Stanford

Research shows AI can accelerate education innovation by simulating interventions before human evaluation—potentially reducing timelines from decades to years.

The study identified three critical success factors: jurisdictional clarity, task centrality, and task homogeneity in organizational AI implementations.

LLMs show high consistency on neutral topics like Thanksgiving but become variable on controversial issues. Larger models outperform smaller ones in reliability.

While software security has reporting infrastructure and bug bounties, AI systems lack similar frameworks for third-party evaluation and protection

"Stanford's fellowship places tech experts in government roles. One fellow helped write AI laws, while others improved public services and training."

"ChatGPT-4 scored 92 in clinical reasoning vs physicians' 74-76. AI-assisted doctors completed diagnoses 1+ minute faster but showed no accuracy gains"