Ep 54: Princeton Researcher Arvind Narayanan on the Limitations of Agent Evals, AI’s Societal Impact & Important Lessons from History
Unsupervised Learning
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Evaluating AI's Role in Decision-Making
This chapter explores the complexities of assessing product market fit for agentic AI, contrasting tools that assist users with those that autonomously make decisions. It addresses the challenges of inaccurate outputs in high-stakes scenarios and highlights the importance of user preferences in AI system refinement. The discussion also includes innovative evaluation methods, like human-in-the-loop systems, to enhance realism in assessing AI agent performance.
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