The content discusses the integration of mechanism design, contract theory, and Bayesian persuasion to bridge the sociotechnical gap in AI alignment. It explores potentials and challenges of each approach, highlighting the importance of aligning AI behavior with human values.
The paper emphasizes the need for exploring Incentive Compatibility Sociotechnical Alignment Problem (ICSAP) to address both technical and societal aspects simultaneously. It proposes leveraging principles from game theory to maintain AI consensus with human societies across different contexts.
Key points include discussing mechanism design, contract theory, and Bayesian persuasion as tools to align AI behavior with human values. The challenges of bridging asymmetric information gaps and ensuring moral hazard mitigation are highlighted.
The potential societal consequences of this work are acknowledged but not specifically highlighted. The content aims to advance the field of Machine Learning through a comprehensive exploration of AI alignment strategies.
In un'altra lingua
dal contenuto originale
arxiv.org
Approfondimenti chiave tratti da
by Zhaowei Zhan... alle arxiv.org 03-04-2024
https://arxiv.org/pdf/2402.12907.pdfDomande più approfondite