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Upcoming Events

AllConferenceSeminars
Alexandr Lenk & Arvind Karunakaran | Industry Conversation with Instacart
SeminarSep 23, 202612:00 PM - 1:15 PM
September
23
2026

This seminar pairs a case study of AI diffusion with an organizational approach to technological changes in the workplace.

September
23
2026

Alexandr Lenk & Arvind Karunakaran | Industry Conversation with Instacart

Sep 23, 202612:00 PM - 1:15 PM

This seminar pairs a case study of AI diffusion with an organizational approach to technological changes in the workplace.

Industry, Innovation
Marlowe | AI + Data for Science with Stephen Baccus
SeminarSep 23, 2026
September
23
2026

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.

September
23
2026

Marlowe | AI + Data for Science with Stephen Baccus

Sep 23, 2026

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.

Data Science
World Development Report 2026: The Promise of Artificial Intelligence
Sep 24, 20269:00 AM - 4:15 PM
September
24
2026
September
24
2026

World Development Report 2026: The Promise of Artificial Intelligence

Sep 24, 20269:00 AM - 4:15 PM
International Affairs, International Security, International Development
Daniel Zhang, Caroline Meinhardt, Jiajun Wu, and Russell Wald | The World Model and Spatial Intelligence Era: Governing AI Beyond Language
SeminarSep 30, 20263:00 PM - 4:15 PM
September
30
2026

As AI moves beyond language into systems that can perceive, understand, and act in the physical world, a new frontier is emerging: world models—AI systems that build and maintain working representations of real environments to predict how they change in response to action.

September
30
2026

Daniel Zhang, Caroline Meinhardt, Jiajun Wu, and Russell Wald | The World Model and Spatial Intelligence Era: Governing AI Beyond Language

Sep 30, 20263:00 PM - 4:15 PM

As AI moves beyond language into systems that can perceive, understand, and act in the physical world, a new frontier is emerging: world models—AI systems that build and maintain working representations of real environments to predict how they change in response to action.

Regulation, Policy, Governance
Marlowe | AI + Data for Science with Gordon Wetzstein
SeminarSep 30, 2026
September
30
2026

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.

September
30
2026

Marlowe | AI + Data for Science with Gordon Wetzstein

Sep 30, 2026

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.

Data Science
Empirical Methods in the Age of AI
ConferenceOct 02, 2026
October
02
2026
October
02
2026

Empirical Methods in the Age of AI

Oct 02, 2026
Computer Vision
Data Science
Anastasios Angelopoulos | Measuring AI in the Real World
SeminarOct 02, 20261:00 PM - 2:15 PM
October
02
2026

This seminar co-hosted with the AI Measurement Science Center (AIMS) invites speakers to discuss academic work in AI evaluation and measurement science.

October
02
2026

Anastasios Angelopoulos | Measuring AI in the Real World

Oct 02, 20261:00 PM - 2:15 PM

This seminar co-hosted with the AI Measurement Science Center (AIMS) invites speakers to discuss academic work in AI evaluation and measurement science.

Data Science
Tim de Silva | AI Financial Advice: Supply, Demand, and Life Cycle Implications
SeminarOct 07, 202612:00 PM - 1:15 PM
October
07
2026
October
07
2026

Tim de Silva | AI Financial Advice: Supply, Demand, and Life Cycle Implications

Oct 07, 202612:00 PM - 1:15 PM
Finance, Business
Marlowe | AI + Data for Science with Olivier Gevaert
SeminarOct 07, 2026
October
07
2026

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.

October
07
2026

Marlowe | AI + Data for Science with Olivier Gevaert

Oct 07, 2026

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.

Data Science
Marlowe | AI + Data for Science with Curtis Langlotz
SeminarOct 14, 2026
October
14
2026

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.

October
14
2026

Marlowe | AI + Data for Science with Curtis Langlotz

Oct 14, 2026

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.

Data Science
Bay Area Tech Economics Seminar with Rehan Khan
SeminarOct 20, 20266:30 PM - 8:30 PM
October
20
2026
October
20
2026

Bay Area Tech Economics Seminar with Rehan Khan

Oct 20, 20266:30 PM - 8:30 PM
Economy, Markets
Data Science
Marlowe | AI + Data for Science with Anshul Kundaje
SeminarOct 21, 2026
October
21
2026

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.

October
21
2026

Marlowe | AI + Data for Science with Anshul Kundaje

Oct 21, 2026

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.

