AI Ethics & Safety

Field notes on responsible AI — alignment, safety, governance, and the audit trails that prove a system can be trusted.

The ethics outpost tracks the rules — written and unwritten — that decide which AI systems get shipped, used, and trusted. We cover the work of practitioners aligning models, the policy teams translating EU AI Act obligations into checklists, the auditors mapping NIST AI RMF 1.0 and its Generative AI Profile to real controls, and the compliance leads chasing ISO/IEC 42001 certification before procurement starts asking for it.

The terrain shifts fast. Anthropic's Responsible Scaling Policy reached v3.0 in early 2026. OpenAI and Google DeepMind run parallel preparedness frameworks. Colorado's AI Act lands in June 2026; the EU AI Act's main obligations follow in August. Inside companies, boards are standing up Chief AI Officer roles and management-level governance committees while legal teams write down what their organizations already do.

Expect plain-language explainers, framework comparisons, post-incident write-ups, and meetup recaps from people doing the work — not abstract debate. If you build, deploy, audit, or govern AI systems, this is your map of the safety-and-rules landscape as it stands today.

Clusters

AI Ethics

Responsible AI in practice — fairness, accountability, transparency, and the trade-offs nobody warns you about.

AI Compliance

Audits, frameworks, and certifications — turning EU AI Act, NIST RMF, and ISO/IEC 42001 into operational controls.

AI Safety

Alignment, robustness, evals, and red-teaming — keeping models behaving as capabilities scale.

AI Governance

Policy, board oversight, and the cross-functional structures that turn AI principles into accountability.

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