In this "quick take", I want to summarize some my idiosyncratic views on AI risk.  My goal here is to list just a few ideas that cause me to approach the subject differently from how I perceive most other EAs view the topic. These ideas largely push me in the direction of making me more optimistic about AI, and less likely to support heavy regulations on AI. (Note that I won't spend a lot of time justifying each of these views here. I'm mostly stating these points without lengthy justifications, in case anyone is curious. These ideas can perhaps inform why I spend significant amounts of my time pushing back against AI risk arguments. Not all of these ideas are rare, and some of them may indeed be popular among EAs.) 1. Skepticism of the treacherous turn: The treacherous turn is the idea that (1) at some point there will be a very smart unaligned AI, (2) when weak, this AI will pretend to be nice, but (3) when sufficiently strong, this AI will turn on humanity by taking over the world by surprise, and then (4) optimize the universe without constraint, which would be very bad for humans. By comparison, I find it more likely that no individual AI will ever be strong enough to take over the world, in the sense of overthrowing the world's existing institutions and governments by surprise. Instead, I broadly expect unaligned AIs will integrate into society and try to accomplish their goals by advocating for their legal rights, rather than trying to overthrow our institutions by force. Upon attaining legal personhood, unaligned AIs can utilize their legal rights to achieve their objectives, for example by getting a job and trading their labor for property, within the already-existing institutions. Because the world is not zero sum, and there are economic benefits to scale and specialization, this argument implies that unaligned AIs may well have a net-positive effect on humans, as they could trade with us, producing value in exchange for our own property and services. Note that my claim here is not that AIs will never become smarter than humans. One way of seeing how these two claims are distinguished is to compare my scenario to the case of genetically engineered humans. By assumption, if we genetically engineered humans, they would presumably eventually surpass ordinary humans in intelligence (along with social persuasion ability, and ability to deceive etc.). However, by itself, the fact that genetically engineered humans will become smarter than non-engineered humans does not imply that genetically engineered humans would try to overthrow the government. Instead, as in the case of AIs, I expect genetically engineered humans would largely try to work within existing institutions, rather than violently overthrow them. 2. AI alignment will probably be somewhat easy: The most direct and strongest current empirical evidence we have about the difficulty of AI alignment, in my view, comes from existing frontier LLMs, such as GPT-4. Having spent dozens of hours testing GPT-4's abilities and moral reasoning, I think the system is already substantially more law-abiding, thoughtful and ethical than a large fraction of humans. Most importantly, this ethical reasoning extends (in my experience) to highly unusual thought experiments that almost certainly did not appear in its training data, demonstrating a fair degree of ethical generalization, beyond mere memorization. It is conceivable that GPT-4's apparently ethical nature is fake. Perhaps GPT-4 is lying about its motives to me and in fact desires something completely different than what it professes to care about. Maybe GPT-4 merely "understands" or "predicts" human morality without actually "caring" about human morality. But while these scenarios are logically possible, they seem less plausible to me than the simple alternative explanation that alignment—like many other properties of ML models—generalizes well, in the natural way that you might similarly expect from a human. Of course, the fact that GPT-4 is easily alignable does not immediately imply that smarter-than-human AIs will be easy to align. However, I think this current evidence is still significant, and aligns well with prior theoretical arguments that alignment would be easy. In particular, I am persuaded by the argument that, because evaluation is usually easier than generation, it should be feasible to accurately evaluate whether a slightly-smarter-than-human AI is taking unethical actions, allowing us to shape its rewards during training accordingly. After we've aligned a model that's merely slightly smarter than humans, we can use it to help us align even smarter AIs, and so on, plausibly implying that alignment will scale to indefinitely higher levels of intelligence, without necessarily breaking down at any physically realistic point. 3. The default social response to AI will likely be strong: One reason to support heavy regulations on AI right now is if you think the natural "default" social response to AI will lean too heavily on the side of laissez faire than optimal, i.e., by default, we will have too little regulation rather than too much. In this case, you could believe that, by advocating for regulations now, you're making it more likely that we regulate AI a bit more than we otherwise would have, pushing us closer to the optimal level of regulation. I'm quite skeptical of this argument because I think that the default response to AI (in the absence of intervention from the EA community) will already be quite strong. My view here is informed by the base rate of technologies being overregulated, which I think is quite high. In fact, it is difficult for me to name even a single technology that I think is currently clearly underregulated by society. By pushing for more regulation on AI, I think it's likely that we will overshoot and over-constrain AI relative to the optimal level. In other words, my personal bias is towards thinking that society will regulate technologies too heavily, rather than too loosely. And I don't see a strong reason to think that AI will be any different from this general historical pattern. This makes me hesitant to push for more regulation on AI, since on my view, the marginal impact of my advocacy would likely be to push us even further in the direction of "too much regulation", overshooting the optimal level by even more than what I'd expect in the absence of my advocacy. 4. I view unaligned AIs as having comparable moral value to humans: This idea was explored in one of my most recent posts. The basic idea is that, under various physicalist views of consciousness, you should expect AIs to be conscious, even if they do not share human preferences. Moreover, it seems likely that AIs — even ones that don't share human preferences — will be pretrained on human data, and therefore largely share our social and moral concepts. Since unaligned AIs will likely be both conscious and share human social and moral concepts, I don't see much reason to think of them as less "deserving" of life and liberty, from a cosmopolitan moral perspective. They will likely think similarly to the way we do across a variety of relevant axes, even if their neural structures are quite different from our own. As a consequence, I am pretty happy to incorporate unaligned AIs into the legal system and grant them some control of the future, just as I'd be happy to grant some control of the future to human children, even if they don't share my exact values. Put another way, I view (what I perceive as) the EA attempt to privilege "human values" over "AI values" as being largely arbitrary and baseless, from an impartial moral perspective. There are many humans whose values I vehemently disagree with, but I nonetheless respect their autonomy, and do not wish to deny these humans their legal rights. Likewise, even if I strongly disagreed with the values of an advanced AI, I would still see value in their preferences being satisfied for their own sake, and I would try to respect the AI's autonomy and legal rights. I don't have a lot of faith in the inherent kindness of human nature relative to a "default unaligned" AI alternative. 5. I'm not fully committed to longtermism: I think AI has an enormous potential to benefit the lives of people who currently exist. I predict that AIs can eventually substitute for human researchers, and thereby accelerate technological progress, including in medicine. In combination with my other beliefs (such as my belief that AI alignment will probably be somewhat easy), this view leads me to think that AI development will likely be net-positive for people who exist at the time of alignment. In other words, if we allow AI development, it is likely that we can use AI to reduce human mortality, and dramatically raise human well-being for the people who already exist. I think these benefits are large and important, and commensurate with the downside potential of existential risks. While a fully committed strong longtermist might scoff at the idea that curing aging might be important — as it would largely only have short-term effects, rather than long-term effects that reverberate for billions of years — by contrast, I think it's really important to try to improve the lives of people who currently exist. Many people view this perspective as a form of moral partiality that we should discard for being arbitrary. However, I think morality is itself arbitrary: it can be anything we want it to be. And I choose to value currently existing humans, to a substantial (though not overwhelming) degree. This doesn't mean I'm a fully committed near-termist. I sympathize with many of the intuitions behind longtermism. For example, if curing aging required raising the probability of human extinction by 40 percentage points, or something like that, I don't think I'd do it.  But in more realistic scenarios that we are likely to actually encounter, I think it's plausibly a lot better to accelerate AI, rather than delay AI, on current margins. This view simply makes sense to me given the enormously positive effects I expect AI will likely have on the people I currently know and love, if we allow development to continue.

