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.
The NIST framework provides the map, but fostering a true culture of responsibility is the journey.
IBM's framework begins with a reversibility assessment that determines which of three automation tiers applies to a given task.
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.
OpenAI research shows AI models deliberately lie and scheme, and training them not to might just make them better at hiding it.
The work proposes a five-layer architectural framework that embeds governance and security requirements throughout system design rather than treating them as separate concerns.
A new approach is needed, one that thinks in terms of dynamic spectrums rather than static boxes.
The Census data suggests companies are shifting from FOMO-driven AI adoption to more evidence-based decisions about what actually works.
Japan enacted its AI Promotion Act with no penalties and no strict compliance—just a request that companies "endeavor to cooperate" and the threat of public shaming. It's a deliberate bet on regulatory minimalism to boost lagging AI investment.