I’ve been a Researcher at Animal Charity Evaluators (ACE) since October 2022. Before joining ACE, I worked in various roles in the U.K. Civil Service, most recently heading up the Animal Welfare Labelling team. I write the monthly Sentient Futures newsletter.
Max Taylor
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Great, thanks Tristan! That’s really good to hear, and noted re. the formatting. And yes, we definitely hope that other researchers will build on this and challenge us so that we can continually improve it.
Thanks David!
We trialled a few formats, including Notion, and Google Docs was overall the easiest overall for reading and updating, but agree the in-built menu bar is a bit unwieldy. We also considered adding a comparison table but decided not to as distilling the content for each intervention to that extent ended up being unhelpfully reductive. We’ll consider other ways to make this easier to navigate though, thanks for flagging!
Yeah, to keep the document tidy and help us moderate comments then we invite people to directly email me (max.taylor@animalcharityevaluators.org) or Alina Salmen (alina.salmen@animalcharityevaluators.org) with feedback or to request comment access, rather than us enabling comment access automatically.
Thanks for noting all the cross-over with The Unjournal, that’s great! I’ve added those evaluations to our list of studies to incorporate when we next update this.
Hey Benny, thanks for the thoughts!
Totally agree on your first point. I guess you could divide positive use cases up into a few different categories:
In some cases, like alt proteins, there are already people/companies intentionally trying to create less exploitative systems with reasonable chance of success, and AI will help them achieve that.
In others, like most alternatives to animal testing methods or many forms of Precision Livestock Farming, AI enables methods that are cheaper, more effective, etc., so those methods will probably end up getting adopted and incidentally helping animals in the process.
But for many other areas, the positive use cases rely on getting governments, public, industry etc. to care about animals. If we think that we’re likely to see transformative AI fairly soon, it probably makes sense to specifically target those kind of MCE efforts at the people who will have most say over AI systems, like governments and AI companies. I’ve explored that a bit in another post.
On your second point: thanks, that’s a good point and I think your suggestion is probably more accurate!
Thanks for this excellent post! The distinction between ‘puntable’ and ‘less puntable’ ideas seems like a really helpful way for advocates to think about tactic prioritisation.
On the point about AI-enabled modelling of wild animal welfare and implications of different interventions: are there any existing promising examples of this? The one example I’ve come across is the model described in the paper ‘Predicting predator–prey interactions in terrestrial endotherms using random forest’ but the predictions seem pretty basic and not necessarily any better than non-AI modelling.
Also, why did you decide that TAI’s role in ‘infrastructure needs’ and ‘getting the “academic stamp of approval”’ weren’t useful to think about?
Nice one, thanks Miranda! Would be really interested to chat about this—I’ll DM you :-)
Thanks Vasco, this is a great idea. I’ll look into it :-)
That’s great to hear! BlueDot has been my main resource for getting to grips with AI. Please feel free to share any ideas that come up as you explore how this applies to your own advocacy :-)
Thanks Tristan! Definitely agree that AGI’s effects on animals (like on humans) are currently extremely uncertain – but by being proactive and strategic, we could still greatly increase the probability that those effects will be positive.
The recommendations I suggested seem broadly sensible to me but I’m sure that some are likely to be much more impactful than others, and some major ones are bound to be missing, and each one of them is sufficiently broad that it could cover a whole range of sub-priorities. This is probably an argument for prioritising the first of the principles that you mention, directing the movement toward considering the role of AI in its future, and agreeing on the set of practical, rapid steps that we need to take over the next few years.
Thanks Simon! Yes, AI for inter-species communication is underway. The main organisations working on this at the moment are Earth Species Project (who just received a $17 million grant) and Project CETI. So far as I can tell, work is still in its early stages and mainly focussed on gathering and cleaning audiovisual data and getting a better sense for different species’ portfolio of sounds, rather than actual communication.
I’m still unsure how good this will be for animals. I wrote a brief post on this for the AI for Animals newsletter if you’re interested, but the upshot is that I can see plenty of ways for this technology to be abused (e.g. used for hunting, fishing, exploitation of companion animals for entertainment purposes, co-option by the factory farming industry, etc.). I also think there’s a risk that we only use it for communication with a handful of popular species (e.g. dogs, cats, whales, dolphins), and don’t consider what this means for other less popular species (like farmed chickens).
The most promising project I’ve seen so far is the partnership between Project CETI and the More Than Human Life (MOTH) Project at New York University, which is focussed on the ethical implications of interspecies communication. I hope that these kinds of guidelines will end up driving progress on this rather than corporate interests… and that we focus on using AI to understand animals better on their own terms, rather than trying to communicate with them purely for our own curiosity and entertainment.
Thanks! I think your cynical take could be pretty accurate. From what I can tell, the alt protein industry is only making limited use of AI at the moment and no current applications seem like major game-changers. But at least in theory I’d expect increasingly advanced AI to significantly accelerate progress in this area given its potential for speeding up research and development more broadly, so my goal with this research was to try to get a sense for the kinds of specific use cases that might be particularly promising in the future as general AI capabilities improve and as companies/researchers find ways to address the various bottlenecks I mention. There’s very limited research on AI and alt proteins and I had to rely a lot on general media coverage, which is obviously pretty limited and skewed, so I’m planning to talk more to experts in the area to get a better sense for this, which I might turn into a follow-up post at some point if it seems helpful.
Hey Jeroen! I’m a researcher at ACE and have been doing some work on our country prioritization model. This is a helpful question and one that we’ve been thinking about ourselves.
