Facial recognition for sheep. Image from Telling (2018).

Precision livestock farming (PLF) is a reality for many farmed animals today, and its use is likely to accelerate in coming years. Systems that are already being rolled out in factory farms track many aspects of farmed animals’ health, such as feed consumption, weight, lameness, and disease prevalence. This data is then processed through machine learning algorithms to identify patterns, enabling producers to more efficiently manage livestock.

Will PLF usher in a new era of welfare transparency across animal agriculture (“precision welfare”), or are we witnessing the takeoff of never-before-seen levels of fully automated animal exploitation?

🧩 Central questions

1. How PLF works: How do sensor technology and machine learning come together in PLF?
2. Defining and measuring welfare: How is the welfare of farmed animals defined in the context of PLF, and how does this relate to the data that is collected?
3. Risks/Benefits: How might PLF lead to improvements in farmed animal welfare, and how could it lead to greater suffering and exploitation?
4. Welfare vs. profit: Is there a tension between farmed animal welfare and profit? Could PLF be leveraged to optimise for both?
5. Steering: What are the most effective intervention points – from the initial data infrastructure and algorithm design to industry regulation – for ensuring PLF systems genuinely prioritize the interests of farmed animals?

🧭 Learning objectives

1. Understand: Explain how PLF works, and identify major benefits (e.g. improved transparency and accountability) and risks (proxy drift, welfare washing).
2. Assess: Anticipate potential tensions between animal welfare and economic efficiency, drawing connections to outcomes for animals. Compare and contrast different conceptions of farmed animal welfare, highlighting assumptions and risks.
3. Reason: Formulate evidence-based arguments about whether PLF is likely to be net positive or negative for farmed animals.
4. Next Steps: Identify strategic recommendations and key intervention points for steering PLF toward animal-positive outcomes.

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Resources

Required readings

Additional readings (please read at least 1)

Further reading (optional)

Pre-session exercises

Please spend 20-30 minutes completing the following three exercises.

• You can write your responses in bullet point format if that’s easier.
• Submit your responses in the weekly Slack thread created by your facilitator in your channel at least 24 hours before your regularly scheduled meeting.
• Leave at least one comment on somebody else’s response.

What is PLF?

“PLF is a bundle of many different technologies… some PLF systems are plausibly good for animals and some are likely bad.” (Simoneau-Gilbert & Birch 2024)

[125 words] In your own words, briefly define precision livestock farming, making sure to connect these three key elements in your response:

1. What is the role of sensors and data collection?