Half Is Heroic: Rewarding Non-Answers for Responsible AI Decision-Making
Sergio Bruccoleri
Abstract
This talk explores a new evaluation paradigm that moves beyond binary correctness to tricategorical reasoning, rewarding AI systems for responsible restraint and ethical uncertainty. We will share insights and early metrics showing how human-in-the-loop evaluation can strengthen content safety and model reliability in real-world applications.
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