The general argument is that strong economic performance tends to correlate with liberalism, democracy, and progressive values, which themselves seem to correlate with progressive attitudes towards, and legislation for, animals. This is why it’s included in Mercy For Animals’ Farmed Animal Opportunity Index (FAOI), which we previously used for our evaluations and which our current country prioritization model is still loosely based on.
The relevance of this factor depends on the type of intervention being used—e.g., economic performance is likely to be particularly relevant for programs that depend on securing large amounts of government funding. For a lot of programs it won’t be very relevant, and for some a similar but more relevant indicator of tractability could be the percentage of income not spent on food (which we also use), as countries are probably more likely to allocate resources to animal advocacy if their money and mental bandwidth aren’t spent on securing essential needs. (Because of these kinds of considerations, this year we took a more bespoke approach when considering the likely tractability of each charity’s work, relying less on the quantitative outputs of the country prioritization framework.)
Your intuition about money going further in poorer countries (everything else being equal) makes sense. We seek to capture this where possible on a charity-by-charity basis in our Cost-Effectiveness Assessments. For country prioritization more broadly, in theory it’s possible to account for this using indices like the OECD’s Purchasing Power Parities (PPP) Index. Various issues have been raised with the validity of PPP measurements (some examples here), which is one of the reasons we haven’t included it to date in our prioritization model, but for next year we plan to explore those issues in more detail and what the trade-offs are.
Hope that helps!
Hey, thanks for the question! I’m Max, a researcher at ACE. To provide some additional context to the other helpful comments:
For our 2023 Evaluations we used a weighted factor model to calculate a cost-effectiveness score (rather than DALYs averted) for the charities that we evaluated. You can read more about this process, and the rationale for it, on the ‘Criterion 2’ tab of this page (with some additional context in this Forum comment).
For our 2024 Evaluations, we’re making a few updates to our criteria, including moving to more bespoke Cost-Effectiveness Analyses of each charity’s key programs. This will be more in line with the DALYs-type metrics you mention (though of course will still be subject to plenty of caveats, uncertainties, and wide confidence estimates).
Generally we think the best bet for ACE donors is our Recommended Charity Fund, as this allows us to allocate funds to the charities that we determine need it most at the time of disbursement.
In case you’ve not already seen it, you might also find Rethink Priorities’ Cross-Cause Cost-Effectiveness Model helpful.
Here’s my Calendly if you want to chat in more depth about ACE’s Evaluations process any time :-)
This is a really interesting project, thanks for sharing! Did you get any insights into how these attitudes might vary between animals/products? I assume people will feel a lot more disgusted about the idea of autonomous farms for e.g. cows and pigs than for e.g. insects, fish, and shrimp, and maybe chickens. (You might have seen this already but in theory you can already buy autonomous insect farms.) I guess public attitudes to this will also vary a lot between countries and cultural contexts.
Generally I think it’s really helpful to start thinking about our messaging around AI’s role in animal farming—there seems like a big risk of industry ‘AI-washing’ their products and making out that all their animals now receive round-the-clock individualized care when actually they might just be using AI to maximise productivity and cut costs, with potentially minimal welfare gains.
Thanks Bruce! Yes, I saw that—great to see this area getting some more funding and public attention!
Thanks for highlighting that point Hayven—I agree, and also hope we get to the point where animals are sufficiently well represented in democratic decision-making that those kinds of conflicts are massively reduced.
Thanks Cameron! That’s a helpful point that I didn’t really touch on in this post. Great that you’re doing work in that space—I’m really interested to hear more about it so will get in touch.
Cheers Vasco! Glad you found it helpful and thanks for the useful points :-)
Thanks for this! For what it’s worth I think this is an important and under-explored area and would be really interested in seeing a longer-form post version.
Thanks Rahela, really appreciate the feedback and great to hear that you found it helpful!
Hey, useful question! This is probably the strongest case I’ve seen, focused on the potential legal implications. But it still rests on the assumption that opening the door for legal recognition of certain charismatic species (like whales) will spill over to other species that people are primed to disregard (like chickens), which definitely isn’t a given. If you’ve not already seen it, the MOTH Project at NYU has also come up with a list of principles that seem like a useful guide for anyone doing work in this space.
On the empathy argument: In theory it could still be more persuasive, and harder for people to ignore, if animals were able to more directly communicate feelings of pain, stress, isolation, etc. And this could also reinforce people’s understanding of animals as individuals if different animals express different emotions in similar situations, which in theory could improve their empathy towards them. But yeah, this depends on a lot of things going right: e.g., the technology accurately relaying animals’ communications, animals coming across as complex/sympathetic, etc., and this being relayed by credible people to key audiences in a persuasive way. There’s likely to be a lot of misleading noise in this area as well—maybe you’ll get some big industry players commissioning studies that ‘translate’ animals’ communications in humane-washing ways. And on top of the points you raised, using this kind of tech on e.g. farmed chickens will give a skewed perspective on the intelligence of a typical chicken, given that farmed meat chickens are killed at a few weeks old so you’d be listening to the equivalent of toddlers who’ve been raised in abnormal conditions that probably stifle normal development.
Broader AI uses for understanding animals better could still be really useful (e.g. by enabling more sophisticated bio-sensors and tracking devices, and the software required to process and interpret all the resulting data), so it would be helpful to pivot people more to thinking about all the messier ways that AI could help us understand animals’ lives on their own terms rather than looking for a clean animal-to-human translation. Mal Graham has written about some of the potential applications in this post.