Algorithms and Fairness
In this course we discuss the increasingly important question of what AI fairness means and how AI fairness can be addressed by legal, social science, and applied mathematical research to inform policy making.
The aim of this course is to understand the history of fairness as defined in law, social science, and applied mathematics research; to identify logical and mathematical conflicts between different definitions of fairness; and to explain why fairness and AI is a highly contested and unresolved problem in law.
This block course will be broken into three components:
Fair outcomes: the equality/equity debate
- The proliferation of fairness definitions
- Impossibility theorems
- AI & fundamental rights
Fair process
- Appropriate use of AI in administrative or judicial roles
- AI counterparties
- Fair markets
Fair distribution
- Distributing scarce resources
- Data markets and data labor
- The future of work