I mean... it's quite easy. There were people who, for some reason, were optimistic regarding the long-term future of humanity and they had more children than others (and maybe a stronger survival drive), all else equal. The claim that there exists such a selection effect seems trivially true.

I agree that you can construct hypothetical scenarios in which a given trait is selected for (though even then you have to postulate that it's heritable, which you didn't specify here). But your claim is is not trivially true, and it does not establish that optimism regarding the long-term future of humanity has in fact been selected for in human evolutionary history. Other beliefs that are more plausibly susceptible to evolutionary debunking include the idea that we have special obligations to our family members, since these are likely connected to kinship ties that have been widely studied across many species.

So I think a key crux between us is on the question: what does it take for a belief to be vulnerable to evolutionary debunking? My view is that it should actually be established in the field of evolutionary psychology that the belief is best explained as the direct^[1] product of our evolutionary history. (Even then, as I think you agree, that doesn't falsify the belief, but it gives us reason to be suspicious of it.)

I asked ChatGPT how evolutionary psychologists typically try to show that a psychological trait was selected for. Here was its answer:

Evolutionary psychologists aim to show that a psychological trait is a product of selection by demonstrating that it likely solved adaptive problems in our ancestral environment. They look for traits that are universal across cultures, appear reliably during development, and show efficiency and specificity in addressing evolutionary challenges. Evidence from comparative studies with other species, heritability data, and cost-benefit analyses related to reproductive success also support such claims. Altogether, these approaches help build a case that the trait was shaped by natural or sexual selection rather than by learning or cultural influence alone.

I think you might say that you don't have to show that a belief is best explain by evolutionary pressure, just that there's some selection for it. In fact, I don't think you've done that (because e.g. you have to show that it's heritable). But I think that's not nearly enough, because "some evolutionary pressure toward belief X" is a claim we can likely make about any belief at all. (E.g., pessimism about the future can be very valuable, because it can make you aware of potential dangers that optimists would miss.)

Also, in response to  this:

On person-affecting beliefs: The vast majority of people holding these are not longtermists to begin with. What we should be wondering is "to the extent that we have intuitions about what is best for the long-term (and care about this), where do these intuitions come from?". Non-longtermist beliefs are irrelevant, here. Hopefully, this also addresses your last bullet point.

I'm not sure why you think non-longtermist beliefs are irrelevant. Your claim is that optimistic longtermist beliefs are vulnerable to evolutionary debunking. But that would only be true if they were plausibly a product of evolutionary pressures which should apply to populations that have been subject to evolutionary selection; otherwise they're not a product of our evolutionary history. And so evidence of what humans generally are prone to believe seems highly relevant. The fact that many people, perhaps most, are pre-theoretically disposed toward views that push away from optimistic longtermism and pro-natalism casts further doubt on the claim that the intuitions that push people toward optimistic longtermism and pro-natalism have been selected for.

1. ^{^}

   I used "direct" here because, in some sense, all of our beliefs are the product of our evolutionary history.

I don't think it's plausible that optimistic longtermism is vulnerable to evolutionary debunking, because:

• I've seen people reason themselves into and out of pro-natalist and anti-natalist stances, often using mathematical reasoning. I haven't seen any reason to believe that the pro-natalists' reasoning in particular is succumbing to evolutionary pressure.
• You can tell a story about pro-natalist beliefs having evolutionary advantages, of course, but that's not actually establishing a fact of evolutionary psychology. There are many such stories that sound plausible, and they can often be contradictory.
• Person-affecting beliefs, and neutrality about creating positive lives, often reflect deeply held intuitions shared by many people that are hard to square with the idea that there's strong evolutionary pressure toward intuitive pro-natalism. Indeed, my experience in philosophy is that these views are treated as the intuitive view that need to be defended from the un-intuitive arguments for longtermism.
• I think in fact it's more plausible to think that evolution selected for people who tend to have sex (that happens to be procreative) and want to care for children, than that it selects for having intuitions that people rely on when they reason impartially about population ethics.

I think if you were to turn this into an academic paper, I'd be interested to see if you could defend the claim that pro-natalist beliefs have been selected for in human evolutionary history.

Hi Rebecca,

Thanks for the question!

We did consider this as an option, and it's possible there are some versions of this we could do in the future, but it's not part of next steps at the moment. The basic reason is that this new strategic approach is the continuation of the direction 80k has been going for many years, so there’s not a segment of 80k with a separate focus to “spin-off” into a new entity. 

Thanks for the additional context! I think I understand your views better now and I appreciate your feedback.

Just speaking for myself here, I think I can identify some key cruxes between us. I'll take them one by one:

I think the impact of most actions here is basically chaotic.

