Microsoft and NYU tested what happens when AI becomes employee #1
The research shows we're moving from AI-as-tool to AI-as-colleague, which means rethinking how we structure accountability and human oversight.
Operationalizing NIST AI Risk Model Framework: Beyond Accuracy and Checklists
The NIST framework provides the map, but fostering a true culture of responsibility is the journey.
A three-tier risk model for Agents based on production status and reversibility
IBM's framework begins with a reversibility assessment that determines which of three automation tiers applies to a given task.
When insurers won't touch AI, you're self-insuring by default
The companies that insure oil rigs and rocket launches won't touch AI systems. They can't model the failure modes well enough to price the risk. For product teams, that means you're absorbing liability that traditional risk transfer won't cover.
Lie to me....
OpenAI research shows AI models deliberately lie and scheme, and training them not to might just make them better at hiding it.
California's DROP system: One button to rule them all
Are you building privacy controls that work at the scale California is designing for? Because "we'll handle deletion requests manually" doesn't survive a system designed to generate them by the millions.
Advancing U.S. Competitiveness in Agentic Gen AI: A Strategic Framework for Interoperability and Governance
The work proposes a five-layer architectural framework that embeds governance and security requirements throughout system design rather than treating them as separate concerns.
The Cracks in Our AI Safety Net
A new approach is needed, one that thinks in terms of dynamic spectrums rather than static boxes.