Data Science
Confronting Our AI Future: Hope, Fear, and the Choices Ahead
ConferenceOct 28, 20269:00 AM - 6:45 PM
October
28
2026

The rapid acceleration of AI comes with a profound wave of anxiety. Across every sector of society, people are facing unsettling questions about their worth and their place in a shifting world.

October
28
2026

Confronting Our AI Future: Hope, Fear, and the Choices Ahead

Oct 28, 20269:00 AM - 6:45 PM

The rapid acceleration of AI comes with a profound wave of anxiety. Across every sector of society, people are facing unsettling questions about their worth and their place in a shifting world.

Workforce, Labor
Sciences (Social, Health, Biological, Physical)
Marlowe | AI + Data for Science with Dan Yamins
SeminarOct 28, 2026
October
28
2026

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.

October
28
2026

Marlowe | AI + Data for Science with Dan Yamins

Oct 28, 2026

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.

Data Science
Marcos Santiago Rojas Pino & Thomas Caruso | Building an International AI Platform for Health Professions Education and the Learning Sciences
SeminarNov 04, 202612:00 PM - 1:15 PM
November
04
2026

Clinical Mind AI is a Stanford-developed, international collaborative platform designed to strengthen clinical reasoning education through AI-simulated patient encounters across health professions.

November
04
2026

Marcos Santiago Rojas Pino & Thomas Caruso | Building an International AI Platform for Health Professions Education and the Learning Sciences

Nov 04, 202612:00 PM - 1:15 PM

Clinical Mind AI is a Stanford-developed, international collaborative platform designed to strengthen clinical reasoning education through AI-simulated patient encounters across health professions.

Healthcare
Education, Skills
Marlowe | AI + Data for Science with Ruijiang Li
SeminarNov 04, 2026
November
04
2026

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.

November
04
2026

Marlowe | AI + Data for Science with Ruijiang Li

Nov 04, 2026

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.

Data Science
2026 SC2 Student Conference
ConferenceNov 06, 20268:30 AM - 5:00 PM
November
06
2026
November
06
2026

2026 SC2 Student Conference

Nov 06, 20268:30 AM - 5:00 PM
Data Science
Marlowe | AI + Data for Science with Mohsen Bayati
SeminarNov 11, 2026
November
11
2026

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.

November
11
2026

Marlowe | AI + Data for Science with Mohsen Bayati

Nov 11, 2026

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.

Data Science
AI100 | AI Goes Mainstream: The Scaling Era and the Rise of Generative AI
SeminarNov 18, 202612:00 PM - 1:15 PM
November
18
2026

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 October 2026. The report was commissioned by the AI100 standing committee and led by study panel chair Michael Wooldridge.

November
18
2026

AI100 | AI Goes Mainstream: The Scaling Era and the Rise of Generative AI

Nov 18, 202612:00 PM - 1:15 PM

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 October 2026. The report was commissioned by the AI100 standing committee and led by study panel chair Michael Wooldridge.

Foundation Models
Industry, Innovation
Democracy
Marlowe | AI + Data for Science with Andreas Tolias
SeminarNov 18, 2026
November
18
2026

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.

November
18
2026

Marlowe | AI + Data for Science with Andreas Tolias

Nov 18, 2026

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.

Data Science
Marlowe | AI + Data for Science with Leonidas Guibas
SeminarDec 02, 2026
December
02
2026

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.

December
02
2026

Marlowe | AI + Data for Science with Leonidas Guibas

Dec 02, 2026

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.

Data Science
Angèle Christin & Hannah Zeavin | Gurus, Hucksters, Entertainers: How Influencers Reshaped Social Media
SeminarDec 09, 202612:00 PM - 1:15 PM
December
09
2026

Please join us for an illuminating investigation of the complex work of social media content creators—their lives, conflicts, and controversies. 

December
09
2026

Angèle Christin & Hannah Zeavin | Gurus, Hucksters, Entertainers: How Influencers Reshaped Social Media

Dec 09, 202612:00 PM - 1:15 PM

Please join us for an illuminating investigation of the complex work of social media content creators—their lives, conflicts, and controversies. 

Communications, Media

Featured Videos

Hear from speakers and attendees at recent Stanford HAI events across research, policy, and education.