I disagree with this. I think it's better if people have a better understanding of the key issues raised by the emergence of AGI. We don't have all the answers, but we've thought about these issues a lot and have ideas about what kinds of problems are most pressing to address and what some potential solutions are. Communicating these ideas more broadly and to people who may be able to help is just better in expectation than failing to do so (all else equal), even though, as with any problem, you can't be sure you're making things better, and there's some chance you make things worse.

I also think "make the world better in meaningful ways in our usual cause areas before AGI is here" probably helps in many worlds, due to things like AI maybe trying to copy our values, or AI could be controlled by the UN or whatever and it's good to get as much moral progress in there as possible beforehand, or just updates on the amount of morally aligned training data being used.

I don't think I agree with this. I think the value of doing work in areas like global health or helping animals is largely in the direct impact of these actions, rather than any impact on what it means for the arrival of AGI. I don't think even if, in an overwhelming success, we cut malaria deaths in half next year, that will meaningfully increase the likelihood that AGI is aligned or that the training data reflects a better morality. It's more likely that directly trying to work to create beneficial AI will have these effects. Of course, the case for saving lives from malaria is still strong, because people's lives matter and are worth saving.

I think that more serious consideration of the Existential Risk Persuasion Tournament leads one to conclude that wildly transformational outcomes just aren't that likely in the short/medium term.

Recall that the XPT is from 2022, so there's a lot that's happened since. Even still, here's what Ezra Karger noted about expectations of the experts and forecasters views when we interviewed him on the 80k podcast:

One of the pieces of this work that I found most interesting is that even though domain experts and superforecasters disagreed strongly, I would argue, about AI-caused risks, they both believed that AI progress would continue very quickly.

So we did ask superforecasters and domain experts when we would have an advanced AI system, according to a definition that relied on a long list of capabilities. And the domain experts gave a year of 2046, and the superforecasters gave a year of 2060. 

My understanding is that XPT was using the definition of AGI used in the Metaculus question cited in Niel's original post (though see his comment for some caveats about the definition). In March 2022, that forecast was around 2056-2058; it's now at 2030. The Metaculus question also has over 1500 forecasters, whereas XPT had around 30 superforecasters, I believe. So overall I wouldn't consider XPT to be strong evidence against short timelines.

I think there is some general "outside view" reason to be sceptical of short timelines. But I think there are good reasons to think that kind of perspective would miss big changes like this, and there is enough reason to believe short timelines are plausible to take action on that basis.

Again, thanks for engaging with all this!

One reason we use phrases “making AGI go well,” rather than some alternatives, is because 80k is concerned about risks like lock-in of really harmful values, in addition to human disempowerment and extinction risk — so I sympathise with your worries here.

Figuring out how to avoid these kinds of risks is really important, and recognising that they might arise soon is definitely within the scope of our new strategy. We have written about ways the future can look very bad even if humans have control of AI, for example here, here, and here.

I think it’s plausible to worry that not enough is being done about these kinds of concerns — that depends a lot on how plausible they are and how tractable the solutions are, which I don’t have very settled views on.

You might also think that there’s nothing tractable to do about these risks, so it’s better to focus on interventions that pay off in the short-term. But my view at least is that it is worth putting more effort into figuring out what the solutions here might be.

Hey Rocky —

Thanks for sharing these concerns. These are really hard decisions we face, and I think you’re pointing to some really tricky trade-offs.

We’ve definitely grappled with the question of whether it would make sense to spin up a separate website that focused more on AI. It’s possible that could still be a direction we take at some point. 

But the key decision we’re facing is what to do with our existing resources — our staff time, the website we’ve built up, our other programmes and connections. And we’ve been struggling with the fact that the website doesn’t really fully reflect the urgency we believe is warranted around rapidly advancing AI. Whether we launch another site or not, we want to honestly communicate about how we’re thinking about the top problem in the world and how it will affect people’s careers. To do that, we need to make a lot of updates in the direction this post is discussing.

That said, I’ve always really valued the fact that 80k can be useful to people who don’t agree with all our views. If you’re sceptical about AI having a big impact in the next few decades, our content on pandemics, nuclear weapons, factory farming — or our general career advice — can still be really useful. I think that will remain true even with our strategy shift.

I also think this is a really important point:

If transformative AI is just five years away, then we need people who have spent their careers reducing nuclear risks to be doing their most effective work right now—even if they’re not fully bought into AGI timelines. We need biosecurity experts building robust systems to mitigate accidental or deliberate pandemics—whether or not they view that work as directly linked to AI.

