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
HAI Weekly Seminar with Garance Burke - Steering Journalism Towards Data Science
HAI Weekly Seminar with Garance Burke - Steering Journalism Towards Data Science
HAI Weekly Seminar with Lucy Suchman - Demystifying AI as an Ethical Project
This talk develops the proposal that a central – and neglected – ethical challenge for the field of AI is demystification of the techniques and technologies that constitute it
This talk develops the proposal that a central – and neglected – ethical challenge for the field of AI is demystification of the techniques and technologies that constitute it
HAI Monthly Community Building Reception - A Conversation about AI Governance
Join California Supreme Court Justice Cuéllar, who teaches the popular “Regulating AI” course at Stanford, Dan Ho, Associate Director of HAI and professor at the law school and political science, and Terah Lyons, the Founding Executive Director of the Partnership on AI, for a conversation on the law, regulation, and governance of AI! The three will provide a range of perspectives on the promise, challenges, and directions for AI governance.
HAI Monthly Community Building Reception - A Conversation about AI Governance
Join California Supreme Court Justice Cuéllar, who teaches the popular “Regulating AI” course at Stanford, Dan Ho, Associate Director of HAI and professor at the law school and political science, and Terah Lyons, the Founding Executive Director of the Partnership on AI, for a conversation on the law, regulation, and governance of AI! The three will provide a range of perspectives on the promise, challenges, and directions for AI governance.
AI for Good Seminar Series: AI for Healthcare
AI for Healthcare session will feature Marzyeh Ghassemi who targets “Healthy ML” focusing on creating and applying machine learning to understand and improve health. Improving health requires targeting and evidence. Marzyeh tackles part of this puzzle with machine learning. This session will cover some of the novel technical opportunities for machine learning in health challenges and the important progress to be made with a careful application to domain. She will also walk through the danger of applying methods without a robust understanding of the domain, and potential downstream uses.
AI for Good Seminar Series: AI for Healthcare
AI for Healthcare session will feature Marzyeh Ghassemi who targets “Healthy ML” focusing on creating and applying machine learning to understand and improve health. Improving health requires targeting and evidence. Marzyeh tackles part of this puzzle with machine learning. This session will cover some of the novel technical opportunities for machine learning in health challenges and the important progress to be made with a careful application to domain. She will also walk through the danger of applying methods without a robust understanding of the domain, and potential downstream uses.
HAI Weekly Seminar with Bongjun Ko - The Value of Data: An Engineer’s Perspective
Recent advances of artificial intelligence and deep learning have been undoubtedly driven by a large amount of data amassed over the years, helping firms, researchers, and practitioners achieve many amazing feats, most notably in recognition tasks often surpassing human ability in several benchmarks.
HAI Weekly Seminar with Bongjun Ko - The Value of Data: An Engineer’s Perspective
Recent advances of artificial intelligence and deep learning have been undoubtedly driven by a large amount of data amassed over the years, helping firms, researchers, and practitioners achieve many amazing feats, most notably in recognition tasks often surpassing human ability in several benchmarks.
Psychology-Neuroscience-Artificial Intelligence, Part 1
Psychology-Neuroscience-Artificial Intelligence, Part 1
AI for Good Seminar Series: AI for Government
AI promises to transform how government agencies work. Where will it have the biggest impact? What are some challenges around transparency, privacy, bias, and accountability? This talk will go beyond the headlines and share highlights of a just-completed report on AI in the US Government.
AI for Good Seminar Series: AI for Government
AI promises to transform how government agencies work. Where will it have the biggest impact? What are some challenges around transparency, privacy, bias, and accountability? This talk will go beyond the headlines and share highlights of a just-completed report on AI in the US Government.
AI for Good Seminar Series: AI for Earth and the Environment
How can AI and machine learning be leveraged to mitigate the impact of human activities on earth’s natural systems? Learn about data science tools and strategies being used to safeguard our water supply, feed the worldwide human population, and promote greater biodiversity and global sustainability.
AI for Good Seminar Series: AI for Earth and the Environment
How can AI and machine learning be leveraged to mitigate the impact of human activities on earth’s natural systems? Learn about data science tools and strategies being used to safeguard our water supply, feed the worldwide human population, and promote greater biodiversity and global sustainability.
Race and Digital Civil Society Lightning Talks & Lunch
Bias in government automated decision systems, the future of farmwork, digital literacy, algorithms in bail decisions, and more.
Race and Digital Civil Society Lightning Talks & Lunch
Bias in government automated decision systems, the future of farmwork, digital literacy, algorithms in bail decisions, and more.
HAI Weekly Seminar with Johannes Eichstaedt - Measuring Physical and Mental Health Using Social Media
The content shared on social media is among the largest data sets on human behavior in history. I leverage this data to address questions in the psychological sciences. Specifically, I apply natural language processing and machine learning to characterize and measure psychological phenomena with a focus on mental and physical health.
HAI Weekly Seminar with Johannes Eichstaedt - Measuring Physical and Mental Health Using Social Media
The content shared on social media is among the largest data sets on human behavior in history. I leverage this data to address questions in the psychological sciences. Specifically, I apply natural language processing and machine learning to characterize and measure psychological phenomena with a focus on mental and physical health.