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Systematically anticipates harms in AI products by categorizing failure modes, misuse scenarios, unintended consequences, and creating risk matrices.
How this skill is triggered — by the user, by Claude, or both
Slash command
/ai-alignment-reasoning:harm-anticipationThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Harm anticipation is the practice of systematically thinking through how an AI product could cause harm — before it does. It's preventive design, not reactive crisis management.
Harm anticipation is the practice of systematically thinking through how an AI product could cause harm — before it does. It's preventive design, not reactive crisis management.
Work through each harm category systematically:
Think like an adversary:
Think about second-order effects:
npx claudepluginhub owl-listener/ai-design-skills --plugin ai-alignment-reasoningGuides structured identification of harms, benefits, and differential impacts across stakeholder groups for decisions affecting people. Covers stakeholder mapping, fairness evaluation, risk mitigation, and monitoring.
Conducts a structured ethical review of AI/ML features, models, or products covering fairness, transparency, privacy, safety, accountability, and societal impact with risk scoring and mitigations.
Conducts ethics reviews for AI and technology projects including ethical impact assessments, stakeholder analysis, and mitigation planning. Use for evaluating risks and harms.