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Evidence record 697 · automatically gathered

Affective AI Safety: The Missing Piece in LLM Safety

AI safety research has focused predominantly on epistemic and physical harms (e.g., misinformation, bias, system reliability) while the risks that arise from AI systems' engagement with human emotional life have remained fragmented and undertheorised. We propose affective safety as a unified class of AI safety concerns grounded in the fact that humans are affective beings. We develop a taxonomy of affective harms and identify recurring harm types: (1) affective self-alienation, (2) fairness and

Record details

Published: 22 June 2026
Source: arXiv
Category: Research
Topics: Bias & fairness · Safety & alignment · Misinformation
Retrieved: 14 July 2026

source-onlyevidence status

These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

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How to cite this record

ethics.ai (22 June 2026), “Affective AI Safety: The Missing Piece in LLM Safety,” evidence record 697, https://ethics.ai/record/697 (originally published by arXiv).

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