Sounds like this is in reaction to yesterday’s launch of the Falcon Fund. I’m very excited this fund is happening, and I am personally donating to.
I appreciate you thinking out loud! As Constance said, I think this points to a lack of communication around the concrete ideas. I think Sentient Futures has done a phenomenal job in bringing attention to this whole area, and to me the whole point of the Falcon Fund is to start turning all the thinking into concrete projects.
My background is in ML in the alternative protein space. So I am also very excited about the prospect of AI helping the development of cultivated meat. However, at this stage, I think the AI-cultivated space suffers even moreso from the exact problem you’re describing where there is no well-defined problem. I wrote about this here if you’d like to discuss it more. I don’t think AI can model and run simulated experiments in this space. One day it might be able to, but that is much more likely going to be downstream of other general advances in the AI-sciences, and won’t be developed in the cultivated industry itself. We don’t have the money, talent, or data throughput to make that happen. I actually think what we should be aiming for in the short-medium term is something that looks like speeding up wet lab trial and error, I think there are a lot of gains to be had from designing experiments better and deploying something that looks like self-driving labs as soon as possible. If you have specific ideas for ideas that we can try testing now, I would love to talk.
In general I agree that we need to put more thought into the AI-cultivated plan.
On AIxAnimals I think there are some pretty clear things we need to do, which are also described on the Falcon Fund page.
Having an observatory/watchdog organization is really critical. We currently have no view on how AI is being used in industries that will impact animals. That will include when they run factory farms, do scientific research in areas like precision livestock farming, and help with ecological management. We need to see what’s going on in order to make decisions.
Having benchmarks is similarly important to actually have visibility into how these systems behave that are going to be very important. Then yes, hill-climbing on these numbers would be great.
I am sympathetic to your skepticism, especially that things that limit profitability will be hard. But I think we can afford to try here. Human values are not the same things as what the markets provide. Humans stated preferences are to like animals. Every ballot measure presented in any state in the US, whether led by Republicans or Democrats, has passed. It is one of the few bipartisan issues. I think a lot of the issues of animal welfare are due to people not being informed. In which case AI can be a powerful tool in aligning people’s behavior with their values, which is something we should encourage.
It is going to be very hard to be concrete about what effect we see in the real world until AI systems become industrially relevant. Until then the primary job is to observe as much as we can and make sure we’re moving things in the right direction. We can do this by having a benchmark, and seeing if the change in model spec language improves the benchmark.
Well said. On top of this, many new interventions are going to be primarily talent constrained, whereas Animal Welfare is primarily funding constrained. Animal Welfare should be prioritized at least until funding is no longer the main constraint.