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