Previous Events at HAI

AllConferenceSeminarsWorkshops
HAI Weekly Seminar with David Robinson - Governing an Algorithm in the Wild
SeminarApr 10, 202011:00 AM - 12:00 PM
April
10
2020

HAI Weekly Seminar with David Robinson - Governing an Algorithm in the Wild

Apr 10, 202011:00 AM - 12:00 PM
HAI Weekly Seminar with John Markoff - Second Thoughts on Digital Utopianism
SeminarMar 27, 202011:00 AM - 12:00 PM
March
27
2020

Bio: John Markoff is HAI’s Journalist-in-Residence. He is also a research affiliate at the Center for Advanced Study in the Behavioral Sciences or CASBS, participating in projects focusing on the future of work and artificial intelligence. He is currently researching a biography of Stewart Brand, the creator of the Whole Earth Catalog. Previously he was a Berggruen Fellow at CASBS. He has also been a staff historian at the Computer History Museum in Mountain View, Calif. Until 2017, he was a reporter at The New York Times, beginning in March 1988 as the paper’s national computer writer. Prior to joining the Times, he worked for the San Francisco Examiner. He has written about technology for Pacific News Service. He was a reporter at Infoworld and West Coast editor for Byte Magazine and wrote a column on personal computers for the San Jose Mercury. He has also been a lecturer at the University of California at Berkeley School of Journalism and an adjunct faculty member of the Stanford Graduate Program on Journalism. In 2013 he was awarded a Pulitzer Prize in explanatory reporting as part of a New York Times project on labor and automation. In 2007, he was named a fellow of the Society of Professional Journalists, the organization’s highest honor. In June of 2010, the New York Times presented him with the Nathaniel Nash Award, which is given annually for foreign and business reporting. He is the co-author of The High Cost of High Tech, published by Harper & Row. He co-wrote Cyberpunk: Outlaws and Hackers on the Computer Frontier published Simon & Schuster. Hyperion published Takedown: The Pursuit and Capture of America's Most Wanted Computer Outlaw, which he co-authored with Tsutomu Shimomura. What the Dormouse Said: How the Sixties Counterculture Shaped the Personal Computer Industry, was published by Viking Books. Machines of Loving Grace: The Quest for Common Ground Between Humans and Robots, was published by HarperCollins Ecco. Markoff grew up in Palo Alto, California, and graduated from Whitman College, Walla Walla, Washington. He attended graduate school at the University of Oregon and received a masters degree in sociology.

HAI Weekly Seminar with John Markoff - Second Thoughts on Digital Utopianism

Mar 27, 202011:00 AM - 12:00 PM

Bio: John Markoff is HAI’s Journalist-in-Residence. He is also a research affiliate at the Center for Advanced Study in the Behavioral Sciences or CASBS, participating in projects focusing on the future of work and artificial intelligence. He is currently researching a biography of Stewart Brand, the creator of the Whole Earth Catalog. Previously he was a Berggruen Fellow at CASBS. He has also been a staff historian at the Computer History Museum in Mountain View, Calif. Until 2017, he was a reporter at The New York Times, beginning in March 1988 as the paper’s national computer writer. Prior to joining the Times, he worked for the San Francisco Examiner. He has written about technology for Pacific News Service. He was a reporter at Infoworld and West Coast editor for Byte Magazine and wrote a column on personal computers for the San Jose Mercury. He has also been a lecturer at the University of California at Berkeley School of Journalism and an adjunct faculty member of the Stanford Graduate Program on Journalism. In 2013 he was awarded a Pulitzer Prize in explanatory reporting as part of a New York Times project on labor and automation. In 2007, he was named a fellow of the Society of Professional Journalists, the organization’s highest honor. In June of 2010, the New York Times presented him with the Nathaniel Nash Award, which is given annually for foreign and business reporting. He is the co-author of The High Cost of High Tech, published by Harper & Row. He co-wrote Cyberpunk: Outlaws and Hackers on the Computer Frontier published Simon & Schuster. Hyperion published Takedown: The Pursuit and Capture of America's Most Wanted Computer Outlaw, which he co-authored with Tsutomu Shimomura. What the Dormouse Said: How the Sixties Counterculture Shaped the Personal Computer Industry, was published by Viking Books. Machines of Loving Grace: The Quest for Common Ground Between Humans and Robots, was published by HarperCollins Ecco. Markoff grew up in Palo Alto, California, and graduated from Whitman College, Walla Walla, Washington. He attended graduate school at the University of Oregon and received a masters degree in sociology.

