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 Monthly Community Building Reception - Compassionate intelligence: Can machine learning bring more humanity to health care?
We will describe the Stanford Medicine Program for AI in Healthcare, which aims to bring AI into clinical use, safely and ethically. The session will begin with an overview of the effort and then focus on describing a project to improve palliative care using machine learning. We will summarize the creation and validation of a mortality prediction model, describe the associated care planning workflow it triggers and the work constraints it needs to function under. We will present preliminary results on an HAI supported project for understanding and addressing ethical challenges with implementation of machine learning to advance palliative care. Using this real-life example, we will elucidate several of the ethical challenges that need to be studied and addressed when combining artificial intelligence technologies with medical expertise to help doctors make faster, more informed and humane decisions.
HAI Monthly Community Building Reception - Compassionate intelligence: Can machine learning bring more humanity to health care?
We will describe the Stanford Medicine Program for AI in Healthcare, which aims to bring AI into clinical use, safely and ethically. The session will begin with an overview of the effort and then focus on describing a project to improve palliative care using machine learning. We will summarize the creation and validation of a mortality prediction model, describe the associated care planning workflow it triggers and the work constraints it needs to function under. We will present preliminary results on an HAI supported project for understanding and addressing ethical challenges with implementation of machine learning to advance palliative care. Using this real-life example, we will elucidate several of the ethical challenges that need to be studied and addressed when combining artificial intelligence technologies with medical expertise to help doctors make faster, more informed and humane decisions.
HAI Weekly Seminar with Pamela Chen
In this talk, Pamela Chen, 2020 Human-Centered AI and JSK Journalism Fellow at Stanford, shares her experiences leading an editorial team at Instagram as the company scaled content discovery to serve more than 1 billion monthly active users. Spoiler alert: it doesn’t go as planned.
HAI Weekly Seminar with Pamela Chen
In this talk, Pamela Chen, 2020 Human-Centered AI and JSK Journalism Fellow at Stanford, shares her experiences leading an editorial team at Instagram as the company scaled content discovery to serve more than 1 billion monthly active users. Spoiler alert: it doesn’t go as planned.
Artificial Intelligence in Healthcare: The Hope, The Hype, The Promise, The Peril
This conference is anchored and building on the release of the Special National Academy of Medicine (NAM) publication titled: “Artificial Intelligence in Healthcare: The Hope, The Hype, The Promise, The Peril.” Co-led by Michael Matheny and Sonoo Thadaney Israni.
Objectives At the conclusion of this activity, participants should be able to:Evaluate AI in the healthcare landscape
Critically assess the opportunities for AI in healthcare
Develop appropriate criteria for evaluating/deploying AI solutions
Build frameworks for creating and testing AI healthcare solutions
Artificial Intelligence in Healthcare: The Hope, The Hype, The Promise, The Peril
This conference is anchored and building on the release of the Special National Academy of Medicine (NAM) publication titled: “Artificial Intelligence in Healthcare: The Hope, The Hype, The Promise, The Peril.” Co-led by Michael Matheny and Sonoo Thadaney Israni.
Objectives At the conclusion of this activity, participants should be able to:Evaluate AI in the healthcare landscape
Critically assess the opportunities for AI in healthcare
Develop appropriate criteria for evaluating/deploying AI solutions
Build frameworks for creating and testing AI healthcare solutions
Human-Centered Artificial Intelligence: Trusted, Reliable and Safe
The next generation of user experiences will produce 1000-fold improvements in human capabilities. This new tools will amplify, augment, enhance, and empower people, just as the Web, email, search, navigation, digital photography, and many other applications have already done. Rather than emphasize autonomous machines and humanoid robots as team partners, these new tools will produce comprehensible, predictable, and controllable applications that promote self-efficacy, human responsibility, and social participation at scale. The goal is to ensure human control, while increasing the level of automation.
Human-Centered Artificial Intelligence: Trusted, Reliable and Safe
The next generation of user experiences will produce 1000-fold improvements in human capabilities. This new tools will amplify, augment, enhance, and empower people, just as the Web, email, search, navigation, digital photography, and many other applications have already done. Rather than emphasize autonomous machines and humanoid robots as team partners, these new tools will produce comprehensible, predictable, and controllable applications that promote self-efficacy, human responsibility, and social participation at scale. The goal is to ensure human control, while increasing the level of automation.