I think we’re mostly in agreement here — work on nuclear risks and biorisks remain really important, and last year we made efforts to make sure our bio and nuclear content was more up to date. We recently made an update about mirror bio risks, because they seem especially pressing.

As the post above says: “When deciding what to work on, we’re asking ourselves ‘How much does this work help make AI go better?’, rather than ‘How AI-related is it?’” So to the extent that other work has a key role to play in the risks that surround a world with rapidly advancing AI, it’s clearly in scope of the new strategy.

But I think it probably is helpful for people doing work in areas like nuclear safety and bio to recognise the way short AI timelines could affect their work. So if 80k can communicate that to our audience more clearly, and help people figure out what that means they should do for their careers, it could be really valuable. 

And if we are truly on the brink of catastrophe, we still need people focused on minimizing human and nonhuman suffering in the time we have left.

I do think we should be absolutely clear that we agree with this — it’s incredibly valuable that work to minimise existing suffering continues. I support that happening and am incredibly thankful to those who do it. This strategy doesn’t change that a bit. It just means 80k thinks our next marginal efforts are best focused on the risks arising from AI.

On the broader issue of what this means for the rest of the EA ecosystem, I think the risks you describe are real and are important to weigh. One reason we wanted to communicate this strategy publicly is so others could assess it for themselves and better coordinate on their paths forward. And as Conor said, we really wish we didn’t have to live in a world where these issues seem as urgent as they do.

But I think I see the costs of the shift as less stark. We still plan to have our career guide up as a central piece of content, which has been a valuable resource to many people; it explains our views on AI, but also guides people through thinking about cause prioritisation for themselves. And as the post notes, we plan to publish and promote a version of the career guide with a professional publisher in the near future. At the same time, for many years 80k has also made it clear that we prioritise risks from AI as the world’s most pressing problem. So I don’t think I see this as clearly a break from the past as you might.

At the highest level, though, we do face a decision about whether to focus more on AI and the plausibly short timelines to AGI, or to spend time on a wider range of problem areas and take less of a stance on timelines. Focusing more does have the risk that we won’t reach our traditional audience as well, which might even reduce our impact on AI; but declining to focus more has the risk of missing out on other audiences we previously haven’t reached, failing to faithfully communicate our views about the world, and missing out on big opportunities to positively work on what we think is the most pressing problem we face.

As the post notes, while we are committed to making the strategic shift, we’re open to changing our minds if we get important updates about our work. We’ll assess how we’re performing on the new strategy, whether there are any unexpected downsides, and whether developments in the world are matching our expectations. And we definitely continue to be open to feedback from you and others who have a different perspective on the effects 80k is having in the world, and we welcome input about what we can do better.

Thanks so much for all your work Lizka!

Hi — thanks for raising this issue.

As has been pointed out, the page where we (80k) detail the definition of “social impact” in depth is explicit that we do consider animals to be a part of impartial social impact. It’s not just in a footnote. The body of the article mentions animals and non-human sentient beings several times, including in this paragraph:

>We mean that we strive to treat equal effects on different beings’ welfare as equally morally important, no matter who they are — including people who live far away or in the future. In addition, we think that the interests of many nonhuman animals, and even potentially sentient future digital beings, should be given significant weight, although we’re unsure of the exact amount. Thus, we don’t think social impact is limited to promoting the welfare of any particular group we happen to be partial to (such as people who are alive today, or human beings as a species).

Also note that in the core argument of our article on longtermism, we strove to make clear that we’re not just concerned with future humans, but all morally relevant beings:

1. We should care about how the lives of future individuals go.
2. The number of future individuals whose lives matter could be vast.
3. We have an opportunity to affect how the long-run future goes — whether there may be many flourishing individuals in the future, many suffering individuals in the future, or perhaps no one at all.

But there can be a trade off between succinctness and complete precision. Being succinct isn’t trivial — writing that is accessible and engaging can be much more effective than verbose academic prose. The page you linked to is a summary of our career planning course, so it's necessarily even more succinct than usual and doesn't delve into the details of each claim. Of course, we don’t want to mislead people about what we believe, so these kinds of decisions are always a balancing act, and we won’t always get it right.

Your post is a good reminder of how some ways of communicating these ideas can give the wrong impression, so we’re going to review whether and to what extent we should make changes to be clearer about this issue. The feedback is much appreciated!

— Cody from 80k

Hi — thanks for for the question! That’s definitely what we care about most, but it’s also unsurprisingly very hard to track, as you say. We have different ways we try to assess our impact along these lines, but the best metrics we can share publicly are in an appendix to our two-year review that summarises the results of our user survey. You can also see Brenton's answer in a separate comment for much more detail about our efforts to track these metrics.