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What is Optimizing Model Selection For Compound AI Systems about?

This position paper critiques empirical human-AI alignment, arguing that it can introduce statistical biases that misrepresent alignment goals. The authors advocate for prescriptive alignment approaches, which focus on defining clear axioms rather than relying on observed human behavior. They emphasize the need for AI systems to be adjusted post-deployment to avoid biases and enhance their potential for scientific discovery.

Author

nitinwahie1992

Language

EN