EVENTS

As the number of job applications increase, hiring managers have turned to artificial intelligence (AI) to help them make decisions faster, and perhaps better. Where once each manager did their own first rough cut of files, now third party software algorithms sort applications for many firms. Human mistakes are inevitable, but fortunately heterogenous. Not so with machine decision-making. Relying on the same AI systems means that each firm makes the same mistakes and suffering from the same biases. When the same person re-encounters the same model again and again, or models trained on the same dataset, she might be wrongly rejected again and again. In this talk, I will argue that it is wrong to allow the quirks of an algorithmic system to consistently exclude a small number of people from consequential opportunities, and I will suggest solutions that can help ameliorate the harm to individuals.

Prof. Dr. Kathleen A. Creel (Northeastern University, Boston, MA, USA)

Kathleen Creel is an Assistant Professor at Northeastern University, cross appointed between the Department of Philosophy and Religion and Khoury College of Computer Sciences. Her research explores the moral, political, and epistemic implications of machine learning as it is used in non-state automated decision making and in science. She co-leads Northeastern’s AI and Data Ethics Training Program and is a winner of the International Association of Computing and Philosophy’s 2023 Herbert Simon Award.

Institutions

• UHH