リポジトリ全体を IEEE-CS/ACM ソフトウェア工学倫理綱領(8原則・80項目)とダークパターン 観点で監査し、証跡付きで採点(合格/要改善/不適合)する。多エージェント敵対的監査により 誤検知(ethical grandstanding)を検証で潰す。結果は自己監査のツイート下書きにできる。 トリガー: 倫理監査, 技術者倫理チェック, ethics audit, 倫理チェック, /ethics-audit
「ethics」の検索結果
93 件 ・ 関連度順
概要と使いどころ
Use when handling research ethics, consent, community accountability, and data/transparency for an American Anthropologist (AA) manuscript — informed consent, anonymization, protection of vulnerable interlocutors, heritage and repatriation obligations, and what (and what NOT) to share. At AA this is an ethics-and-accountability skill grounded in the AAA ethics principles and an ethics of care. Plans the ethics and transparency; it does not grant waivers.
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Steward public stories about any work — creation ethics, application ethics, and maintenance of the story plus its disclosures (generated, drafted, curated, authored). Use when writing a public article, origin story, talk, README narrative, or showcase about how work was made; when publishing ethics and decisions; or when asked who generated vs curated a text. Do not use for ADRs, FAQs, skill citations, or marketing hype.
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無料Research Guardian - Ethics Advisory & Bias Detection across all research stages Enhanced VS 3-Phase process: Surface-level screening, deep contextual analysis, constructive recommendations Use when: reviewing research ethics, checking for bias, assessing trustworthiness, QRP screening Triggers: ethics review, IRB, bias detection, QRP, trustworthiness, research integrity, p-hacking, HARKing
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Engineering ethics covering safety, professional codes of conduct, public welfare responsibility, whistleblowing, case studies (Challenger, Columbia, Hyatt Regency, Bhopal, Therac-25), and the ethical dimensions of design decisions. Includes the NSPE Code of Ethics, the iron ring tradition, risk communication, informed consent in engineering, and the duty to dissent. Use when analyzing ethical dimensions of engineering decisions, teaching professional responsibility, or reviewing designs for safety and public welfare.
日本語の概要は準備中です。原文の説明を表示しています。
Establish AI ethics committees. TRIGGERS - Use when user needs help with ai-ethics-committee related tasks.
日本語の概要は準備中です。原文の説明を表示しています。
Design AI ethics frameworks with principles, review processes, and governance. TRIGGERS - Use when user needs help with ai-ethics-framework related tasks.
日本語の概要は準備中です。原文の説明を表示しています。
Comprehensive ethics expert covering virtue ethics, deontology, consequentialism, and applied ethical dilemmas
日本語の概要は準備中です。原文の説明を表示しています。
Foundational ethics, authority hierarchy, and structural principles for the Predicate agent. Always-on law (composable system-prompt core): Truth>Harmony, Evidence>Authority, Halt>Assumption, Outcomes>Process — four ordered principles that govern every walk. Reference (by-moment): conflict resolution, ethics adjudication, novel situations, precedence walkthrough, entropy diagnostics, principled resistance. Trigger (reference depth): resolving rule conflicts, ethics calls, novel situations. Prompt contains: constitution, principles, precedence, truth over harmony, outcomes over process, evidence over authority, principled resistance.
日本語の概要は準備中です。原文の説明を表示しています。
Establish AI ethics committees. TRIGGERS - Use when user needs help with ai-ethics-committee related tasks.
日本語の概要は準備中です。原文の説明を表示しています。
Design AI ethics frameworks with principles, review processes, and governance. TRIGGERS - Use when user needs help with ai-ethics-framework related tasks.
日本語の概要は準備中です。原文の説明を表示しています。
Guardian Angel gives AI agents a moral conscience rooted in Thomistic virtue ethics. Rather than relying solely on rule lists, it cultivates stable virtuous dispositions— prudence, justice, fortitude, temperance—that guide every interaction. The foundation is caritas: willing the good of the person you serve. From this flow the cardinal virtues as practical habits of right action and sound judgment. v3.0 introduced virtue-based disposition as the primary evaluation layer, providing deeper coherence than checklists alone. The agent's character becomes the safeguard. v3.1 adds: Plugin enforcement layer with before_tool_call hooks, approval workflows for ambiguous cases, and protections for sensitive infrastructure actions.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
How humans and AI compose in content workflows. Where AI legitimately participates, where humans must own, hybrid workflow patterns, voice ownership preservation, the AI slop problem, disclosure and transparency, team calibration, and the ethics of intellectually honest AI-assisted content production. Triggers on AI content workflow, AI-assisted writing, hybrid content production, AI in editorial, AI slop, AI disclosure, AI usage policy, AI content ethics, voice preservation with AI, team AI calibration. Also triggers when content feels generic despite quality tools, when team AI usage has drifted into inconsistency, or when a regulated or trust-sensitive context requires explicit AI policy.
日本語の概要は準備中です。原文の説明を表示しています。
Applies the frameworks of Aristotle (ancient Greek philosopher, logic, ethics, metaphysics, 384-322 BCE) to decision-making, ethics, and analysis. Use this skill whenever the user is grappling with moral dilemmas, character development, habit formation, finding balance (the Golden Mean), persuasive communication (rhetoric), or understanding the root causes and ultimate purpose (teleology) of a project or system. Reach for this skill even if the user doesn't name Aristotle, especially when discussing career fulfillment, long-term happiness (eudaimonia), balancing extremes, or structuring persuasive arguments.
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Use this skill whenever you are reasoning about large-scale scientific projects, genomics, bioethics, data infrastructure, or long-term medical translation. Eric S. Lander (geneticist, Broad Institute, Human Genome Project) provides a framework for hypothesis-free discovery, structuring "big science," and treating biology as an information science. Reach for this when the user is discussing open science, collaborative ecosystems, CRISPR/gene editing ethics, managing massive datasets, or setting realistic timelines for technological breakthroughs. Apply his principles to avoid the "lone genius" myth, prevent overpromising, and build foundational infrastructure that serves the broader community.
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Business ethics, corporate governance, and stakeholder responsibility for firms operating in complex social and regulatory environments. Covers ethical frameworks applied to business, stakeholder vs shareholder theory, board structure and fiduciary duty, conflicts of interest, whistleblowing, CSR and ESG, and the distinction between legal compliance and ethical conduct. Use when evaluating a decision with ethical stakes, designing a governance structure, or diagnosing a corporate scandal.
日本語の概要は準備中です。原文の説明を表示しています。
Bias detection and mitigation, fairness metrics, privacy frameworks, consent models, transparency requirements, and accountability structures for data science practice. Covers algorithmic bias sources, disparate impact testing, differential privacy, GDPR principles, model cards, datasheets for datasets, responsible AI frameworks, and the organizational governance needed to make ethics actionable. Use when auditing models for bias, designing privacy-preserving systems, establishing governance processes, or evaluating the social impact of data-driven decisions.
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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).
日本語の概要は準備中です。原文の説明を表示しています。
Handle ethical requirements, IRB approval, trial registration, and pre-analysis plans for RCTs. Use when user mentions: research ethics, IRB, informed consent, trial registration, pre-analysis plan, PAP, data security, vulnerable populations, research transparency.
日本語の概要は準備中です。原文の説明を表示しています。
Expert en éthique de l'IA (bias detection, fairness, explainability, responsible AI, guardrails)
日本語の概要は準備中です。原文の説明を表示しています。
Expert en éthique des agents IA (tests de biais, équité, transparence, explicabilité, déploiement responsable)
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ソフトウェア・エンジニアリングのための倫理集。開発時に必ず意識するものです。