mlsanityData to 7 Oct 2026

Roadmap on Incentive Compatibility for AI Alignment and Governance in Sociotechnical Systems

arXiv 2402.12907 ↗First posted 20 Feb 2024cs.AI cs.CY cs.GTcited by 6

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Abstract (arXiv)

The burgeoning integration of artificial intelligence (AI) into human society brings forth significant implications for societal governance and safety. While considerable strides have been made in addressing AI alignment challenges, existing methodologies primarily focus on technical facets, often neglecting the intricate sociotechnical nature of AI systems, which can lead to a misalignment between the development and deployment contexts. To this end, we posit a new problem worth exploring: Incentive Compatibility Sociotechnical Alignment Problem (ICSAP). We hope this can call for more researchers to explore how to leverage the principles of Incentive Compatibility (IC) from game theory to bridge the gap between technical and societal components to maintain AI consensus with human societies in different contexts. We further discuss three classical game problems for achieving IC: mechanism design, contract theory, and Bayesian persuasion, in addressing the perspectives, potentials, and challenges of solving ICSAP, and provide preliminary implementation conceptions.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 30 of its 84 references that are in the map. First posted on arXiv 20 Feb 2024.

Builds on

30 of 84 references.

References · 30

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18 more
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 2; 2026: 3.

6 papers.