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Shortcomings of Visualizations for Human-in-the-Loop Machine Learning
While visualizations can help developers better design, train, and understand their models, new research shows gaps...
Exploring New Horizons in Generative AI
The Stanford HAI fall conference brings together scholars across disciplines to explore AI’s impact on science,...
How to Promote Responsible Open Foundation Models
Experts from industry, academia, and government share lessons learned and outline a path forward at a Princeton-Stanford...
When AI Systems Systemically Fail
By studying the marketplace of commercial machine learning models, scholars characterize when individuals are...
Computational Agents Exhibit Believable Humanlike Behavior
Generative agents rely on a large language model to remember their interactions, build relationships, and plan...
Urgent Call for AI to “Do No Harm” in Biomedicine
Stanford researchers urge coordinated action by federal and state governments, academic institutions, and hospitals to...
Spellburst: A Large Language Model–Powered Interactive Canvas for Generative Artists
This new creativity support tool helps artists who work in code explore ideas using natural language and iterate with...
Stanford Ethicists Developing Guidelines for the Safe Inclusion of Pediatric Data in AI-Driven Medical Research
AI algorithms often are trained on adult data, which can skew results when evaluating children. A new perspective piece...
AI Shows Dermatology Educational Materials Often Lack Darker Skin Tones
Black and brown skin tones are underrepresented in books meant to teach doctors to recognize skin disease. The shortfall...
AI Researchers Tap into Medical Twitter To Create Powerful New Analysis Tool
Stanford researchers discover a rich new data source in the anonymized pathology images and online comments of thousands...
How Trustworthy Are Large Language Models Like GPT?
More people feel comfortable outsourcing important projects to AI; new research shows why we shouldn’t.
Stanford HAI Brings Congressional Staff to AI School
To effectively regulate AI, Congress must first understand it. The Stanford HAI boot camp helped staffers think...