Exploring Data Partitions and Fairness in Machine Learning

Today we’re joined by Sarah Brown, an Assistant Professor of Computer Science at the University of Rhode Island.

In our conversation with Sarah, whose research focuses on Fairness in AI, we discuss why a “systems-level” approach is necessary when thinking about ethical and fairness issues in models and algorithms. We also explore Wiggum: a fairness forensics tool, which explores bias and allows for regular auditing of data, as well as her ongoing collaboration with a social psychologist to explore how people perceive ethics and fairness.

Finally, we talk through the role of tools in assessing fairness and bias, and the importance of understanding the decisions the tools are making.

The complete show notes can be found at twimlai.com/go/456.