  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.
