Lets fix factory farming with AI

A synthesis paper by Yiting Lu et al. published in MDPI's Veterinary Sciences journal describes how deep learning models are being applied to monitor and manage viral diseases in livestock, offering a way to detect outbreaks early and reduce pandemic risks from factory farms. The paper highlights that while a global ban on intensive animal agriculture is not imminent, AI-driven precision livestock farming can help mitigate the spread of pathogens such as avian influenza (H5N1) in the meantime.

Let me preface this by saying: I am a huge proponent of banning intensive farm agriculture https://link.springer.com/article/10.1007/s41055-021-00089-6 in its current form and probably do not need to list the plethora of negative effects it has, not only on the animals involved, but also biodiversity, emissions of greenhouse gasses and human health, not to even mention their potential to function as breeding ground for possibly zoonotic diseases. Although this transition away from factory-farmed meats has already begun https://law.lclark.edu/live/files/36825-8sebopdf in many countries with a push for alternative protein, the ban of hen cages in certain parts of Europe, the ban on gestational crates for pigs in Sweden and Norway, along with other small but relevant steps, it is clear that a global pivot away from industrial agriculture isn't yet around the corner. Some argue we should aim to ban industrial animal farming by 2050 https://verfassungsblog.de/global-ban-on-industrial-animal-agriculture/ and I'd like to be so hopeful. In the mean time these farms present a huge risk when it comes to communicable diseases. Factory farms form the perfect environment for breeding pathogens https://www.nationofchange.org/2025/06/13/factory-farms-and-the-next-pandemic-how-industrial-animal-agriculture-fuels-global-health-threats/ . An enclosure with thousands of genetically similar animals with elevated stress levels, weakened immune systems, close contact with animals under-ventilated conditions, and oftentimes on a consistent dose of antibiotics. It's almost a textbook example of a perfect place for viruses to evolve. Additionally, due to the use of antibiotics, it is the perfect breeding ground for drug-resistant bacteria. This not only causes outbreaks between animals of the same species as well as inter species like the spillover of bird flu H5N1 into dairy cows https://theecologist.org/2025/apr/08/factory-farming-and-next-global-pandemic , but also plenty of chances for transmission between animals and https://www.cdc.gov/bird-flu/situation-summary/index.html humans https://pmc.ncbi.nlm.nih.gov/articles/PMC4593676/ due to handling of animals, animal transport, etc. As well as a chance for spillback into animals, allowing the pathogen to further evolve under the radar. The major player here is influenza. Specifically the spillover potential https://pmc.ncbi.nlm.nih.gov/articles/PMC4593676/ of avian influenza is being closely https://www.thelancet.com/journals/laninf/article/PIIS1473-3099 24 00238-X/fulltext looked https://publichealth.jhu.edu/2025/bird-flu-is-raising-red-flags-among-health-officials at https://www.cdc.gov/bird-flu/situation-summary/index.html . Preventing this spread or catching early signs of these diseases could not only prevent the culling of millions of animals https://www.cdc.gov/bird-flu/situation-summary/current-bird-flu-situation-in-poultry.html and the disruption of food systems but also helps prevent global pandemics. The obvious solution would be large scale governmental regulations and pushback against factory farming. But while we willfully ignore this issue because the world has too big of a meat appetite https://pmc.ncbi.nlm.nih.gov/articles/PMC9756515/ , there are ways to hamper the spread of diseases in these settings. Considering the more and more widespread adoption of deep learning models across all industries, it would be surprising if we didn't get to see a similar trend in the animal agriculture industry. It's a part of the ongoing push towards precision livestock farming which aims to offer a real-time monitoring and automation system for farmers. It's aimed towards improving the production, health, welfare of animals and as far as I can tell is unsurprisingly mostly economically driven. A synthesis paper by Yiting Lu et. al. https://www.mdpi.com/2306-7381/12/12/1129 describes advances that have been made in animal viral disease management. Direct monitoring of communicable diseases consist of two main components: Moreover, risk factors can be monitored with machine learning to predict farm-level disease risk and spread and support targeted surveillance https://www.mdpi.com/2306-7381/12/12/1129 . Many technical challenges still remain including unbalanced datasets, the structural and evolutionary complexity of viruses, and the poor cross-species transferability of predictive models before we get to a comprehensive disease monitoring suite, but the foundation is definitely there. Precision livestock farming PLF methods have received significant https://sentientmedia.org/ai-is-coming-to-factory-farms/ criticism https://givingcompass.org/article/will-ai-in-factory-farms-help-the-animals-or-strengthen-the-industrial-farming-system from https://forum.effectivealtruism.org/posts/BhAJu2fMAEj6ZeTw5/animal-advocates-should-campaign-to-restrict-ai-precision animal-welfare groups, stating that this could bolster the existence of factory farms under some kind of "disease-prevention-washing" label or will likely increase total animals farmed due to efficiency gains, disregarding the suffering of animals. I agree. The facts, however, are that right now communicable diseases in farms are causing animals to die https://www.sciencedirect.com/topics/medicine-and-dentistry/animal-culling , people to die https://www.fao.org/animal-health/situation-updates/avian-influenza-A%28H7N9%29-virus/en and risk causing another global pandemic https://www.isglobal.org/en/healthisglobal/-/custom-blog-portlet/a-new-list-of-priority-pathogens-that-could-cause-the-next-pandemic . Buller et. al. https://pmc.ncbi.nlm.nih.gov/articles/PMC7599464/ state that "A combined multi-actor approach that brings together industry, scientists, food chain actors, policy-makers and NGOs is needed to develop and use the promise of PLF for the creative and effective improvement of farmed animal welfare". Not only is this holistic approach currently lacking, but it does not include the discourse around pandemic prevention.