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AI, Pluralism, and (Social) Compensation

Nandhini Swaminathan, David Danks

TL;DR

A practical ethical analysis of the conditions in which social compensation in the response to pluralistic values in a user population may nonetheless be justifiable.

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.

AI, Pluralism, and (Social) Compensation

TL;DR

A practical ethical analysis of the conditions in which social compensation in the response to pluralistic values in a user population may nonetheless be justifiable.

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.
Paper Structure (9 sections, 6 equations, 1 figure, 1 table)

This paper contains 9 sections, 6 equations, 1 figure, 1 table.

Figures (1)

  • Figure 1: Game tree representation of signaling game with values