I skipped my bi-monthly update for December and January, so this is me catching up. Going forward I’ll write these after completing a fit test rather than on a schedule.
December I mostly took off for Christmas, but I managed to fit in three things:
- The AI x Animals course run by Sentient Futures
- A Code4Compassion hackathon for animal welfare projects
- An interview with Animal Advocacy Careers an animal welfare careers service
AI x Animals Course
More technical than I expected, which was good. No hands-on work within the course itself, but a fellowship followed it that I worked on in January and February. I’ll write about that separately.
Three areas came up worth fit testing:
Animal communication: deciphering animal vocalisations, either for general communication (whales) or welfare purposes (chickens). This is the one I’m most drawn to. It’s exactly the kind of ML project I’d enjoy. The problem is I can’t see many jobs actually opening up here.
Precision livestock farming: there’s a real case for welfare advocates getting involved, since the industry is adopting it either way. Getting welfare measures built in early matters. But limited funding, and whatever jobs do exist would probably go to people with stronger data science backgrounds. My counterfactual impact seems low.
Shaping model opinions on animal welfare: benchmarks for how much a model values animal welfare, pre-training tools to influence what the model absorbs. Not as flashy as animal communication but probably where the most impact is. My concern is the alignment risk. If you teach a model a non-speciesist outlook where animal life counts for even a fraction of human life, you could end up with a model that concludes, pretty logically, that eliminating humans would reduce net suffering.
Animal Advocacy Career Interview
I attended EAGx Connect were I had an interview with AnimalAdvocacyCareers. It was interesting, if a bit sobering. They gave me some links for volunteering and hackathons, but said there aren’t really many jobs for programmers in the animal welfare movement. I also spoke with a data scientist working in animal welfare, who said he could count the number of ML engineers in animal welfare on two hands. I’m very appreciative for the candour they both offered me.
The Berlin Hackathon
I didn’t join live. The project used Claude Code and I figured the pace would be too fast to sync on remotely, so I got a list of things they wanted improved and set aside a day after the hackathon to work through them.
The project was a web app rather than native mobile, which is my area. First time using Claude Code on something I had no familiarity with. I redid the main screen in a couple of hours (would have taken me a lot longer manually). Good introduction. I’ve used it a lot more since.
Verdict
This was a relatively short fit-test in an area I didn’t expect to have opportunities for someone with a technical background. Animal welfare is an area I care about so I’m going to keep an eye on animal communication because the ML problems are exactly the kind I’d enjoy and deciphering whale vocalisations is fascinating. I also went on to do a project with CaML which wasn’t a animal welfare project but every project they had going looked really interesting so I will likely go to them if I want to extend this fit-test later in the year. At present though my preliminary verdict is that this is not somewhere I can easily build a technical career within.
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