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#94 - ALAN CHAN - AI Alignment and Governance #NEURIPS

Machine Learning Street Talk (MLST)

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Navigating Consequentialism in AI and Human Reasoning

This chapter examines the nuances of machine learning terminology, focusing on loss functions and utility functions within optimization contexts. It also critiques the challenges of consequentialist thinking in AI, emphasizing the risks of oversimplifying complex reward dynamics in reinforcement learning.

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