Dustin Moskovitz claims "Tesla has committed consumer fraud on a massive scale", and "people are going to jail at the end" https://www.threads.net/@moskov/post/C6KW_Odvky0/ Not super EA relevant, but I guess relevant inasmuch as Moskovitz funds us and Musk has in the past too. I think if this were just some random commentator I wouldn't take it seriously at all, but a bit more inclined to believe Dustin will take some concrete action. Not sure I've read everything he's said about it, I'm not used to how Threads works

My recommended readings/resources for prospective community builders/organisers * CEA's groups resource centre, naturally  * This handbook on community organising  * High Output Management by Andrew Groves * How to Launch a High-Impact Nonprofit * LifeLabs's coaching questions (great for 1-1s with organisers) * The 2-Hour Cocktail Party * Centola's work on social change, e.g., the book Change: How to Make Big Things Happen * Han's work on organising, e.g., How Organisations Develop Activists (I wrote up some notes here) * This 80k article on community coordination * @Michael Noetel's forum post - 'We all teach: here's how to do it better'  * Theory of change in ten steps * Rumelt's Good Strategy Bad Strategy * IDinsight's Impact Measurement Guide

Given how bird flu is progressing (spread in many cows, virologists believing rumors that humans are getting infected but no human-to-human spread yet), this would be a good time to start a protest movement for biosafety/against factory farming in the US.

