could you either clarify or be explicit that you intended not to say explicitly what you meant? Thanks!

And later, gjm again:

I'll list my leading hyp...