Most published animal welfare research is carried out by universities in labs.
I kind of assumed that this was a necessity in some way. Either stuff can't get published if you're not affiliated with a university, or universities just have the necessary rigour to get things done. I just assumed there's a whole host of reasons why this had to be the case, but I think those are mistaken.
And as a result, I think that when you start to look at universities, it starts to look strangely expensive to get things done. Things have a much longer time scale than is useful. And the facilities that they have to set up are often not good indicators of what reality looks like outside of the lab.
I think that high-quality welfare work can be done outside of universities and in fact, I think a huge amount of welfare work is done outside universities on farms but just isn't actually published and available in the literature. It just needs to be brought to the surface.
I want to see if it's possible for the animal welfare movement to rethink the model of research work and actively turn farms into welfare labs. I don't think this is necessarily possible across the board, but I do think there are quite a few engaged farmers who would be willing to collaborate on this. They already have a really great setup and may already be doing a lot of this work anyway.
How do we actually get data from farms?
There are probably a few things we could do here. Like through insurance or banks or auditors, providing this data in an anonymised way to various authorities could become a requirement of receiving approval for loans, coverage, etc. We could work through unions like the National Farmers Union, where there might be a collective good for them to share the data and share that knowledge. We could pay them directly for the data and subsidise the costs to facilitate data sharing. We could set up our own animal welfare certification body that requires data sharing.
We could start with data in places where there's already lots of data already - aquaculture and salmon in particular seem to be doing really well. There are companies like AgriGates, which is like data infrastructure for Precision Livestock Farming.
There are already places that are tracking lots of data, like slaughterhouses that already track a bunch of data from a bunch of different farms. They track things like body condition scores for the animals that they receive and they do this to pay farmers depending on the scores. So we could link this to on-farm condition data sets. Although we might be skeptical about the actual quality of this data, we can maybe get it from freedom of information requests or public records.
Can we turn them into Welfare Labs?
What is it that we'd actually want to do? I think this would start by identifying pertinent welfare indicators and exploring what a sort of coalition with farms would look like. It's also worth trying to tap into some of the funding sources that universities are already accessing.
We probably want to do lots of preference testing or motivation testing or enrichment testing. For example, variable lighting: Welfare researchers have already been paid by Tyson to do variable lighting tests for broilers. This kind of work is already happening, it's just not getting published in the traditional academic sense.
It's important to talk with farmers, and in particular, farmers whom we think could be really engaged, like Vertical Oceans. Farmers in China could also be amenable to this - they are interested in precision farming, and they have subsidies for installing PLF tech.
The RSPCA wants to monitor their certification scheme using precision welfare tech. Can we just find out what it is they actually want and then just build it ourselves? There's no reason why this needs to go through a university.
Why this makes sense
When you think about it, farmers are already running experiments all the time, including welfare inputs and/or outcomes. They're testing different lighting regimes, different feeding schedules, different housing configurations. They're collecting data on mortality, feed conversion, growth rates. The only difference is that they're not writing it up for peer review.
And actually, their data might be more valuable than university data in many ways. It's collected under real commercial conditions, with commercial genetics, at commercial scale. A university study with 500 birds doesn't necessarily tell you what will happen with 50,000 birds in a real barn.
The timeline issue is also crucial. By the time a university study is designed, funded, approved by ethics committees, run, analysed, written up, and published, we're generally looking at 3-5 years minimum. We need answers now. If we can create a system where farmers can share what they're learning in real time, we could accelerate welfare improvements dramatically.
I think this is one of those ideas that seems radical at first but then becomes obvious when you think about it. Of course we should be learning from what's actually happening on farms. Of course farmers should be partners in welfare research, not just subjects of it. The infrastructure is already there, the data is already being collected, we just need to connect the dots.
Academic studies are definitely slow, but 3-5 years strikes me as extremely slow, even for academia.
I'm generally on board with what you're describing but I wonder whether there's also opportunities to work better with academia? Like if you're the one providing the funding, you might be able to negotiate with them and keep them accountable to timelines. There's probably also lots of variability between academics so you can identify the ones that are capable of executing well and quickly, and then work with them.
Some half-baked thoughts that you probably have already considered:
Definitely agree that welfare science could be moving much faster than it currently is, and part of that is tied to the research process in universities. But many of the restrictions that make the process slower do have benefits wrt to rigour.
In an ideal world, the research produced by universities is trusted because it passes through a structured process designed to limit bias and enhance rigour. A good study is typically specified in advance: what intervention will occur, how outcomes will be measured, and how they will be analysed. Measurement uses agreed definitions so results are comparable across sites. The protocol is documented and deviations are recorded. Data are retained and can be inspected. Researchers are accountable to supervisors, ethics committees, and institutional reputation, which creates penalties for selective reporting.
After that, peer review functions as an additional filter. Independent reviewers, who (hopefully) have no stake in the result, check whether alternative explanations could account for the findings, whether statistics are appropriate, and whether the conclusions match the data. Weak causal claims can be weeded out at this stage, and appropriate qualifications made.
On farms, how much of this holds? I imagine that the same person might feasibly implement the change, observe the outcome, and possibly even benefit from their interpretation. Management conditions might change simultaneously, unsuccessful trials might be rarely recorded in a standardised way, and there may be no routine adversarial check of the inference by a domain expert. That makes it difficult for third parties to judge whether an alleged welfare improvement genuinely reflects the supposed intervention.
Collecting farm data is feasible, but achieving comparable credibility requires some mechanism(s) for maintaining rigour, including but not limited to: predefined methods, independent verification, and systematic challenge of the conclusions by experts.
My two genuine (not-leading) questions would be:
1) How feasible is this in the farm environment? This means not only implementing the mechanisms to ensure rigour, but also ensuring that key stakeholders trust the process. Even if your research is sound, if key stakeholders won't trust your results because you did it in a farm and not a lab, then you definitely have to take that into consideration rather than scoff at it.
2) Once you implement those mechanisms for rigour, are you still significantly quicker and more streamlined than university research? (If the answer to this is yes, one would wonder why universities aren't able to do the same. But obviously there are non-research related factors influencing university research).
I imagine that there's a trade-off between rigour and resources, where you the more rigour you want, the more resources (including time) you need. So a third bonus question is, how much rigour is enough?
Thanks for the thoughtful comment!
I guess what I mean by Welfare Labs in this context is something lower down on the Scientific Evidence Pyramid. There doesn't seem to be an agreed-upon version of the evidence pyramid (especially in animal welfare), but often it looks something like this:
Where the lower down the pyramid you go, the weaker the evidence is. I think that academic research and the process you outlined above falls in the category of Primary Studies. But I think that leaping from Opinion to Primary Study often misses out this useful middle step of Observational Studies. And I think farms are well placed to rapidly test hypotheses, before committing to a Primary Study with more rigour.
To answer your specific questions:
Executive summary: The author argues that animal welfare research does not need to be primarily university-and-lab-based, and that the movement should “turn farms into welfare labs” by surfacing and sharing high-quality welfare data already generated under commercial conditions.
Key points:
This comment was auto-generated by the EA Forum Team. Feel free to point out issues with this summary by replying to the comment, and contact us if you have feedback.
Cool idea. I assume you're tracking Innovate Animal Ag already; they might be interested in this