Vaccines saved 150M+ lives over the past 50 years, including 100M+ infants and nearly 100M lives from Measles alone: https://www.gavi.org/vaccineswork/new-data-shows-vaccines-have-saved-154-million-lives-past-50-years https://www.who.int/news/item/24-04-2024-global-immunization-efforts-have-saved-at-least-154-million-lives-over-the-past-50-years

First in-ovo sexing in the US Egg Innovations announced that they are "on track to adopt the technology in early 2025." Approximately 300 million male chicks are ground up alive in the US each year (since only female chicks are valuable) and in-ovo sexing would prevent this.  UEP originally promised to eliminate male chick culling by 2020; needless to say, they didn't keep that commitment. But better late than never!  Congrats to everyone working on this, including @Robert - Innovate Animal Ag, who founded an organization devoted to pushing this technology.[1] 1. ^ Egg Innovations says they can't disclose details about who they are working with for NDA reasons; if anyone has more information about who deserves credit for this, please comment!

With the US presidential election coming up this year, some of y’all will probably want to discuss it.[1] I think it’s a good time to restate our politics policy. tl;dr Partisan politics content is allowed, but will be restricted to the Personal Blog category. On-topic policy discussions are still eligible as frontpage material. 1. ^ Or the expected UK elections.

Ben West recently mentioned that he would be excited about a common application. It got me thinking a little about it. I don't have the technical/design skills to create such a system, but I want to let my mind wander a little bit on the topic. This is just musings and 'thinking out out,' so don't take any of this too seriously. What would the benefits be for some type of common application? For the applicant: send an application to a wider variety of organizations with less effort. For the organization: get a wider variety of applicants. Why not just have the post openings posted to LinkedIn and allow candidates to use the Easy Apply function? Well, that would probably result in lots of low quality applications. Maybe include a few question to serve as a simple filter? Perhaps a question to reveal how familiar the candidate is with the ideas and principles of EA? Lots of low quality applications aren't really an issue if you have an easy way to filter them out. As a simplistic example, if I am hiring for a job that requires fluent Spanish, and a dropdown prompt in the job application asks candidates to evaluate their Spanish, it is pretty easy to filter out people that selected "I don't speak any Spanish" or "I speak a little Spanish, but not much." But the benefit of Easy Apply (from the candidate's perspective) is the ease. John Doe candidate doesn't have to fill in a dozen different text boxes with information that is already on his resume. And that ease can be gained in an organization's own application form. An application form literally can be as simple as prompts for name, email address, and resume. That might be the most minimalistic that an application form could be while still being functional. And there are plenty of organizations that have these types of applications: companies that use Lever or Ashby often have very simple and easy job application forms (example 1, example 2). Conversely, the more than organizations prompt candidates to explain "Why do you want to work for us" or "tell us about your most impressive accomplishment" the more burdensome it is for candidates. Of course, maybe making it burdensome for candidates is intentional, and the organization believes that this will lead to higher quality candidates. There are some things that you can't really get information about by prompting candidates to select an item from a list.

Maybe EA philanthropists should be invest more conservatively, actually The pros and cons of unusually high risk tolerance in EA philanthropy have been discussed a lot, e.g. here. One factor that may weigh in favor of higher risk aversion is that nonprofits benefit from a stable stream of donations, rather than one that goes up and down a lot with the general economy. This is for a few reasons: * Funding stability in a cause area makes it easier for employees to advance their careers because they can count on stable employment. It also makes it easier for nonprofits to hire, retain, and develop talent. This allows both nonprofits and their employees to have greater impact in the long run. Whereas a higher but more volatile stream of funding might not lead to as much impact. * It becomes more politically difficult to make progress in some causes during a recession. For example, politicians may have lower appetite for farm animal welfare regulations and might even be more willing to repeal existing regulations if they believe the regulations stifle economic growth. This makes it especially important for animal welfare orgs to retain funding.

