#ai-safety
6 articles
The Reasoning Transcript Is a User Interface, Not an X-Ray
Reasoning models can produce persuasive accounts of how they reached an answer. Treating those accounts as faithful evidence of internal computation is a category error with consequences for evaluation, debugging, and safety.
Voluntary Safety Commitments Are Turning Into a De Facto Regulatory Floor
Frontier labs signed a round of voluntary safety commitments with little enforcement mechanism behind them. Government AI safety institutes have since started treating those same commitments as the baseline they evaluate against, which is quietly giving them the force regulation usually takes years to acquire.
Copyright Lawsuits Are Quietly Rewriting AI Product Roadmaps
The training-data lawsuits against AI companies are still working through courts, but their outcome is already visible in product decisions: licensing deals, opt-out tooling, and provenance features that did not exist two years ago and now ship as standard.
The EU AI Act's Real Deadline Is the One Builders Keep Missing
Most coverage of the EU AI Act focused on the ban on the worst use cases, which took effect first and affected almost nobody building ordinary products. The obligations that actually touch mainstream AI development are arriving in phases most teams have not scheduled for.
A Human in the Loop Is Not a Control System
Human review is often added to AI products as a reassuring label, even when reviewers lack time, context, or authority. Real oversight must be engineered as an operating system for exceptions, not assigned as ceremonial responsibility.
The Hard Part of Agentic AI Is Measurement, Not Reasoning
The industry still talks as if smarter models automatically become better agents. The harder truth is that once models can act, the bottleneck shifts to observing, scoring, and constraining behavior in the messy conditions where real work happens.