The case for rethinking when humans should review AI output Listen to this article: We tend to treat human oversight in AI adoption as the responsible choice. But as organizations increase their reliance on AI, the feasibility of that plan falters: if AI is deployed at scale, there will simply be too many touchpoints to […]

A new framework argues that AI evaluation should start where AI actually gets used. Listen to this article: Real-world AI use is messy. Uneven user expertise, shifting workflows, institutional dynamics, and a range of other factors all have an effect on what we get out of AI, but we also want to have a clear […]

A new framework for creating original ideas with AI Listen to this article: “Give me 20 headlines.” “Create 30 research questions.” “Generate 50 business ideas.” Beneath these requests lies an intuitive assumption about large language models: that originality emerges automatically from quantity. If an AI can generate ideas faster than humans, then perhaps creativity becomes […]