AI Safety is the field focused on ensuring AI systems behave reliably and don’t cause harm, even when they’re powerful, widely deployed, or operating in unexpected situations. It covers issues like preventing accidents (errors, brittleness), misuse (fraud, cyberattacks), and loss of human control (systems pursuing goals in unsafe ways). The aim is to build AI that is robust, secure, and aligned with human intentions and societal values.
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A new Stanford study reveals that AI therapy chatbots may not only lack effectiveness compared to human therapists but could also contribute to harmful stigma and dangerous responses.
A new Stanford study reveals that AI therapy chatbots may not only lack effectiveness compared to human therapists but could also contribute to harmful stigma and dangerous responses.


Stanford HAI joined global leaders to discuss the balance between AI innovation and safety and explore future policy paths.
Stanford HAI joined global leaders to discuss the balance between AI innovation and safety and explore future policy paths.


As AI technologies rapidly evolve, Professor Kochenderfer leads the charge in developing effective validation mechanisms to ensure safety in autonomous systems like vehicles and drones.
As AI technologies rapidly evolve, Professor Kochenderfer leads the charge in developing effective validation mechanisms to ensure safety in autonomous systems like vehicles and drones.