AI and Ethics
Faculty Leaders: Rob Reich and Seth Lazar
Conversations about ethics and AI are commonplace today, but they are often pitched at a high level of generality or abstraction. In this workshop, we gathered together leading young scholars, chiefly philosophers, to discuss a more detailed research agenda with a particular focus on moral and political philosophy and their intersections with AI. Topics included AI and explainability, AI and value alignment, governance of AI, and more.
AI and Ethics
Faculty Leaders: Rob Reich and Seth Lazar
Conversations about ethics and AI are commonplace today, but they are often pitched at a high level of generality or abstraction. In this workshop, we gathered together leading young scholars, chiefly philosophers, to discuss a more detailed research agenda with a particular focus on moral and political philosophy and their intersections with AI. Topics included AI and explainability, AI and value alignment, governance of AI, and more.
AI and Digital Policy in China
China’s government and tech industry have great ambitions for artificial intelligence development and leadership, and Chinese society is facing economic, ethical, and regulatory challenges related to AI much like those around the world. At a time when the U.S. and Chinese governments are locked in escalating disputes over technology and trade, understanding Chinese ambitions, realities, and politics surrounding digital technologies is ever more important. Hosted by DigiChina, a project of the Stanford Cyber Policy Center Program on Geopolitics, Technology and Governance and the New America Cybersecurity Initiative. Speakers include: Shazeda Ahmed, PhD Candidate, UC Berkeley School of Information; Predoctoral Fellow, Stanford Institute for Human-Centered Artificial Intelligence and Center for International Security and CooperationRogier Creemers, Assistant Professor in the Law and Governance of China, University of LeidenAndrew Grotto, William J. Perry International Security Fellow and Director of the Program on Geopolitics, Technology and Governance at the Stanford Cyber Policy Center; Visiting Fellow, Hoover InstitutionSamm Sacks, Cybersecurity Policy and China Digital Economy Fellow, New AmericaKatharin Tai, PhD Student, Political Science, Massachusetts Institute of TechnologyGraham Webster, Coordinating Editor, Stanford-New America DigiChina Project; China Digital Economy Fellow, New AmericaWu Shenkuo, Professor of Law, Beijing Normal UniversityJulia Voo, Research Director, China Cyber Policy Initiative, Harvard Belfer CenterYuan Yang, China Technology Correspondent, Financial Times The organizers are grateful for the support of the Harvard-MIT Ethics and Governance of AI Initiative. Please register at https://www.eventbrite.com/e/ai-and-digital-policy-in-china-tickets-76168400737 *Please park in the Galvez Lot (L-96) in one of the spaces with a HAI Only reserved sign.
AI and Digital Policy in China
China’s government and tech industry have great ambitions for artificial intelligence development and leadership, and Chinese society is facing economic, ethical, and regulatory challenges related to AI much like those around the world. At a time when the U.S. and Chinese governments are locked in escalating disputes over technology and trade, understanding Chinese ambitions, realities, and politics surrounding digital technologies is ever more important. Hosted by DigiChina, a project of the Stanford Cyber Policy Center Program on Geopolitics, Technology and Governance and the New America Cybersecurity Initiative. Speakers include: Shazeda Ahmed, PhD Candidate, UC Berkeley School of Information; Predoctoral Fellow, Stanford Institute for Human-Centered Artificial Intelligence and Center for International Security and CooperationRogier Creemers, Assistant Professor in the Law and Governance of China, University of LeidenAndrew Grotto, William J. Perry International Security Fellow and Director of the Program on Geopolitics, Technology and Governance at the Stanford Cyber Policy Center; Visiting Fellow, Hoover InstitutionSamm Sacks, Cybersecurity Policy and China Digital Economy Fellow, New AmericaKatharin Tai, PhD Student, Political Science, Massachusetts Institute of TechnologyGraham Webster, Coordinating Editor, Stanford-New America DigiChina Project; China Digital Economy Fellow, New AmericaWu Shenkuo, Professor of Law, Beijing Normal UniversityJulia Voo, Research Director, China Cyber Policy Initiative, Harvard Belfer CenterYuan Yang, China Technology Correspondent, Financial Times The organizers are grateful for the support of the Harvard-MIT Ethics and Governance of AI Initiative. Please register at https://www.eventbrite.com/e/ai-and-digital-policy-in-china-tickets-76168400737 *Please park in the Galvez Lot (L-96) in one of the spaces with a HAI Only reserved sign.
