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AI, Pluralism, and (Social) Compensation

arXiv 2404.19256 ↗First posted 30 Apr 2024cs.AI cs.CY cs.GTcited by 0

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Abstract (arXiv)

One strategy in response to pluralistic values in a user population is to personalize an AI system: if the AI can adapt to the specific values of each individual, then we can potentially avoid many of the challenges of pluralism. Unfortunately, this approach creates a significant ethical issue: if there is an external measure of success for the human-AI team, then the adaptive AI system may develop strategies (sometimes deceptive) to compensate for its human teammate. This phenomenon can be viewed as a form of social compensation, where the AI makes decisions based not on predefined goals but on its human partner's deficiencies in relation to the team's performance objectives. We provide a practical ethical analysis of the conditions in which such compensation may nonetheless be justifiable.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 7 of its 48 references that are in the map. First posted on arXiv 30 Apr 2024.

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7 of 48 references.

References · 7

  1. 2023Direct Preference Optimization: Your Language Model is Secretly a Reward Modelcited by 8,065
  2. 2017Deep reinforcement learning from human preferencescited by 3,912
  3. 2016Concrete Problems in AI Safetycited by 1,642
  4. 2016Cooperative Inverse Reinforcement Learningcited by 300
  5. 2017Deal or No Deal? End-to-End Learning for Negotiation Dialoguescited by 209
  6. 2023AI Deception: A Survey of Examples, Risks, and Potential Solutionscited by 188
  7. 2017A Voting-Based System for Ethical Decision Makingcited by 55

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