I don't think we have a good answer to what happens after we do auditing of an AI model and find something wrong.   Given that our current understanding of AI's internal workings is at least a generation behind, it's not exactly like we can isolate what mechanism is causing certain behaviours. (Would really appreciate any input here- I see very little to no discussion on this in governance papers; it's almost as if policy folks are oblivious to the technical hurdles which await working groups)

Consider donating all or most of your Mana on Manifold to charity before May 1. Manifold is making multiple changes to the way Manifold works. You can read their announcement here. The main reason for donating now is that Mana will be devalued from the current 1 USD:100 Mana to 1 USD:1000 Mana on May 1. Thankfully, the 10k USD/month charity cap will not be in place until then. Also this part might be relevant for people with large positions they want to sell now: > One week may not be enough time for users with larger portfolios to liquidate and donate. We want to work individually with anyone who feels like they are stuck in this situation and honor their expected returns and agree on an amount they can donate at the original 100:1 rate past the one week deadline once the relevant markets have resolved.

I see way too many people confusing movement with progress in the policy space.  There can be a lot of drafts becoming bills with still significant room for regulatory capture in the specifics, which will be decided later on. Take risk levels, for instance, which are subjective - lots of legal leeway for companies to exploit. 

This is an extremely "EA" request from me but I feel like we need a word for people (i.e. me) who are Vegans but will eat animal products if they're about to be thrown out. OpportuVegan? UtilaVegan?

High impact startup idea: make a decent carbon emissions model for flights. Current ones simply use flight emissions which makes direct flights look low-emission. But in reality, some of these flights wouldn't even be there if people could be spread over existing indirect flights more efficiently, which is why they're cheaper too. Emission models should be relative to counterfactual. The startup can be for-profit. If you're lucky, better models already exist in scientific literature. Ideal for the AI for good-crowd. My guess is that a few man-years work could have a big carbon emissions impact here.

I think it would be good if lots of EAs answered this twitter poll, so we could get a better sense for the communities views on the topic of Enlightenment / Awakening: https://twitter.com/SpencrGreenberg/status/1782525718586413085?ref_src=twsrc%5Egoogle%7Ctwcamp%5Eserp%7Ctwgr%5Etweet

CEA is hiring for someone to lead the EA Global program. CEA's three flagship EAG conferences facilitate tens of thousands of highly impactful connections each year that help people build professional relationships, apply for jobs, and make other critical career decisions. This is a role that comes with a large amount of autonomy, and one that plays a key role in shaping a key piece of the effective altruism community’s landscape.  See more details and apply here!

Quote from VC Josh Wolfe: > Biology. We will see an AWS moment where instead of you having to be a biotech firm that opens your own wet lab or moves into Alexandria Real Estate, which is you know, specializes in hosting biotech companies, in in all these different regions approximate to academic research centers. You will be able to just take your experiment and upload it to the cloud where there are cloud-based robotic labs. We funded some of these. There's one company called Stratios. > > There's a ton that are gonna come on wave, and this is exciting because you can be a scientist on the beach in the Bahamas, pull up your iPad, run an experiment. The robots are performing 90% of the activity of Pouring something from a beaker into another, running a centrifuge, and then the data that comes off of that. > > And this is the really cool part. Then the robot and the machines will actually say to you, “Hey, do you want to run this experiment but change these 4 parameters or these variables?” And you just click a button “yes” as though it's reverse prompting you, and then you run another experiment. So the implication here is that the boost in productivity for science, for generation of truth, of new information, of new knowledge, That to me is the most exciting thing. And the companies that capture that, forget about the societal dividend, I think are gonna make a lot of money. https://overcast.fm/+5AWO95pnw/46:15

I noticed that many people write a lot not only on forums but also on personal blogs and Substack. This is sad. Competent and passionate people are writing in places that get very few views. I too am one of those people. But honestly, magazines and articles are stressful and difficult, and forums are so huge that even if they have a messaging function, it is difficult to achieve a transparent state where each person can fully recognize their own epistemological status. I'm interested in such collaborative blogs, similar to the early Overcoming Bias. I believe that many bloggers and writers need help and that we can help each other. Is there anyone who wants to be with me?

