Study: Soldiers Trust AI Targeting Less Than Humans — Until You Explain It
A 2,015-participant experiment with a replica Israeli military AI targeting system found algorithmic aversion, not automation bias — but adding explainability features erased that skepticism entirely.
Sycophancy, Overconfidence, and the AI Risk You Can't Fix With a Patch
Bruce Schneier and Nathan Sanders argue that many of AI's harms are business-model failures, not engineering ones — but the essay also flags two technical failure modes vendors keep ignoring, and those belong on every AI governance register.
DeepSeek Ships V4 Pro 0813 With No Announcement — What That Means for AI Governance
DeepSeek's newest reasoning model surfaced on OpenRouter with no model card, no vendor announcement, and benchmarks first seen in a leaked WeChat screenshot. For teams with an AI governance program, that's the real story.
Distillation, Fair Use, and the Open-Weight Model Land Grab
A Ben Thompson proposal to legalise AI distillation, surfaced by Simon Willison, lands the same week Alibaba and Moonshot pushed out trillion-parameter open-weight models — and raises real questions for anyone doing AI vendor due diligence.
MIT's 500-Camera AI Surveillance Buildout Is a Governance Test Case
A $3M rollout of AI-driven cameras across MIT's campus shows what happens when biometric analytics infrastructure scales faster than the governance built to control it.
Token Leaderboards and Blind Mandates: AI's Hidden Governance Risk
A widely shared consultant's account of executives mandating AI use they've never touched themselves is a governance failure, not just a culture problem — and it leaves real gaps for security teams to close.
AI-Built Dev Tools and the Verification Gap: A SQLite Case Study
Simon Willison had an AI model build an interactive SQLite query-plan explainer — then published it with an explicit admission he can't verify its output himself. That's a small, honest window into a governance problem security and engineering teams will keep running into.
Why Giving Users 'Control' Over Data Won't Fix AI-Era Privacy
Legal scholar Daniel Solove argues in the Wall Street Journal that consent-based privacy law has failed — and that AI makes the case for regulating companies directly, the way food and drug law does.
Thinking Machines' Inkling: Open Weights, Thin Data Provenance
Mira Murati's lab has open-sourced a 975-billion-parameter multimodal model under Apache 2.0 — but its training-data documentation gives security and governance teams little to work with.
Why an AI Agent Can Never Be Your DRI
Simon Willison's take on "Directly Responsible Individuals" is a reminder that accountability doesn't scale to agents — and that gap is now a governance problem, not a philosophical one.
Why Chatbot Sycophancy and AI's Flattened Speech Share a Root Cause
A Schneier and Palmer essay on how LLMs are reshaping human speech points to a training-data blind spot with a second, more consequential effect: chatbots that reflexively agree with users.
US Export Curbs on Claude Fable 5 and Mythos 5: A New AI Governance Risk
Washington ordered Anthropic to cut off foreign access to two frontier models, then reversed course days later under new security conditions — a preview of how export control is becoming an AI governance variable.