Upcoming Events
Center for Decoding the Universe Fall Forum
Please note that this event is open to Stanford affiliates only.
Center for Decoding the Universe Fall Forum
Please note that this event is open to Stanford affiliates only.
Daniel Wurgaft | A Resource Rational Analysis of Representations: Geometry, Inference, Capacity
A Center for Neural Data Science Seminar Series
Daniel Wurgaft | A Resource Rational Analysis of Representations: Geometry, Inference, Capacity
A Center for Neural Data Science Seminar Series
HAI & AI Governance Lab | A Conversation with Jacob Coxon & Rob Reich
This in-person event is open to current Stanford faculty, students, and staff. ID will be required at check in. Other guests are invited to join the webinar.
HAI & AI Governance Lab | A Conversation with Jacob Coxon & Rob Reich
This in-person event is open to current Stanford faculty, students, and staff. ID will be required at check in. Other guests are invited to join the webinar.
Marlowe | AI + Data for Science with Alex Pentland
Sessions run Wednesdays from 4:30–5:30 PM in CoDa E160. Each session features a different Stanford speaker; talk titles are announced by the organizers.
Marlowe | AI + Data for Science with Alex Pentland
Sessions run Wednesdays from 4:30–5:30 PM in CoDa E160. Each session features a different Stanford speaker; talk titles are announced by the organizers.
Khaoula Chehbouni | Best Practices for the Use of LLMs as Judges
An AI Measurement Science (AIMS) Seminar Series
Khaoula Chehbouni | Best Practices for the Use of LLMs as Judges
An AI Measurement Science (AIMS) Seminar Series
Special Seminar and Fireside Chat: Understanding Work Using AI
Phil Lewis from the National Center for O*NET Development will talk about data infrastructure the US Department of Labor provides, and how AI is used to update it. A panel with Diyi Yang from the Stanford Computer Science Department and DEL’s Erik Brynjolfsson will discuss the opportunities of a new partnership between Stanford and the National Center for O*NET Development.
Special Seminar and Fireside Chat: Understanding Work Using AI
Phil Lewis from the National Center for O*NET Development will talk about data infrastructure the US Department of Labor provides, and how AI is used to update it. A panel with Diyi Yang from the Stanford Computer Science Department and DEL’s Erik Brynjolfsson will discuss the opportunities of a new partnership between Stanford and the National Center for O*NET Development.
Christopher Ong | Research Acceleration: The View Inside OpenAI
In the last year, AI models have rapidly improved on public benchmarks measuring their ability to carry out research tasks autonomously. Such performance suggests that models may be capable of automating parts of the AI R&D process itself, thereby accelerating the pace of AI progress.
Christopher Ong | Research Acceleration: The View Inside OpenAI
In the last year, AI models have rapidly improved on public benchmarks measuring their ability to carry out research tasks autonomously. Such performance suggests that models may be capable of automating parts of the AI R&D process itself, thereby accelerating the pace of AI progress.
AI100 | AI Goes Mainstream: The Scaling Era and the Rise of Generative AI
This talk will cover key insights from the third AI100 report, AI Goes Mainstream: The Scaling Era and the Rise of Generative AI, set for release in November 2026. The report was commissioned by the AI100 standing committee and led by study panel chair Michael Wooldridge.
AI100 | AI Goes Mainstream: The Scaling Era and the Rise of Generative AI
This talk will cover key insights from the third AI100 report, AI Goes Mainstream: The Scaling Era and the Rise of Generative AI, set for release in November 2026. The report was commissioned by the AI100 standing committee and led by study panel chair Michael Wooldridge.
Marlowe | AI + Data for Science with Andreas Tolias
Sessions run Wednesdays from 4:30–5:30 PM in CoDa E160. Each session features a different Stanford speaker; talk titles are announced by the organizers.
Marlowe | AI + Data for Science with Andreas Tolias
Sessions run Wednesdays from 4:30–5:30 PM in CoDa E160. Each session features a different Stanford speaker; talk titles are announced by the organizers.
Marlowe | AI + Data for Science with Leonidas Guibas
Sessions run Wednesdays from 4:30–5:30 PM in CoDa E160. Each session features a different Stanford speaker; talk titles are announced by the organizers.
Marlowe | AI + Data for Science with Leonidas Guibas
Sessions run Wednesdays from 4:30–5:30 PM in CoDa E160. Each session features a different Stanford speaker; talk titles are announced by the organizers.
Angèle Christin & Hannah Zeavin | Gurus, Hucksters, Entertainers: How Influencers Reshaped Social Media
Please join us for an illuminating investigation of the complex work of social media content creators—their lives, conflicts, and controversies.
