A new paper proposes a three-step framework for establishing rational trust in generative AI outputs, addressing the challenges posed by the "generality problem" and the "Gettier machine" phenomenon. The proposed "Justified True Output" (JTO) criterion suggests that users should acquire, understand, and independently verify AI-generated information. This approach aims to provide a stakes-indexed method for determining when AI outputs can be rationally trusted, even as models improve and the concept of the extended mind is considered. AI
IMPACT Offers a new epistemological framework for evaluating the reliability of generative AI outputs, potentially influencing how users interact with and trust AI systems.
RANK_REASON Academic paper proposing a new framework for AI trust. [lever_c_demoted from research: ic=1 ai=1.0]
- arXiv
- Generality problem
- generative artificial intelligence
- Gettier Machine
- Hugging Face
- JTB Corporation
- Justified True Output
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