When H.R.1 (the "Big Beautiful Bill") passed in the U.S. on July 4th, I wondered what it meant for farmed animals. So, I decided to use AI to do a quick analysis for my own interest. (The bill is 130,000+ words long, which is 70% as long as Harry Potter and the Goblet of Fire, making AI a helpful tool for "quick" analysis.)
I haven't seen any other policy analyses come out specifically about the impacts of H.R.1 on farmed animals, so I thought I would share this AI analysis here in case it's helpful.
I think the analysis could be helpful in two ways:
Here are the main two documents:
More (very important) details and disclaimers below.
(Edit 2025-07-22: I've gotten a request to put some of the findings from the analysis here in the post itself, which I didn't originally do for fear of people casually taking these as truth without understanding that this report was fully AI generated. So with all due caveats and disclaimers, here are potential takeaways.)
If the AI analysis is correct, here are some of the primary cross-cutting themes—pretty much all of which seem to further entrench CAFOs and reduce avenues for fighting them:
(Copied from the executive summary)
The short story is that much of the bill improves the economics of factory farming (through increased crop subsidies, better insurance, tax credits for manure gas production, etc.) and strips away environmental and other regulations that could be used to fight factory farms. If the analysis is correct, this bill is a huge gift to large-scale animal agriculture.
I used the OpenAI o3 "advanced reasoning" model which tends to perform fairly well on complex analysis questions like this. I've used this model a lot in my work and personal life, and I tend to trust o3's general analysis 80–90% of the time, if I had to guesstimate. However, I also trust that there will occasionally be errors, especially when it comes to specific numbers.
I did not do thorough validation of the analysis (I did read and spot check some things) and am relying here on my trust of the o3 model being "mostly right most of the time", which means it's possible that large portions of the analysis are completely incorrect—if anyone discovers that the analysis is in large part incorrect, please let me know. All statements and conclusions in either of these reports should be independently verified before use. My work does not directly involve policy-making, lobbying, or economic analysis, so I am not currently planning on using this analysis for any advocacy work.
Since the bill is very long, I used a Python script to split the bill into ~50 chunks and process each chunk through o3 using the API, using a detailed prompt for how I wanted the analysis conducted (i.e. through the lens of farmed animal advocacy). This process could be adapted fairly easily to analyze the bill through a different lens, as well.
I think this approach could be very good for quickly discovering insights, keeping up with things at a pace that's otherwise impossible, and conducting "good enough" analyses when you don't have the expertise to do so. I would not recommend: copy/pasting without double-checking; quoting insights without verification; or relying on this analysis for high-stakes situations where 100% factual accuracy is needed. Rather than this being the last step of research, I would view this as a first step, with the experts picking it up from here.
If anyone is interested in talking more about the potential for AI to help with policy tracking or policy analysis, please feel free to reach out. If AI analysis is good enough and accurate enough, it's possible that this type of approach could be used to help automatically track and analyze bills for their impacts on farmed animals, leading to advocates being able to respond more quickly in the future. Any publicly available text on the Internet can now be automatically analyzed by AI for animal impacts—I think there's probably a lot of opportunity there.
(For the curious: AI did not write any of this post, with the exception of the 5 "cross cutting themes" copied from the executive summary.)