Hi Sam, Thank you for sharing your thoughts. You mentioned that AI is already contributing to worsening conditions, but I’m not fully convinced that the examples you provided support this claim. Both examples seem to reflect broader trends of technological intensification, rather than generative AI specifically (which wasn’t available at the time those developments occurred). My focus is on generative AI, while other forms like machine learning and deep learning are already deeply embedded in industry practices.
That said, my main point remains: other things being equal, and acknowledging that factory farms are, unfortunately, a current reality, I hold an optimistic view of AI’s introduction into the industry: AI can monitor and address key production factors that overlap with welfare concerns, such as body scores, heat stress at the individual level, and the detection of injuries or diseases, far more effectively than traditional methods.
Rather than advocating for the abolition of AI in factory farming, I believe we should focus on campaigning for transparency. Specifically, the data gathered by AI and other monitoring technologies should be made accessible to independent stakeholders. This would create greater accountability and improve oversight.
Transparency-focused legislation is more plausible than bans on AI across an entire sector. It’s difficult to argue against the idea that the food industry should be transparent about its non-proprietary practices, particularly when animal welfare is concerned. While I’m not naive about existing challenges, such as ag-gag laws and potential loopholes, the chances of passing transparency laws are higher than prohibiting the use of technology outright.
Thanks for your reply and for clarifying your perspective. I do agree that the most harmful applications of PLF technology we’re currently seeing are driven by machine learning and deep learning, rather than generative AI. When I refer to AI in factory farming, I’m using the term in its broader sense to include these technologies as well—beyond just large language models specifically.
On the main point, I think campaigns for restrictions or bans on AI in factory farming can actively strengthen the push for transparency, rather than being at odds with it.
Broadly speaking, transparency campaigns without accompanying pressure tend to fail across cause areas. Companies are unlikely to willingly share data unless there’s significant public scrutiny or regulatory threat. Calls for a ban increase that scrutiny by raising public awareness about the risks AI poses to animals, highlighting the need for accountability and uniting broad coalitions that increase political power.
The risk, if the movement focuses solely on promoting “positive” uses of PLF, is that we create an environment where welfare washing and complacency thrive. Companies will only adopt welfare improvements where they align with profitability, and even then, these measures are often incidental rather than intentional. In many cases, welfare “improvements” serve to entrench factory farming further, creating the illusion of progress whilst masking systemic harm. For example, technologies that reduce disease outbreaks may allow producers to justify increasing stocking densities, leading to even greater overall suffering, despite the initial appearance of progress.
To meaningfully challenge these systems, we need radical counterpressure—calls for bans or restrictions. Without this counterbalance, we increase the probability that AI will cement factory farming’s dominance rather than dismantle it. History shows us that meaningful action—particularly changes that hurt industry interests—rarely happens without radical demands to push the boundaries of what’s politically acceptable.
Campaigns for bans aren’t in opposition with calls for transparency, they’re a strategic neccessity in achieving them. They apply the pressure needed to drive reforms, expose harmful practices, and keep the ultimate goal—fighting factory farming—at the center of the conversation. Without this pressure, transparency risks becoming toothless, co-opted as a tool for welfare-washing or superficial improvements that merely serve industry interests. Coupling bold demands for bans with transparency-focused efforts ensures that any improvements are not only genuine and accountable, but also prevent the illusion of progress from entrenching the very systems we aim to dismantle.
In this way, the two strategies can complement each other: bold calls for bans provide the pressure and visibility needed to make transparency campaigns more effective.
Hi Sam,
Thank you for sharing your thoughts. You mentioned that AI is already contributing to worsening conditions, but I’m not fully convinced that the examples you provided support this claim. Both examples seem to reflect broader trends of technological intensification, rather than generative AI specifically (which wasn’t available at the time those developments occurred). My focus is on generative AI, while other forms like machine learning and deep learning are already deeply embedded in industry practices.
That said, my main point remains: other things being equal, and acknowledging that factory farms are, unfortunately, a current reality, I hold an optimistic view of AI’s introduction into the industry: AI can monitor and address key production factors that overlap with welfare concerns, such as body scores, heat stress at the individual level, and the detection of injuries or diseases, far more effectively than traditional methods.
Rather than advocating for the abolition of AI in factory farming, I believe we should focus on campaigning for transparency. Specifically, the data gathered by AI and other monitoring technologies should be made accessible to independent stakeholders. This would create greater accountability and improve oversight.
Transparency-focused legislation is more plausible than bans on AI across an entire sector. It’s difficult to argue against the idea that the food industry should be transparent about its non-proprietary practices, particularly when animal welfare is concerned. While I’m not naive about existing challenges, such as ag-gag laws and potential loopholes, the chances of passing transparency laws are higher than prohibiting the use of technology outright.
Thanks for your reply and for clarifying your perspective. I do agree that the most harmful applications of PLF technology we’re currently seeing are driven by machine learning and deep learning, rather than generative AI. When I refer to AI in factory farming, I’m using the term in its broader sense to include these technologies as well—beyond just large language models specifically.
On the main point, I think campaigns for restrictions or bans on AI in factory farming can actively strengthen the push for transparency, rather than being at odds with it.
Broadly speaking, transparency campaigns without accompanying pressure tend to fail across cause areas. Companies are unlikely to willingly share data unless there’s significant public scrutiny or regulatory threat. Calls for a ban increase that scrutiny by raising public awareness about the risks AI poses to animals, highlighting the need for accountability and uniting broad coalitions that increase political power.
The risk, if the movement focuses solely on promoting “positive” uses of PLF, is that we create an environment where welfare washing and complacency thrive. Companies will only adopt welfare improvements where they align with profitability, and even then, these measures are often incidental rather than intentional. In many cases, welfare “improvements” serve to entrench factory farming further, creating the illusion of progress whilst masking systemic harm. For example, technologies that reduce disease outbreaks may allow producers to justify increasing stocking densities, leading to even greater overall suffering, despite the initial appearance of progress.
To meaningfully challenge these systems, we need radical counterpressure—calls for bans or restrictions. Without this counterbalance, we increase the probability that AI will cement factory farming’s dominance rather than dismantle it. History shows us that meaningful action—particularly changes that hurt industry interests—rarely happens without radical demands to push the boundaries of what’s politically acceptable.
Campaigns for bans aren’t in opposition with calls for transparency, they’re a strategic neccessity in achieving them. They apply the pressure needed to drive reforms, expose harmful practices, and keep the ultimate goal—fighting factory farming—at the center of the conversation. Without this pressure, transparency risks becoming toothless, co-opted as a tool for welfare-washing or superficial improvements that merely serve industry interests. Coupling bold demands for bans with transparency-focused efforts ensures that any improvements are not only genuine and accountable, but also prevent the illusion of progress from entrenching the very systems we aim to dismantle.
In this way, the two strategies can complement each other: bold calls for bans provide the pressure and visibility needed to make transparency campaigns more effective.