Has anyone seen an analysis that takes seriously the idea that people should eat some fruits, vegetables and legumes over others based on how much animal suffering they each cause? I.e. don't eat X fruit, eat Y one instead, because X fruit is [e.g.] harvested in Z way, which kills more [insert plausibly sentient creature].

The catchphrase I walk around with in my head regarding the optimal strategy for AI Safety is something like: Creating Superintelligent Artificial Agents* (SAA) without a worldwide referendum is ethically unjustifiable. Until a consensus is reached on whether to bring into existence such technology, a global moratorium is required (*we already have AGI). I thought it might be useful to spell that out.

GiveWell and Open Philanthropy just made a $1.5M grant to Malengo! Congratulations to @Johannes Haushofer and the whole team, this seems such a promising intervention from a wide variety of views

I'm going to make a quick take thread of EA-relevant software projects I could work on. Agree / disagree vote if you think I should/ should not do some particular project.

I recently discovered the idea of driving all blames into oneself, which immediately resonated with me. It is relatively hardcore; the kind of thing that would turn David Goggins into a Buddhist. Gemini did a good job of summarising it: This quote by Pema Chödron, a renowned Buddhist teacher, represents a core principle in some Buddhist traditions, particularly within Tibetan Buddhism. It's called "taking full responsibility" or "taking self-blame" and can be a bit challenging to understand at first. Here's a breakdown: What it Doesn't Mean: * Self-Flagellation: This practice isn't about beating yourself up or dwelling on guilt. * Ignoring External Factors: It doesn't deny the role of external circumstances in a situation. What it Does Mean: * Owning Your Reaction: It's about acknowledging how a situation makes you feel and taking responsibility for your own emotional response. * Shifting Focus: Instead of blaming others or dwelling on what you can't control, you direct your attention to your own thoughts and reactions. * Breaking Negative Cycles: By understanding your own reactions, you can break free from negative thought patterns and choose a more skillful response. Analogy: Imagine a pebble thrown into a still pond. The pebble represents the external situation, and the ripples represent your emotional response. While you can't control the pebble (the external situation), you can control the ripples (your reaction). Benefits: * Reduced Suffering: By taking responsibility for your own reactions, you become less dependent on external circumstances for your happiness. * Increased Self-Awareness: It helps you understand your triggers and cultivate a more mindful response to situations. * Greater Personal Growth: By taking responsibility, you empower yourself to learn and grow from experiences. Here are some additional points to consider: * This practice doesn't mean excusing bad behavior. You can still hold others accountable while taking responsibility for your own reactions. * It's a gradual process. Be patient with yourself as you learn to practice this approach.

Animal Justice Appreciation Note Animal Justice et al. v A.G of Ontario 2024 was recently decided and struck down large portions of Ontario's ag-gag law. A blog post is here. The suit was partially funded by ACE, which presumably means that many of the people reading this deserve partial credit for donating to support it. Thanks to Animal Justice (Andrea Gonsalves, Fredrick Schumann, Kaitlyn Mitchell, Scott Tinney), co-applicants Jessica Scott-Reid and Louise Jorgensen, and everyone who supported this work!

Be the meme you want to see in the world (screenshot).  

While AI value alignment is considered a serious problem, the algorithms we use every day do not seem to be subject to alignment. That sounds like a serious problem to me. Has no one ever tried to align the YouTube algorithm with our values? What about on other types of platforms?

The topics of working for an EA org and altruist careers are discussed occasionally in our local group.  I wanted to share my rough thoughts and some relevant forum posts that I've compiled in this google doc. The main thesis is that it's really difficult to get a job at an EA org, as far as I know, and most people will have messier career paths. Some of the posts I link in the doc, specifically around alternate career paths: The career and the community Consider a wider range of jobs, paths and problems if you want to improve the long-term future My current impressions on career choice for longtermists

The New York Declaration on Animal Consciousness and an article about it: https://sites.google.com/nyu.edu/nydeclaration/declaration https://www.nbcnews.com/science/science-news/animal-consciousness-scientists-push-new-paradigm-rcna148213

