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James Landay: Paving a Path for Human-Centered Computing
The Stanford HAI co-director has blazed a trail by keeping humans at the center of emerging technologies.
The Challenge of Aligning AI ChatBots
Ever-changing lexicons, multilingualism, and varying cultural value systems compromise accuracy of large language models...
How Culture Shapes What People Want from AI
Stanford researchers explore how to build culturally inclusive and equitable AI by offering initial empirical evidence...
AI’s Impact on Black Americans
A new white paper for the Congressional Black Caucus addresses risks and opportunities of AI for Black communities.
Pathways to Governing AI Technologies in Healthcare
Leading policymakers, academics, healthcare providers, AI developers, and patient advocates discuss the path forward for...
How Can We Better Regulate Health AI?
HAI Associate Director Curt Langlotz explains the current state of health regulation and where we need to move to...
Exploring the Complex Ethical Challenges of Data Annotation
A cross-disciplinary group of Stanford students examines the ethical challenges faced by data workers and the companies...
TextGrad: AutoGrad for Text
Scholars develop a new framework that optimizes compound AI systems by backpropagating large language model feedback.
Digital Advertisers Often Fund Misinformation Unwittingly
The bulk purchase of digital ads through automated placement platforms often matches legitimate ad buyers with websites...
AI can Outperform Humans in Writing Medical Summaries
A new study adapts large language models to summarize clinical documents, showing a promising path for AI to improve...
Digital Economy Lab Fellow Alex “Sandy” Pentland: Building a Better, Safer Digital Ecosystem
The MIT professor describes practical approaches to improving the internet.
How Bias Hides in ‘Kitchen Sink’ Approaches to Data
In risk modeling, AI researchers take a more-is-better approach to training data, but a new study argues that a less-is...