As Artificial Intelligence (AI) becomes more integrated into our daily lives, from recommending movies to assisting in medical diagnoses, we need to have a similar, yet much deeper, level of trust in these complex systems.
The Law of Yesterday for the AI of Tomorrow
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.
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.
OpenAI cut off FoloToy's API access after researchers at the Public Interest Research Group found the company's AI teddy bear teaching childre…
EDPB guidance demonstrates how structured privacy governance approaches for LLM systems create competitive advantages while ensuring regulatory compliance.
The NIST AI RMF shifts AI risk management from abstract principles to a structured, operational process...When AI is ubiquitous, trust matters. The RMF provides a tool for building that trust through continuous improvement.
The shift to widespread AI requires a shift in approach: from reactive problem-solving to intentional design... The organizations that get ahead of this will be the ones that can prove their AI systems work as intended—and can be trusted accordingly.