AI Alignment From Social Choice Perspectives
Alignment from human feedback uses human judgments about model outputs to steer the behavior of language models after pretraining. When those judgments reflect conflicting views of desirable behavior, the learned objective becomes an aggregate determination of what the model should prefer. We survey recent work that has studied this aggregation problem through the lens of social choice theory. We illustrate how the social choice perspective helps identify failure modes in the feedback aggregatio
Record details
Published: 19 June 2026
Source: arXiv
Category: Research
Topics: Safety & alignment
Retrieved: 14 July 2026
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ethics.ai (19 June 2026), “AI Alignment From Social Choice Perspectives,” evidence record 762, https://ethics.ai/record/762 (originally published by arXiv).
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