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 bad 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.

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!

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

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.

My recommended readings/resources for 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