PhD in Ethical, Legal, and Social Aspects (ELSA) in Artificial Intelligence (AI) Systems for Promoting Animal Welfare

As a Ph.D. student in this project, you will study, develop, and validate an ELSA-compliant data-driven farmer-in-the- loop decision-support system (DSS) to support effective and responsible decision-making on farms. The DSS will be designed and implemented in generic terms, but its validation will rely on a case study concerning the recommendation of suitable treatment procedures, for example, for mastitis disease in dairy cattle. The focus will be on the development of AI-based solutions that embed ELSA aspects in a recommendation system that could be used to counteract, for example, new strains, high infection pressure, or antibiotic resistance of bacteria.

This Ph.D. position is part of the AI for sustainable food systems (AI4SFS) laboratory, an interdisciplinary research project funded by the Dutch Research Council NWO that will start on June 1st, 2022. The AI4SFS project develops responsible and trustworthy AI in sustainable food systems through the development of an Ethical, Legal, and Social Aspects (ELSA) lab. We will (a) develop insights into the ELSA challenges and opportunities related to AI applications for sustainable food systems, (b) design an ELSA lab methodology (including tools, (ethical and legal) guidelines, and engagement strategies) for responsible AI for the agri-food sector, and (c) conduct multiple case studies where we will integrate ELSA aspects in AI (re)design. After the project, we will develop the ELSA lab into an independent hub for responsible AI for sustainable food systems.

What you tell at birthday parties: I develop and apply AI systems that recommend suitable treatments for animals. My systems comply with ethical, legal, and social aspects of "good stockmanship," appropriate use of medicine, and increased welfare of animals.

What we really need: What we are looking for is a Ph.D. student who is eager to investigate state-of-the-art AI methods that are compliant with ELSA aspects and relate them to animal welfare and production data. You should have demonstrable experience with AI methods. Besides a strong technical background, and an affinity for livestock farming is desirable. You need to be able to work independently and collaborate with other PhDs in the Farm Technology Group, Information Technology Group, and the AI4SFS project, as well as with stakeholders (e.g., veterinarians, pharmaceutical representatives, farmers) in the field of livestock farming.

A typical day at the office: Your days at the office range from frustrating farm data downloads to energy-boosting acceptance letters of your ground-breaking articles, and anything in between!
Today's challenge is to use AI to foster sustainable ELSA-complaint production. The first check of the day: is your on-farm data correctly collected? You start to think of an experiment to test your recently developed recommendation algorithm. You explore the preliminary results and over a mug of coffee, you discuss your ideas with Ricardo, Bedir, Gert, Tarek, and Rik who have been dealing with these issues each in their specific domains.

At lunchtime, you will join other students and researchers to have lunch and take a relaxing de-tour back to your office. The fresh air makes you consider developing an AI model that provides suitable recommendations more robustly. But first, you start a discussion with a fellow student as your sparring partner, after which you sit back to implement the method.
Good job! You have shown that the method can make suitable recommendations in several practical scenarios. Now you start planning how you can concisely write your results into a scientific paper and how the application can be used by relevant stakeholders.