Faculty Friday with Sina Fazelpour: The Impact of Group Decision-Making on Responsible AI and Training Data

Sina Fazelpour


When it comes to machine learning and artificial intelligence, training data doesn’t come out of a vacuum. It’s based on historical decisions that we have made. In this week’s EAI Faculty Friday video, we hear from Northeastern University Assistant Professor Sina Fazelpour about how training data is directly impacted by the decision-making of different groups of individuals with their own backgrounds, identities, and views, and how those decisions could lead to negative consequences. Check out the video to learn more!



Sina Fazelpour is an assistant professor of philosophy and computer science at Northeastern University. Sina studies the social impacts and governance of data-driven and artificial intelligence technologies, with a focus on justice, diversity, and reliability in sociotechnical, human-AI systems. He also works on understanding the concepts and consequences of diversity in social groups and networks. To address these issues, he draws on analytical tools of philosophy, methods of cognitive science, and formal techniques of agent-based simulation and machine learning. His articles on these and other areas have appeared in Philosophy of SciencePhilosophy and Phenomenological ResearchSyntheseEuropean Journal for Philosophy of ScienceCognition, and more. 

Before joining Northeastern, Sina was a Social Sciences and Humanities Research Council Postdoctoral Fellow in the Department of Philosophy at Carnegie Mellon University, with a secondary affiliation with the Machine Learning Department. In addition to a doctorate in philosophy, Sina holds a Master of Science in medical biophysics and a Bachelor of Engineering in electrical and biomedical engineering.