Analysis finds history textbooks misrepresent the scientific consensus around climate change
A new AI-driven analysis finds the most popular U.S. history textbooks used in California and Texas commonly misrepresent the scientific consensus around climate change.
There’s a problem with making technology genderless
There’s a push to make tech genderless to avoid perpetuating stereotypes, but research shows gender is one of the fundamental ways we connect with objects.
A generative search engine is supposed to respond to queries using content extracted from top web search hits, but there’s no easy way to know when it’s just making things up.
Why GPT detectors aren’t a solution to the AI cheating problem
At least seven algorithms promise to expose AI-written prose, but there’s one problem: They’re especially unreliable when the author is not a native English speaker.
A new machine learning model predicts rare diseases
A new model combs a wealth of patient data from demographic information to lab test results to better predict the probability of diseases for which data are sparse.
Stanford Institute for Human-Centered AI and Wu Tsai Neurosciences Institute grants support research teams spanning all seven of Stanford’s schools, on themes ranging from healthcare to robotics.
Here’s how we can design ethical self-driving cars
Chris Gerdes, co-director of the Center for Automotive Research at Stanford, discusses the ethical dilemmas and exceptional driving situations that AV designers must take into account.
Stanford Institute for Human-Centered Artificial Intelligence —
Quantifying therapists’ language to improve patient outcomes
A new set of open-source tools analyze the timing, responsiveness, and consistency of the language therapists use to better understand what works for patients.
Stanford Institute for Human-Centered Artificial Intelligence —
HAI on the biggest headlines of 2022
Generative models like ChatGPT and DALL-E 2 made news this year, as did discussions about sentient AI, tools for evaluating large language models, policy recommendations, and more.
This year’s biggest headline might have been generative AI, but what should we expect from the field in 2023? Four Stanford HAI faculty predict the biggest advances, opportunities, and challenges for the coming year.