HAI Weekly Seminar with Marietje Schaake
SeminarMar 20, 202011:00 AM - 12:00 PM
March
20
2020

Bio: Marietje Schaake is an International Policy Fellow at the Stanford Institute for Human-Centered Artificial Intelligence (HAI) and the International Policy Director of the Cyber Policy Center, where she conducts policy-relevant research focused on cyber policy recommendations for industry and government. In addition to her own research, she represents the center to governments, NGOs, and the technology industry. Schaake also teaches courses on cyber policy from an international perspective, and brings to Stanford leaders from around the world to discuss cyber policy.  Prior to joining Stanford, Marietje Schaake led an active career in politics and civic service. She was a representative of the Dutch Democratic Party and the Alliance of Liberals and Democrats for Europe (ALDE) in European Parliament where she was first elected in 2009. In European Parliament, Schaake focused on trade, foreign policy and technology, and as a member of the Global Commission on the Stability of Cyberspace, and founder of the European Parliament Intergroup on the European Digital Agenda, Schaake develops solutions to strengthen the rule of law online, including initiating the net neutrality law now in effect throughout Europe.

HAI Weekly Seminar with Marietje Schaake

Mar 20, 202011:00 AM - 12:00 PM

Bio: Marietje Schaake is an International Policy Fellow at the Stanford Institute for Human-Centered Artificial Intelligence (HAI) and the International Policy Director of the Cyber Policy Center, where she conducts policy-relevant research focused on cyber policy recommendations for industry and government. In addition to her own research, she represents the center to governments, NGOs, and the technology industry. Schaake also teaches courses on cyber policy from an international perspective, and brings to Stanford leaders from around the world to discuss cyber policy.  Prior to joining Stanford, Marietje Schaake led an active career in politics and civic service. She was a representative of the Dutch Democratic Party and the Alliance of Liberals and Democrats for Europe (ALDE) in European Parliament where she was first elected in 2009. In European Parliament, Schaake focused on trade, foreign policy and technology, and as a member of the Global Commission on the Stability of Cyberspace, and founder of the European Parliament Intergroup on the European Digital Agenda, Schaake develops solutions to strengthen the rule of law online, including initiating the net neutrality law now in effect throughout Europe.

HAI Weekly Seminar with Brian Cantwell Smith - Reckoning and Judgment: The Promise of AI
SeminarMar 06, 202011:00 AM - 12:00 PM
March
06
2020

Abstract: New developments in Artificial Intelligence, particularly deep learning and other forms of “second-wave” AI, are attracting enormous public attention.  Both triumphalists and doomsayers are predicting that human-level AI may be “just around the corner.”  To assess whether that prediction is true, we need a broad understanding of intelligence, in terms of which to assess: (i) what kinds of intelligence machines currently have, and will likely have in the future; and (ii) what kinds of intelligence people currently have, and may be capable of in the future.  As the first step in this direction, I distinguish two kinds of intelligence: (i) “reckoning,” the kind of calculative rationality that computers excel at, including both first- and second-wave AI; and (ii) “judgment,” a form of dispassionate, deliberative thought, grounded in ethical commitment and responsible action, that is appropriate to the situation in which it is deployed.  AI will develop world-changing reckoning systems, I argue, but nothing in AI as currently conceived approaches what is required to build a system capable of judgment. 

Bio: Brian Cantwell Smith is Reid Hoffman Professor of Artificial Intelligence and the Human at the University of Toronto, where he is also Professor of Information, Philosophy, Cognitive Science, and the History and Philosophy of Science and Technology, as well as being a Senior Fellow at Massey College.   Smith’s research focuses on the philosophical foundations of computation, artificial intelligence, and mind, and on fundamental issues in metaphysics and epistemology.  In the 1980s he developed the world’s first reflective programming language (3Lisp).  He is the author of *On the Origin of Objects* (MIT Press, 1996), and of *On the Promise of Artificial Intelligence: Reckoning and Judgment* (MIT Press, 2019).

HAI Weekly Seminar with Brian Cantwell Smith - Reckoning and Judgment: The Promise of AI

Mar 06, 202011:00 AM - 12:00 PM

Abstract: New developments in Artificial Intelligence, particularly deep learning and other forms of “second-wave” AI, are attracting enormous public attention.  Both triumphalists and doomsayers are predicting that human-level AI may be “just around the corner.”  To assess whether that prediction is true, we need a broad understanding of intelligence, in terms of which to assess: (i) what kinds of intelligence machines currently have, and will likely have in the future; and (ii) what kinds of intelligence people currently have, and may be capable of in the future.  As the first step in this direction, I distinguish two kinds of intelligence: (i) “reckoning,” the kind of calculative rationality that computers excel at, including both first- and second-wave AI; and (ii) “judgment,” a form of dispassionate, deliberative thought, grounded in ethical commitment and responsible action, that is appropriate to the situation in which it is deployed.  AI will develop world-changing reckoning systems, I argue, but nothing in AI as currently conceived approaches what is required to build a system capable of judgment. 

