Blog
In-depth analysis of AI safety research, policy, and industry developments.
Why AI Incident Tracking Matters
AI safety work needs a public memory: incidents, failure modes, and the operational lessons they reveal.
A Practical Preview Of Model Safety Scores
A first-pass scoring model can help readers compare hallucination, jailbreak, bias, and context stability risks.
Prompt Injection Is An AI Security Incident Class
Prompt injection is not just a jailbreak trick; it is a repeatable security failure mode for AI systems that read untrusted content.
How To Read AI Model Safety Scorecards
A practical guide to reading model cards, system cards, benchmarks, and safety score previews without mistaking them for safety certificates.
Bias Auditing Checklist For AI Hiring Tools
A practical checklist for reviewing AI hiring systems before historical bias becomes automated screening at scale.
Autonomous Vehicle AI Safety Case Review Template
A vehicle-centered checklist for reviewing autonomous driving safety evidence before perception, fallback, oversight, and crash-response gaps become safety failures.
How to Read an AI Model Card: A Practical Guide for Engineers and Auditors
Model cards are supposed to make AI transparent. Most don't. Here's how to read them so you actually learn what the model can and cannot do.
AI Red Teaming: A Practical Guide for Teams Without a Budget
Red teaming doesn't require a dedicated team. It requires structured thinking, repeatable tests, and the willingness to break your own assumptions.
AI Governance Checklist for Enterprise Deployment
Deploying AI in a regulated environment requires more than a model card. This checklist covers the governance, risk, and compliance layers most teams miss.
AI Transparency in 2026: What Companies Actually Disclose and What They Hide
Transparency reports are now standard for major AI labs. But the gap between what is disclosed and what users need is still wide. Here's what to look for.
Jailbreak Defense Strategies That Actually Work in 2026
Jailbreaks are getting more sophisticated. The defenses that worked in 2024 are losing ground. Here are the techniques that are holding up against current frontier models.
AI Safety Metrics That Actually Matter — And How to Measure Them
Most AI safety metrics are either too vague or too narrow. This guide defines the metrics that should be on every AI safety team's dashboard.
The Misalignment Weekly
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