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harm-anticipation

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Proactively identifying failure modes, misuse, and unintended consequences.

skills/ai-alignment-reasoning/harm-anticipation/SKILL.md

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# Harm Anticipation

Harm anticipation is systematically thinking through how an AI product could cause harm — before it does. Preventive design, not reactive crisis management.

The work is unglamorous and easy to skip. Done well, it produces specific testable mitigations. Done badly, it produces a doc nobody reads.

## Categories of AI harm

- **Direct harm**: the AI outputs something harmful — dangerous advice, discriminatory content, privacy violations
- **Facilitated harm**: the AI helps a user do something harmful, even if the AI's output itself is benign
- **Emergent harm**: harmful patterns from scale or interaction effects, not from any single output
- **Omission harm**: the AI fails to act when it should — not flagging a crisis, not escalating
- **Erosion harm**: gradual negative effects — dependency, deskilling, manipulation, trust erosion

## Structured anticipation
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