2019 Fall Conference: AI Ethics, Policy, and Governance
HAI's October 28-29 conference on AI Ethics, Policy, and Governance at Stanford University will convene experts and leaders from academia, industry, civil society, and government to explore critical and emerging issues related to understanding and guiding AI's human and societal impact. Through plenary discussions, breakout sessions, and workshops we will explore the latest research, delve into case studies, illuminate best practices, and build a global community of research, policy, and practice committed to ensuring that AI benefits humanity.
HAI's October 28-29 conference on AI Ethics, Policy, and Governance at Stanford University will convene experts and leaders from academia, industry, civil society, and government to explore critical and emerging issues related to understanding and guiding AI's human and societal impact. Through plenary discussions, breakout sessions, and workshops we will explore the latest research, delve into case studies, illuminate best practices, and build a global community of research, policy, and practice committed to ensuring that AI benefits humanity.
Embedding the Human in AI Research
Faculty Leaders: Jeff Hancock, Angèle Christin, Gaby Harari, and Londa Schiebinger
How can we integrate the human into work on artificial intelligence? How can we best define “human-centered”? Can HAI develop a mechanism that facilitates collaboration across disciplines to promote human-centered AI? These were some of the central questions that brought together 15 Stanford faculty members and researchers from the social sciences, humanities, and computer science for the “Embedding the Human in AI Research” workshop. As ethical AI guidelines are springing up, central questions of human-centeredness and effective collaboration remain open. Between 2011 and 2018, 84 ethical statements appeared globally, with 88% released after 2016 (Jobin, Ienca, & Vayena, Artificial Intelligence: the global landscape of ethics guidelines. Nature Machine Intelligence, 2019). Jobin et al., found that top topics of interest included: transparency, justice & fairness, non-maleficence, responsibility, and privacy. Not well represented was sustainability, defined as deploying AI to help protect the environment, improve the planet’s ecosystem, and promote peace. How do we put such ethical aspirations into action in HAI research? Can we develop a mechanism mechanism for HAI by which social scientists/humanists and technical people collaborate from the VERY BEGINNING when setting research priorities and formulating research questions? Overall: There was excellent discussion. A number of participants were new faculty at Stanford. They express concerns about time spent on interdisciplinary work, but were intrigued and pleased to be invited. Participants raised questions about how cultural and structural approaches can better be integrated into AI research. While there is growing attention to ethics within technology, ethics is very individualized, despite the fact that inequalities and biases can be systematic.Embedding the Human in AI Research
Faculty Leaders: Jeff Hancock, Angèle Christin, Gaby Harari, and Londa Schiebinger
How can we integrate the human into work on artificial intelligence? How can we best define “human-centered”? Can HAI develop a mechanism that facilitates collaboration across disciplines to promote human-centered AI? These were some of the central questions that brought together 15 Stanford faculty members and researchers from the social sciences, humanities, and computer science for the “Embedding the Human in AI Research” workshop. As ethical AI guidelines are springing up, central questions of human-centeredness and effective collaboration remain open. Between 2011 and 2018, 84 ethical statements appeared globally, with 88% released after 2016 (Jobin, Ienca, & Vayena, Artificial Intelligence: the global landscape of ethics guidelines. Nature Machine Intelligence, 2019). Jobin et al., found that top topics of interest included: transparency, justice & fairness, non-maleficence, responsibility, and privacy. Not well represented was sustainability, defined as deploying AI to help protect the environment, improve the planet’s ecosystem, and promote peace. How do we put such ethical aspirations into action in HAI research? Can we develop a mechanism mechanism for HAI by which social scientists/humanists and technical people collaborate from the VERY BEGINNING when setting research priorities and formulating research questions? Overall: There was excellent discussion. A number of participants were new faculty at Stanford. They express concerns about time spent on interdisciplinary work, but were intrigued and pleased to be invited. Participants raised questions about how cultural and structural approaches can better be integrated into AI research. While there is growing attention to ethics within technology, ethics is very individualized, despite the fact that inequalities and biases can be systematic.HAI Monthly Community Building Reception: AI and Refugee Integration
Jens Hainmueller is a Professor in the Department of Political Science at Stanford University and holds a courtesy appointment in the Stanford Graduate School of Business. He is also the Faculty Co-Director of the Stanford Immigration Policy Lab that is focused on the design and evaluation of immigration and integration policies and programs.
HAI Monthly Community Building Reception: AI and Refugee Integration
Jens Hainmueller is a Professor in the Department of Political Science at Stanford University and holds a courtesy appointment in the Stanford Graduate School of Business. He is also the Faculty Co-Director of the Stanford Immigration Policy Lab that is focused on the design and evaluation of immigration and integration policies and programs.