Hoffman-Yee Symposium 2025
The 2025 Hoffman-Yee Grant Symposium will comprise of public talks from the six teams who are competing for funding, as well as showcase the work of the four 2024 winners of the Hoffman-Yee Research Grants. All teams will present their results to date and plans for the future.
The Hoffman-Yee Research Grant program is a multiyear initiative to invest in research that leverages artificial intelligence to address significant scientific and/or societal challenges aligned with Stanford HAI’s key areas of focus: understanding the human and societal impact of AI, augmenting human capabilities, and developing AI technologies inspired by human intelligence. We believe the results of these projects could play a significant role in defining future work in AI from academia to industry, government, healthcare and civil society.
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Ashesh Rambachan | From Next-Token Prediction to Automatic Induction of Automata
Sequence data is ubiquitous in economics — job histories in labor economics, diagnosis and treatment sequences in health economics, strategic interactions in game theory. Generative sequence models can learn to predict these sequences well, but their complexity makes it hard to extract interpretable economic insights from their predictions.
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Sequence data is ubiquitous in economics — job histories in labor economics, diagnosis and treatment sequences in health economics, strategic interactions in game theory. Generative sequence models can learn to predict these sequences well, but their complexity makes it hard to extract interpretable economic insights from their predictions.
Caroline Meinhardt, Thomas Mullaney, Juan N. Pava, and Diyi Yang | How Can AI Support Language Digitization and Digital Inclusion?
What does digital inclusion look like in the age of AI? Over 6,000 of the world’s 7,000-plus living languages remain digitally disadvantaged.
What does digital inclusion look like in the age of AI? Over 6,000 of the world’s 7,000-plus living languages remain digitally disadvantaged.
Matt Beane | Precision Proactivity: Measuring Cognitive Load in Real-World AI-Assisted Work
Systems like ChatGPT and Claude assist billions through proactive dialogue—offering unsolicited, task-relevant information. Drawing on Cognitive Load Theory, we study how cognitive load shapes performance in AI assisted knowledge work.
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Systems like ChatGPT and Claude assist billions through proactive dialogue—offering unsolicited, task-relevant information. Drawing on Cognitive Load Theory, we study how cognitive load shapes performance in AI assisted knowledge work.