Design AI ethics frameworks with principles, review processes, and governance. TRIGGERS - Use when user needs help with ai-ethics-framework related tasks.
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Design AI ethics frameworks with principles, review processes, and governance. TRIGGERS - Use when user needs help with ai-ethics-framework related tasks.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Establish AI ethics committees. TRIGGERS - Use when user needs help with ai-ethics-committee related tasks.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Establish AI ethics committees. TRIGGERS - Use when user needs help with ai-ethics-committee related tasks.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Design AI ethics frameworks with principles, review processes, and governance. TRIGGERS - Use when user needs help with ai-ethics-framework related tasks.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Write an AI usage policy people can actually follow — approved tools, data rules, disclosure duties, and review obligations, in one page instead of legal fog. Use when asked for a company AI policy, acceptable-use rules for ChatGPT/Claude/Copilot at work, guidance on what data may go into AI tools, or to fix a policy nobody reads. Produces a one-page usable policy plus the decision log behind it. Not a substitute for legal advice; pairs with compliance-checklist for regulatory mapping and ai-ethics-review for system-level assessments.
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Conduct a structured ethical review of an AI or ML feature, model, or product. Use when preparing to deploy an AI system, assessing algorithmic risk, auditing a model for bias, or producing a responsible AI impact assessment. Produces a structured ethics review covering fairness, transparency, privacy, safety, accountability, and societal impact with a risk tier score, pre-deployment checklist, and prioritised mitigations.
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Responsible AI development and ethical considerations. Use when evaluating AI bias, implementing fairness measures, conducting ethical assessments, or ensuring AI systems align with human values.
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"Apply AI ethics frameworks (fairness, accountability, transparency, privacy) to evaluate AI systems for algorithmic bias, explainability gaps, and value alignment failures. Use this skill when the user needs to audit an AI system for ethical risks, design fairness constraints, assess explainability requirements, or when they ask 'is this AI system fair', 'how do we detect algorithmic bias', 'what are the ethical implications of this AI deployment', or 'how do we make this model explainable to stakeholders'.".
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Use when designing or reasoning about an Agentforce Grid worksheet — the spreadsheet-like Agentforce workspace where rows are jobs and columns are sequential Data / AI / Action steps that process left to right — to run bulk record updates, generate insights, or test multi-turn AI conversations over CRM or Data Cloud (Data 360) data without Apex or Flow. Trigger keywords: Agentforce Grid, workbook, worksheet, grid column, data column, AI column, action column, bulk AI update, Flex Credits per row, metered compute. NOT for building the agent, its topics, or its actions themselves (use agentforce/* action and topic skills), NOT for single-record prompt design (use the prompt-builder skills), NOT for deployable metadata/Apex (Grid is a no-code Studio tool, not a metadata type), and NOT for AI governance/ethics policy (use admin/ai-ethics-and-governance-requirements).
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Use this skill when defining AI governance policies, designing human oversight workflows, documenting bias mitigation strategies, or meeting regulatory transparency requirements for Salesforce AI features. Trigger keywords: responsible AI, AI bias, AI audit trail, AI transparency, human-in-the-loop, AI risk inventory, AI disclosure. NOT for the MLOps pipeline or Policy-as-Code engine architecture — use architect/ai-governance-architecture. NOT for Trust Layer technical configuration — use agentforce/einstein-trust-layer.
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Expert en éthique de l'IA (bias detection, fairness, explainability, responsible AI, guardrails)
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Expert en éthique des agents IA (tests de biais, équité, transparence, explicabilité, déploiement responsable)
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Regulatory review across 14 frameworks — compliance review, privacy impact assessment, regulatory gap analysis, data subject rights, consent mechanisms, audit trail, AI ethics review, data flow mapping. Covers GDPR, PIPEDA, HIPAA, PCI-DSS, SOC2, UAE-PDPL, EU AI Act and more.
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