There's a quote in the post:

Some effective altruists expect artificial general intelligence (AGI) or transformative AI (TAI) to solve the taste and price challenges for alternative meats, and so they wonder: What's the point of work on alternative meats now? 

I'd be interested to learn more about the reasoning behind this view. So far I'm only familiar with [1](https://www.lesswrong.com/posts/DuCWLYx4jAFPMXKjZ/paper-artificial-intelligence-in-life-extension-from-deep) and [2](https://forum.effectivealtruism.org/posts/TYhs8zehyybvMt5E4/).

And I have an intuition (possibly because I'm unintentionally making a strawman out of the actual position simply because I don't understand it) that the "we need AGI to solve this problem" relies on the assumption that "AGI is a thing that will solve basically all existing problems simply because it's generally much better at solving problems than we are". And the implicit conclusion is "so we don't need to think about how exactly AGI will solve this particular problem".

It seemed to me that the post was arguing against this approach.

And I actually want to argue even further:

I think we somewhat understand the problem at the gears-level where we can build models and test them against reality, given that we have narrow AI with today's SOTA capabilities at our disposal. Current models have already shown themselves to be effective in some kinds of scientific research (mostly when the task is formulated in a specific, AI-tractable way).

And overall I assign a higher probability to A than B.

• Where A is: "We can build a high-level model of what interventions are needed to achieve large-scale replacement of animal products, ensure a smooth and comfortable transition, and make this new dietary pattern stable. And then decompose the problem in such a way that the applied parts of this research would benefit significantly from using SOTA AI. And eventually succeed."
• Where B is: "We manage to build an AI that will solve a whole range of very different problems, including this one, without us having to put effort into investigating this particular problem now."

And I assign a substantially higher probability to A than B. (And I'm not even talking about existential risks here, but never mind.)

Is it really true that my view is far from consensus? I thought pretty much everyone thought roughly along these lines, but after reading this post I'm somehow not so sure anymore.

If you have engaged with Anthony's sequence, and you hadn't thought seriously about cluelessness before, I'd be interested in knowing if it changed your mind on your cause prioritisation. You can answer as a reply, or just vote:

Note: I couldn't post this at the time because there was a bug, but I'd be keen to hear responses now as well. 

(We've talked about most of this outside of the public view, but I can't restrain myself from commenting none-the-less)

1. Legibility

I agree with you strategically that people who care about mental health need to make their case in a way that's legible to more traditional metrics like income, DALYs, etc. But the general thing this points to is greater legibility --> greater uptake --> impact blah blah. 

On this general point, one thing we've been thinking about and piloting is just trying to make WELLBYs more legible, especially for MH interventions by converting them to years of depression averted (YODAs). 

So I could say that a fictional charity Gaya Kuides generates 1,000 WELLBYs per $1k donated. Or given that the typical case of depression (moderate depression) is associated with a -1.3. lower wellbeing compared to low depression symptoms -- this implies that actually GK averts the equivalent of 1000 / 1.3 =769 years of depression per $1k donated. FWIW we explain the YODAs more here and we're looking for feedback on whether this seems like a useful communication device. 

It just seems way easier to imagine the value of a year of depression averted compared to "WELLBY". 

2. Long-run effects of psychotherapy 

This is very important and understudied. The effects of psychotherapy could last much longer, and we could maybe make these interventions benefit people for much longer than we. But we don't care much about LR effects in general in the research community and we do not have much understanding of the mechanisms that support long-term benefits. I obviously wish that we'd change on both accounts. 

• I think the Cuijpers stuff is interesting, and I think the results are consistent with the existence of the long-term effects of psychotherapy. I take this from ignoring the splines and just seeing that there are observations of effects years later.
• Sure it doesn't rule out indefinite effects. But you could say the same thing about finding positive effects after 1 month, so I'm less gung-ho on the language.
• Some methodological concern with Cuijpers et al. they only present and discuss one sort of unconventional model (why not a linear model? It looks like a linear model would predict decay but I obviously can't tell). They also don't do a lot of (any?) tests like seeing how stable these are when we remove studies or whether there's publication bias where you only do a follow-up when you think you're going to find something (you could interrogate this by seeing if earlier effects are higher than effects in that same time window). Basically I'd be more reassured if they ran and reported a lot of different models and robustness tests.
• Mechanisms! Why do the benefits of mental health interventions persist and decay? I'd guess that the mechanisms are some mix of A) access to and utilization to new tools for thinking. These require practice and memory so I expect we will see decay without some structure to continue maintenance. B) A change in believes around mental health or in one's agency to affect their MH. This seems like this part is something that could plausibly last much longer as a result of a short intervention. If you make someone believe this is a solvable problem, then that could benefit them for life. But note I expect that the belief mechanism is probably more important in LMICs where stigma and traditional believes around mental health (it's demons or curses, etc) is more common. This would make me think it's likelier that the benefits last longer in LMICs than HICs. But this is the opposite of what our meta-analytic results suggest (effects last 2-6 years in LMICs) versus Cuijpers implied you treat someone in HICs and it benefits them indefinitely.
  • I guess back to Cuijpers... one thing that could explain the LR results is that in HIC after you start getting treatment even if the RCT ends you may just keep getting therapy. That presumably doesn't happen in LMICs and may explain the discrepancy. But I'd need to dig into the Cuijpers data to interrogate that.
• Mechanisms part 2: treat the young. It seems plausible that you can potentially change lifelong trajectories by treating earlier. This is commonly assumed but there's not too much evidence I've found (e.g., Bhalotra et al., 2025 seems to suggest LR positive effects but I think there are some other econ papers that find null LR results for natural experiments increasing access to MH treatment for youth).