Bio: Brian Cantwell Smith is Reid Hoffman Professor of Artificial Intelligence and the Human at the University of Toronto, where he is also Professor of Information, Philosophy, Cognitive Science, and the History and Philosophy of Science and Technology, as well as being a Senior Fellow at Massey College.   Smith’s research focuses on the philosophical foundations of computation, artificial intelligence, and mind, and on fundamental issues in metaphysics and epistemology.  In the 1980s he developed the world’s first reflective programming language (3Lisp).  He is the author of *On the Origin of Objects* (MIT Press, 1996), and of *On the Promise of Artificial Intelligence: Reckoning and Judgment* (MIT Press, 2019).

HAI Weekly Seminar with Thomas Dimson - Algorithms Algorithms Algorithms
SeminarFeb 28, 202011:00 AM - 12:00 PM
February
28
2020

Abstract: The biggest challenge with the democratization of content is how to make sense of the scale. In the last decade, curation of content has consolidated into the hands of a few of the largest technology companies. Today, that curation takes the form of machine learning — often dubbed algorithms by the media. Thomas helped build and introduce the most controversial algorithms of Instagram: non-chronological feed and personalized recommendations. He will discuss challenges from the perspective of an engineer in the control room as Instagram scaled to serve over a billion people. Thomas will share a few of his thoughts about future directions as we start to form a dialogue about the responsibilities of platforms operating on a global scale.

Bio: Thomas Dimson is the original author of “The Algorithm” — the recommender systems behind Instagram's feed, stories and discovery surfaces. He joined Instagram as one of its first 50 employees in 2013, working for seven years as a principal engineer and eventually an engineering director. In that time, he also invented products such as the stories polling sticker, Hyperlapse, and engineering and was named one of the top ten most creative people in business by Fast Company. Thomas graduated from the University of Waterloo with a bachelor's of mathematics and received his master's in computer science from Stanford with a specialization in artificial intelligence.

HAI Weekly Seminar with Thomas Dimson - Algorithms Algorithms Algorithms

Feb 28, 202011:00 AM - 12:00 PM

Abstract: The biggest challenge with the democratization of content is how to make sense of the scale. In the last decade, curation of content has consolidated into the hands of a few of the largest technology companies. Today, that curation takes the form of machine learning — often dubbed algorithms by the media. Thomas helped build and introduce the most controversial algorithms of Instagram: non-chronological feed and personalized recommendations. He will discuss challenges from the perspective of an engineer in the control room as Instagram scaled to serve over a billion people. Thomas will share a few of his thoughts about future directions as we start to form a dialogue about the responsibilities of platforms operating on a global scale.

Bio: Thomas Dimson is the original author of “The Algorithm” — the recommender systems behind Instagram's feed, stories and discovery surfaces. He joined Instagram as one of its first 50 employees in 2013, working for seven years as a principal engineer and eventually an engineering director. In that time, he also invented products such as the stories polling sticker, Hyperlapse, and engineering and was named one of the top ten most creative people in business by Fast Company. Thomas graduated from the University of Waterloo with a bachelor's of mathematics and received his master's in computer science from Stanford with a specialization in artificial intelligence.

