AI, Pluralism, and (Social) Compensation

Abstract

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.

Cite

Text

Swaminathan and Danks. "AI, Pluralism, and (Social) Compensation." NeurIPS 2024 Workshops: Pluralistic-Alignment, 2024.

Markdown

[Swaminathan and Danks. "AI, Pluralism, and (Social) Compensation." NeurIPS 2024 Workshops: Pluralistic-Alignment, 2024.](https://mlanthology.org/neuripsw/2024/swaminathan2024neuripsw-ai/)

BibTeX

@inproceedings{swaminathan2024neuripsw-ai,
  title     = {{AI, Pluralism, and (Social) Compensation}},
  author    = {Swaminathan, Nandhini and Danks, David},
  booktitle = {NeurIPS 2024 Workshops: Pluralistic-Alignment},
  year      = {2024},
  url       = {https://mlanthology.org/neuripsw/2024/swaminathan2024neuripsw-ai/}
}