An alternate stance on moderation (from @Habryka.) This is from this comment responding to this post about there being too many bans on LessWrong. Note how the LessWrong is less moderated than here in that it (I guess) responds to individual posts less often, but more moderated in that I guess it rate limits people more without reason.  I found it thought provoking. I'd recommend reading it. > Thanks for making this post!  > > One of the reasons why I like rate-limits instead of bans is that it allows people to complain about the rate-limiting and to participate in discussion on their own posts (so seeing a harsh rate-limit of something like "1 comment per 3 days" is not equivalent to a general ban from LessWrong, but should be more interpreted as "please comment primarily on your own posts", though of course it shares many important properties of a ban). This is a pretty opposite approach to the EA forum which favours bans. > Things that seem most important to bring up in terms of moderation philosophy:  > > Moderation on LessWrong does not depend on effort > > "Another thing I've noticed is that almost all the users are trying.  They are trying to use rationality, trying to understand what's been written here, trying to apply Baye's rule or understand AI.  Even some of the users with negative karma are trying, just having more difficulty." > > Just because someone is genuinely trying to contribute to LessWrong, does not mean LessWrong is a good place for them. LessWrong has a particular culture, with particular standards and particular interests, and I think many people, even if they are genuinely trying, don't fit well within that culture and those standards.  > > In making rate-limiting decisions like this I don't pay much attention to whether the user in question is "genuinely trying " to contribute to LW,  I am mostly just evaluating the effects I see their actions having on the quality of the discussions happening on the site, and the quality of the ideas they are contributing.  > > Motivation and goals are of course a relevant component to model, but that mostly pushes in the opposite direction, in that if I have someone who seems to be making great contributions, and I learn they aren't even trying, then that makes me more excited, since there is upside if they do become more motivated in the future. I sense this is quite different to the EA forum too. I can't imagine a mod saying I don't pay much attention to whether the user in question is "genuinely trying". I find this honesty pretty stark. Feels like a thing moderators aren't allowed to say. "We don't like the quality of your comments and we don't think you can improve". > Signal to Noise ratio is important > > Thomas and Elizabeth pointed this out already, but just because someone's comments don't seem actively bad, doesn't mean I don't want to limit their ability to contribute. We do a lot of things on LW to improve the signal to noise ratio of content on the site, and one of those things is to reduce the amount of noise, even if the mean of what we remove looks not actively harmful.  > > We of course also do other things than to remove some of the lower signal content to improve the signal to noise ratio. Voting does a lot, how we sort the frontpage does a lot, subscriptions and notification systems do a lot. But rate-limiting is also a tool I use for the same purpose. > Old users are owed explanations, new users are (mostly) not > > I think if you've been around for a while on LessWrong, and I decide to rate-limit you, then I think it makes sense for me to make some time to argue with you about that, and give you the opportunity to convince me that I am wrong. But if you are new, and haven't invested a lot in the site, then I think I owe you relatively little.  > > I think in doing the above rate-limits, we did not do enough to give established users the affordance to push back and argue with us about them. I do think most of these users are relatively recent or are users we've been very straightforward with since shortly after they started commenting that we don't think they are breaking even on their contributions to the site (like the OP Gerald Monroe, with whom we had 3 separate conversations over the past few months), and for those I don't think we owe them much of an explanation. LessWrong is a walled garden.  > > You do not by default have the right to be here, and I don't want to, and cannot, accept the burden of explaining to everyone who wants to be here but who I don't want here, why I am making my decisions. As such a moderation principle that we've been aspiring to for quite a while is to let new users know as early as possible if we think them being on the site is unlikely to work out, so that if you have been around for a while you can feel stable, and also so that you don't invest in something that will end up being taken away from you. > > Feedback helps a bit, especially if you are young, but usually doesn't > > Maybe there are other people who are much better at giving feedback and helping people grow as commenters, but my personal experience is that giving users feedback, especially the second or third time, rarely tends to substantially improve things.  > > I think this sucks. I would much rather be in a world where the usual reasons why I think someone isn't positively contributing to LessWrong were of the type that a short conversation could clear up and fix, but it alas does not appear so, and after having spent many hundreds of hours over the years giving people individualized feedback, I don't really think "give people specific and detailed feedback" is a viable moderation strategy, at least more than once or twice per user. I recognize that this can feel unfair on the receiving end, and I also feel sad about it. > > I do think the one exception here is that if people are young or are non-native english speakers. Do let me know if you are in your teens or you are a non-native english speaker who is still learning the language. People do really get a lot better at communication between the ages of 14-22 and people's english does get substantially better over time, and this helps with all kinds communication issues. Again this is very blunt but I'm not sure it's wrong.  > We consider legibility, but its only a relatively small input into our moderation decisions > > It is valuable and a precious public good to make it easy to know which actions you take will cause you to end up being removed from a space. However, that legibility also comes at great cost, especially in social contexts. Every clear and bright-line rule you outline will have people budding right up against it, and de-facto, in my experience, moderation of social spaces like LessWrong is not the kind of thing you can do while being legible in the way that for example modern courts aim to be legible.  > > As such, we don't have laws. If anything we have something like case-law which gets established as individual moderation disputes arise, which we then use as guidelines for future decisions, but also a huge fraction of our moderation decisions are downstream of complicated models we formed about what kind of conversations and interactions work on LessWrong, and what role we want LessWrong to play in the broader world, and those shift and change as new evidence comes in and the world changes. > > I do ultimately still try pretty hard to give people guidelines and to draw lines that help people feel secure in their relationship to LessWrong, and I care a lot about this, but at the end of the day I will still make many from-the-outside-arbitrary-seeming-decisions in order to keep LessWrong the precious walled garden that it is. > > I try really hard to not build an ideological echo chamber > > When making moderation decisions, it's always at the top of my mind whether I am tempted to make a decision one way or another because they disagree with me on some object-level issue. I try pretty hard to not have that affect my decisions, and as a result have what feels to me a subjectively substantially higher standard for rate-limiting or banning people who disagree with me, than for people who agree with me. I think this is reflected in the decisions above. > > I do feel comfortable judging people on the methodologies and abstract principles that they seem to use to arrive at their conclusions. LessWrong has a specific epistemology, and I care about protecting that. If you are primarily trying to...  > > * argue from authority,  > * don't like speaking in probabilistic terms,  > * aren't comfortable holding multiple conflicting models in your head at the same time,  > * or are averse to breaking things down into mechanistic and reductionist terms,  > > then LW is probably not for you, and I feel fine with that. I feel comfortable reducing the visibility or volume of content on the site that is in conflict with these epistemological principles (of course this list isn't exhaustive, in-general the LW sequences are the best pointer towards the epistemological foundations of the site). It feels cringe to read that basically if I don't get the sequences lessWrong might rate limit me. But it is good to be open about it. I don't think the EA forum's core philosophy is as easily expressed. > If you see me or other LW moderators fail to judge people on epistemological principles but instead see us directly rate-limiting or banning users on the basis of object-level opinions that even if they seem wrong seem to have been arrived at via relatively sane principles, then I do really think you should complain and push back at us. I see my mandate as head of LW to only extend towards enforcing what seems to me the shared epistemological foundation of LW, and to not have the mandate to enforce my own object-level beliefs on the participants of this site. > > Now some more comments on the object-level:  > > I overall feel good about rate-limiting everyone on the above list. I think it will probably make the conversations on the site go better and make more people contribute to the site.  > > Us doing more extensive rate-limiting is an experiment, and we will see how it goes. As kave said in the other response to this post, the rule that suggested these specific rate-limits does not seem like it has an amazing track record, though I currently endorse it as something that calls things to my attention (among many other heuristics). > > Also, if anyone reading this is worried about being rate-limited or banned in the future, feel free to reach out to me or other moderators on Intercom. I am generally happy to give people direct and frank feedback about their contributions to the site, as well as how likely I am to take future moderator actions. Uncertainty is costly, and I think it's worth a lot of my time to help people understand to what degree investing in LessWrong makes sense for them. 

