Fairness in Machine Learning - Lessons from Political Philosophy

Explore the intersection of machine learning and political philosophy in this thought-provoking 20-minute conference talk by Reuben Binns from the University of Oxford. Delve into the complex issue of fairness in machine learning algorithms and discover valuable insights drawn from political philosophy. Examine how ethical principles and theories of justice can inform the development of fair AI systems. Gain a deeper understanding of the challenges and potential solutions in addressing bias and discrimination in automated decision-making processes. Learn about the implications of different fairness definitions and their practical applications in real-world scenarios. Engage with cutting-edge research presented at the FAT* 2018 conference, bridging the gap between computer science and social sciences to create more equitable and just AI technologies.

FAT* 2018: Reuben Binns - Fairness in Machine Learning: Lessons from Political Philosophy