2min chapter

Machine Learning Street Talk (MLST) cover image

#92 - SARA HOOKER - Fairness, Interpretability, Language Models

Machine Learning Street Talk (MLST)

CHAPTER

Navigating Fairness and Utility in Reinforcement Learning

This chapter delves into the intricacies of reinforcement learning and its impact on fairness and utility functions. It discusses the challenges of optimizing diverse values amidst varying cultural definitions of fairness and the role of adaptive development sets in machine learning.

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