It seems plausible to me that those involved in Nonlinear have received more social sanction than those involved in FTX, even though the latter was obviously more harmful to this community and the world.

Marcus Daniell appreciation note @Marcus Daniell, cofounder of High Impact Athletes, came back from knee surgery and is donating half of his prize money this year. He projects raising $100,000. Through a partnership with Momentum, people can pledge to donate for each point he gets; he has raised $28,000 through this so far. It's cool to see this, and I'm wishing him luck for his final year of professional play!

FHI has shut down yesterday: https://www.futureofhumanityinstitute.org/

Ethical Implications of AI in Military Operations: A Look at Project Nimbus   Recently, 'Democracy Now' highlighted Google’s involvement in Project Nimbus, a $1.2 billion initiative to provide cloud computing services to the Israeli government, including military applications. Google employees have raised concerns about the use of AI in creating 'kill lists' with minimal human oversight, as well as the usage of Google Photos to identify and detain individuals. This raises ethical questions about the role of AI in warfare and surveillance. Despite a sit-in and retaliation against those speaking against the project, there has been little visible impact on the continuation of the contract. The most recent protesters faced arrest. What does this suggest about the power of AI in the hands of governments and the efficacy of public dissent in influencing such high-stakes deployments of AI use?

I am not confident that another FTX level crisis is less likely to happen, other than that we might all say "oh this feels a bit like FTX". Changes: * Board swaps. Yeah maybe good, though many of the people who left were very experienced. And it's not clear whether there are due diligence people (which seems to be what was missing). * Orgs being spun out of EV and EV being shuttered. I mean, maybe good though feels like it's swung too far. Many mature orgs should run on their own, but small orgs do have many replicable features. * More talking about honesty. Not really sure this was the problem. The issue wasn't the median EA it was in the tails. Are the tails of EA more honest? Hard to say * We have now had a big crisis so it's less costly to say "this might be like that big crisis". Though notably this might also be too cheap - we could flinch away from doing ambitious things * Large orgs seem slightly more beholden to comms/legal to avoid saying or doing the wrong thing. * OpenPhil is hiring more internally Non-changes: * Still very centralised. I'm pretty pro-elite, so I'm not sure this is a problem in and of itself, though I have come to think that elites in general are less competent than I thought before (see FTX and OpenAI crisis) * Little discussion of why or how the affiliation with SBF happened despite many well connected EAs having a low opinion of him * Little discussion of what led us to ignore the base rate of scamminess in crypto and how we'll avoid that in future

I recently wrote a post on the EA forum about turning animal suffering to animal bliss using genetic enhancement. Titotal raised an thoughtful concern: "How do you check that your intervention is working? For example, suppose your original raccoons screech when you poke them, but the genetically engineered racoons don't. Is that because they are experiencing less pain, or have they merely evolved not to screech?" This is a very good point. I was recently considering how we could be sure to not just change the expressions of suffering and I believe that I have determined a means of doing so. In psychology, it is common to use factor analysis to study a latent variables--the variables that we cannot measure directly. It seems extremely reasonable to think that animal pain is real, but the trouble is measuring it. We could try to get at pain by getting a huge array of behaviors and measures that are associated with pain (heart rate, cortisol levels, facial expressions, vocalizations, etc.) and find a latent factor of suffering that accounts for some of these behaviors. To determine if an intervention is successful at changing the latent factor of suffering for the better, we could test for measurement invariance which is an important step in making a relevant comparison between two groups. This basically tests whether the nature of the factor loadings remains the same between groups. This would mean a reduction in all of the traits associated with suffering. This would also seem relevant for environmental interventions as well.  As an illustration: imagine that I measure wefare of a raccoon by the amount of screeching it does. A bad intervention would be taping the raccoons mouth shut. This would reduce screeching, but there is no good reason to think that would alleviate suffering. However, imagine I gave the raccoon a drug and it acted less stressed, screeched less, had less cortisol, and started acting much more friendly. This would be much better evidence of true reduction in suffering.  There is much more to be defended in my thesis but this felt like a thought worth sharing.

From a utilitarian perspective, it would seem there are substantial benefits to accurate measures of welfare.  I was listening to Adam Mastroianni discuss the history of trying measure happiness and life satisfaction and it was interesting to find a level of stability across the decades. Could it really be that the increases in material wealth do not result in huge objective increases in happiness and satisfaction for humans? It would seem the efforts to increase GDP and improve standard of living beyond the basics may be misdirected. Furthermore, it seems like it would be extremely helpful in terms of policy creation to have an objective unit like a util.  We could compare human and animal welfare directly, and genetically engineer animals to increase their utils.  While efforts might not super successful, it would seem very important to merely improve objective measures of wellbeing by say 10%.

Making an image with generative AI uses as much energy as charging your phone - MIT Technology review.  Should the EA forum still recommend to use an AI generated picture for a post's preview image? https://www.technologyreview.com/2023/12/01/1084189/making-an-image-with-generative-ai-uses-as-much-energy-as-charging-your-phone/