HAI Weekly Seminar with Garance Burke - Steering Journalism Towards Data Science
SeminarFeb 21, 202011:00 AM - 12:00 PM
February
21
2020
Abstract: Algorithmic tools are transforming our daily lives, but journalism is still playing catch up. As in other times of global transition, news consumers are anxious that artificial intelligence will overtake human abilities and question whether these systems will  take our jobs, amplify racial bias or expose our privacy. As one of few technically trained data journalists, it’s clear to me that most newsrooms lack the training to understand how algorithms work, let alone how they are deployed to guide crucial decisions in hiring, banking, criminal justice and medicine. And the rapidly expanding field of algorithmic accountability reporting has yet to be codified in simple terms that most reporters can understand. Naturally, this leads to questions: How can we ensure that reporters ask the right questions? Or that a larger group of journalists can access work examining the technology's impacts on society? How can we encourage nuanced journalism about AI that accurately reflects the state of science? As an inaugural 2020 Human Centered Artificial Intelligence-John S. Knight journalism fellow, I am developing a new set of journalistic best practices to provide reporters and editors with scientifically rigorous standards for algorithmic accountability reporting. Bio: Garance Burke is an investigative journalist who applies her training in statistical analysis to reveal vital truths in the public interest. Often driven by data, her work for The Associated Press on topics ranging from immigration to cybersecurity has helped to shape presidential elections, inspire congressional hearings and spark federal investigations. As an inaugural 2020 Institute for Human-Centered Artificial Intelligence-John S. Knight Journalism fellow, she is deepening her data science skills to draft standards that will help train more reporters to produce deeper stories about the algorithmic systems they encounter on their beats. In 2019, her stories were honored as a finalist for the Pulitzer Prize in national reporting and the Anthony Shadid Award for Journalism Ethics, and received the Robert F. Kennedy Journalism Award and the National Press Club Award for Diplomatic Correspondence. Burke began her career at the Mexican financial newspaper El Financiero, then worked in Mexico City for The Washington Post and The Boston Globe. She received dual master’s degrees from the University of California, Berkeley’s Goldman School of Public Policy and Graduate School of Journalism, where she has taught as a lecturer in basic data journalism. 

HAI Weekly Seminar with Garance Burke - Steering Journalism Towards Data Science

Feb 21, 202011:00 AM - 12:00 PM
Abstract: Algorithmic tools are transforming our daily lives, but journalism is still playing catch up. As in other times of global transition, news consumers are anxious that artificial intelligence will overtake human abilities and question whether these systems will  take our jobs, amplify racial bias or expose our privacy. As one of few technically trained data journalists, it’s clear to me that most newsrooms lack the training to understand how algorithms work, let alone how they are deployed to guide crucial decisions in hiring, banking, criminal justice and medicine. And the rapidly expanding field of algorithmic accountability reporting has yet to be codified in simple terms that most reporters can understand. Naturally, this leads to questions: How can we ensure that reporters ask the right questions? Or that a larger group of journalists can access work examining the technology's impacts on society? How can we encourage nuanced journalism about AI that accurately reflects the state of science? As an inaugural 2020 Human Centered Artificial Intelligence-John S. Knight journalism fellow, I am developing a new set of journalistic best practices to provide reporters and editors with scientifically rigorous standards for algorithmic accountability reporting. Bio: Garance Burke is an investigative journalist who applies her training in statistical analysis to reveal vital truths in the public interest. Often driven by data, her work for The Associated Press on topics ranging from immigration to cybersecurity has helped to shape presidential elections, inspire congressional hearings and spark federal investigations. As an inaugural 2020 Institute for Human-Centered Artificial Intelligence-John S. Knight Journalism fellow, she is deepening her data science skills to draft standards that will help train more reporters to produce deeper stories about the algorithmic systems they encounter on their beats. In 2019, her stories were honored as a finalist for the Pulitzer Prize in national reporting and the Anthony Shadid Award for Journalism Ethics, and received the Robert F. Kennedy Journalism Award and the National Press Club Award for Diplomatic Correspondence. Burke began her career at the Mexican financial newspaper El Financiero, then worked in Mexico City for The Washington Post and The Boston Globe. She received dual master’s degrees from the University of California, Berkeley’s Goldman School of Public Policy and Graduate School of Journalism, where she has taught as a lecturer in basic data journalism. 
HAI Weekly Seminar with Lucy Suchman - Demystifying AI as an Ethical Project
SeminarFeb 14, 2020
February
14
2020

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 Weekly Seminar with Lucy Suchman - Demystifying AI as an Ethical Project

Feb 14, 2020

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

Ethics, Equity, Inclusion
HAI Weekly Seminar with Bongjun Ko - The Value of Data: An Engineer’s Perspective
SeminarFeb 07, 202011:00 AM - 12:00 PM
February
07
2020

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

Feb 07, 202011:00 AM - 12:00 PM

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.

Machine Learning
AI for Good Seminar Series: AI for Government
SeminarFeb 03, 20204:00 PM - 5:30 PM
February
03
2020

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

Feb 03, 20204:00 PM - 5:30 PM

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.

Economy, Markets
HAI Weekly Seminar with Johannes Eichstaedt - Measuring Physical and Mental Health Using Social Media
SeminarJan 24, 202011:00 AM - 12:00 PM
January
24
2020

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

Jan 24, 202011:00 AM - 12:00 PM

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.

 

Sciences (Social, Health, Biological, Physical)
Communications, Media
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