Summary of Incentive Compatibility For Ai Alignment in Sociotechnical Systems: Positions and Prospects, by Zhaowei Zhang et al.
Incentive Compatibility for AI Alignment in Sociotechnical Systems: Positions and Prospects
by Zhaowei Zhang, Fengshuo Bai, Mingzhi Wang, Haoyang Ye, Chengdong Ma, Yaodong Yang
First submitted to arxiv on: 20 Feb 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computers and Society (cs.CY); Computer Science and Game Theory (cs.GT); Human-Computer Interaction (cs.HC)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper addresses the integration of artificial intelligence (AI) into human society, highlighting the importance of understanding the complex sociotechnical nature of AI systems. The authors propose the Incentive Compatibility Sociotechnical Alignment Problem (ICSAP), which focuses on aligning technical and societal components to maintain consensus between AI and human societies in different contexts. They draw parallels with game theory concepts such as mechanism design, contract theory, and Bayesian persuasion to explore ways to bridge the gap between technical and societal aspects of AI development and deployment. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary AI is changing how we live and work, but it’s important to make sure it aligns with human values. Right now, most people are focusing on making AI “smart” without thinking about how it affects society. This paper suggests that instead of just making AI smart, we should also make sure it works well in different social situations. They’re looking at ways to use game theory ideas like mechanism design and contract theory to make sure AI is aligned with what people want. |
Keywords
» Artificial intelligence » Alignment