Angèle Christin & Hannah Zeavin | Gurus, Hucksters, Entertainers: How Influencers Reshaped Social Media
Please join us for an illuminating investigation of the complex work of social media content creators—their lives, conflicts, and controversies.
YoungJu Jo | Data-driven Discovery and Control of Neural Computations
A Center for Neural Data Science Seminar Series
YoungJu Jo | Data-driven Discovery and Control of Neural Computations
A Center for Neural Data Science Seminar Series
2027 Conference on Physics and AI (PhyStat 2027)
The Center for Decoding the Universe brings together researchers across scientific disciplines to answer the biggest questions about our Universe by leveraging complex data with the most advanced statistical and computational methods.
2027 Conference on Physics and AI (PhyStat 2027)
The Center for Decoding the Universe brings together researchers across scientific disciplines to answer the biggest questions about our Universe by leveraging complex data with the most advanced statistical and computational methods.
Featured Videos
Hear from speakers and attendees at recent Stanford HAI events across research, policy, and education.
Previous Events at HAI
New Horizons in Generative AI: Science, Creativity, and Society
New Horizons in Generative AI: Science, Creativity, and Society
Ram Shankar Siva Kumar | A Few Useful Lessons about AI Red Teaming
AI red teaming is exploding in popularity: At DEF CON this year, more than 2,500 hackers descended to red-team AI systems. Every organization investing in AI—from Microsoft to Google to Meta to NVIDIA—has AI red teams to actively secure their AI systems
Ram Shankar Siva Kumar | A Few Useful Lessons about AI Red Teaming
AI red teaming is exploding in popularity: At DEF CON this year, more than 2,500 hackers descended to red-team AI systems. Every organization investing in AI—from Microsoft to Google to Meta to NVIDIA—has AI red teams to actively secure their AI systems
Nick Haber | Motivation, Representation, and Autonomous Agents
The past decade’s series of dramatic AI successes has brought us closer to realizing the dream of the autonomous agent—an artificial system that can learn about its world, make decisions, and set and achieve goals, all with minimal human intervention.
Nick Haber | Motivation, Representation, and Autonomous Agents
The past decade’s series of dramatic AI successes has brought us closer to realizing the dream of the autonomous agent—an artificial system that can learn about its world, make decisions, and set and achieve goals, all with minimal human intervention.
HAI Orientation: Cultivating Collaborative Communities
Friends of the Stanford Institute for Human-Centered AI (HAI): We invite you to the second Stanford HAI Orientation to learn more about our work, meet faculty and peers, and find out more about the ways in which you can get involved. All Stanford students, faculty and staff are welcome to attend.
HAI Orientation: Cultivating Collaborative Communities
Friends of the Stanford Institute for Human-Centered AI (HAI): We invite you to the second Stanford HAI Orientation to learn more about our work, meet faculty and peers, and find out more about the ways in which you can get involved. All Stanford students, faculty and staff are welcome to attend.
Simulcast: Geoffrey Hinton in Conversation with Fei-Fei Li
In this Radical AI Founders Masterclass, Geoffrey Hinton and Fei-Fei Li will share their experiences building tech-first startups and scaleups, offering up their guidance, advice, and personal viewpoints.
Simulcast: Geoffrey Hinton in Conversation with Fei-Fei Li
In this Radical AI Founders Masterclass, Geoffrey Hinton and Fei-Fei Li will share their experiences building tech-first startups and scaleups, offering up their guidance, advice, and personal viewpoints.
HAI Vodcast with Ge Wang and Vanessa Parli | Episode 1: What Do We (Really) Want from AI?
Workshop on Responsible and Open Foundation Models
In the last year, open foundation models have proliferated widely. Given the rapid adoption of these models, cultivating a responsible open source AI ecosystem is crucial and urgent. Our workshop presents an opportunity to learn from experts in different fields who have worked on responsible release strategies, risk mitigation, and policy interventions that can help.
Workshop on Responsible and Open Foundation Models
In the last year, open foundation models have proliferated widely. Given the rapid adoption of these models, cultivating a responsible open source AI ecosystem is crucial and urgent. Our workshop presents an opportunity to learn from experts in different fields who have worked on responsible release strategies, risk mitigation, and policy interventions that can help.
Decoding the EU Artificial Intelligence Act
The European Parliament recently voted to pass its position on the EU AI Act, the world’s first comprehensive AI regulation.
Decoding the EU Artificial Intelligence Act
The European Parliament recently voted to pass its position on the EU AI Act, the world’s first comprehensive AI regulation.
Advancing AI Audit - Project Showcase and Lessons Learned
How can we effectively design and develop practical tools to assess the presence of bias and potential discrimination in AI systems?
Advancing AI Audit - Project Showcase and Lessons Learned
How can we effectively design and develop practical tools to assess the presence of bias and potential discrimination in AI systems?