Roadmap on Incentive Compatibility for AI Alignment and Governance in Sociotechnical Systems
Zhaowei Zhang; Fengshuo Bai; Mingzhi Wang; Haoyang Ye; Chengdong Ma; Yaodong Yang · 2025 · AGI 2025 (Springer LNAI), pp. 370-380 background low priority coded
Main argument
Thesis: existing alignment focuses on technical facets and neglects the sociotechnical gap between development and deployment contexts; game-theoretic INCENTIVE COMPATIBILITY (mechanism design, contract theory, Bayesian persuasion) should bridge technical and societal components to 'maintain AI consensus with human societies in different contexts' - the ICSAP problem statement plus preliminary implementation conceptions.
Why it matters here
Names the development-vs-deployment context gap as the 'Incentive Compatibility Sociotechnical Alignment Problem' and proposes game-theoretic bridges (mechanism design, contract theory, Bayesian persuasion). The Peking/BIGAI group's governance-side companion to the Ji survey - a technical-community acknowledgment that alignment fails WITHOUT institutional incentive design.
Reading notes
Compact treatment (11pp roadmap; same Yaodong Yang group as Ji et al. survey and HVAE). Abstract + framing read.
Zhang, Z., et al. (2025). Roadmap on Incentive Compatibility for AI Alignment and Governance in Sociotechnical Systems. In AGI 2025 Proceedings Part II. Springer.