How can AI address climate change? alleviate poverty? predict natural disasters? cure diseases?
How can AI be invulnerable to bias? respect ethical boundaries? protect privacy?
The AI for Good Seminar Series (CME 500) explores ways artificial intelligence can benefit society and our planet. In weekly talks, leaders from academia, industry, and NGOs, who are at the forefront of using AI for social good, showcase AI applications that are forging positive changes in healthcare, the environment, education, technology, government and more. Speakers discuss how challenges regarding fairness, bias, privacy, ethics, etc. are beginning to be addressed.
Interested students will have access to supplemental materials such as mini case studies and Jupyter notebooks. Students of all academic backgrounds and interests can register for this 1-unit credit/no-credit course (CME 500). No prerequisites. Space permitting, this series is open to Stanford faculty, staff, and ICME partners. Students may register via Axess.
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Click here to watch via Livestream on most Mondays at 4:30pm.
To view past AI for Good and other AI seminar series sessions hosted by ICME, visit the ICME video page.
To read blog articles about past AI for Good sessions, visit the ICME News Page.
Opening Session: Is AI a Force for Good?
Our first session considers the central question of how AI can be a force for good and lays the framework for the entire series. As we explore how artificial intelligence can address some of the world’s most vexing issues, we will pair the positive outcomes with crucial awareness of potential unintended consequences. Our panel will discuss considerations to be made to ensure this new era will help humanity and not harm it.
- Rob Reich - Professor of Political Science and Director, Ethics in Society at Stanford University
- Margot Gerritsen - Professor of Energy Resources Engineering and Senior Associate Dean, Stanford School of Earth
- Sharad Goel - Founder & Executive Director, Stanford Computational Policy Lab and Assistant Professor, Management Science & Engineering at Stanford University
- Panel Moderator: Scott Penberthy, Head of Applied AI, Google
AI for Nonprofits | Google AI Impact Challenge
Breakthroughs in technology often have humble origins. Through it's Google AI Impact Challenge grant program, Google.org lends a helping hand to nonprofit innovators and social entrepreneurs who are using the power of AI to address social and environmental challenges. This session will feature a panel of Google AI Impact Challenge Grantees who are using AI and machine learning to tackle issues affecting the environment, educational equity, at-risk youth, and mental health.
- Heejae Lim - Founder and CEO, TalkingPoints
- Grace Mitchell - Data Analyst, WattTime
- Nick Hobbs - Senior Data Scientist, The Trevor Project.org
- Panel Moderator: Mollie Javerbaum - Google.org
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? Hear how data science tools and strategies are being used to safeguard our water supply, feed the worldwide human population, and promote greater biodiversity and global sustainability. Join Lucas Joppa and Stefano Ermon in a conversation with Gretchen C. Daily, Director of the Center for Conservation Biology at Stanford.
- Lucas Joppa - Chief Environmental Officer, Microsoft
- Stefano Ermon - Assistant Professor of Computer Science, Stanford University
- Gretchen C. Daily - Professor of Environmental Science and Director of the Center for Conservation Biology at Stanford.
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.
- Daniel E Ho - Professor of Law, Professor of Political Science, Director of the Regulation, Evaluation, and Governance Lab (RegLab) at Stanford University
- David Freeman Engstrom - Professor of Law and Associate Dean for Strategic Initiatives, Stanford Law School
AI for Healthcare
Marzyeh Ghassemi, Assistant Professor of Computer Science and Medicine, University of Toronto
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 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 Human Rights
Megan Price, Executive Director, Human Rights Data Analysis Group
As a team of data scientists, the Human Rights Data Analysis Group (HRDAG) partners with human rights advocacy organizations to identify questions that can be answered and arguments that can be strengthened using data science. Dr. Price’s talk will highlight how data science and AI methods and tools are being used to tell stories, build cases, and answer important questions about the human toll of conflicts in Syria, Mexico, and Guatemala. She will also address the potential harm that can be done when relying on incomplete and imperfect data such as predictive policing of drug use in Oakland.
The Future of AI: What Comes Next?
*Note the alternate Date and Location*
Beyond today’s plans for driverless cars and workerless factories, what will the future of AI really look like? Which sectors and nations will be affected the most? What core tenets should be set to ensure AI works for all of humanity? This session will be a conversation about the longer term impact of the AI era, and an inside look at the new Stanford Institute for Human-Centered AI (HAI), with John Etchemendy, Co-Director of HAI and Stanford's Provost Emeritus and Professor Russ Altman, the host of Stanford Engineering's "The Future of Everything" podcast.
John Etchemendy - Provost Emeritus, and Patrick Suppes Family Professor in the School of Humanities and Sciences, and Co-Director, Human-Centered Artificial Intelligence Initiative, Stanford University.
Russ Altman - Kenneth Fong Professor of Bioengineering, Genetics, Medicine, Biomedical Data Science and (by courtesy) Computer Science at Stanford University.
AI for Everyone | A Multi-Disciplinary Approach
How do we ensure AI solutions are designed to work for all – regardless of race, gender, ability, or background? Within the promise of artificial intelligence lie a number of difficult questions and challenges. A multi-disciplinary approach, one that has people from a variety of backgrounds involved in designing the solutions, is needed. In their talks and joint Q&A, Timnit and Omer will address challenges around data collection and algorithm development regarding bias, fairness, accountability, differential privacy and ethics.
Timnit Gebru, Research Scientist and Technical Co-lead of Google’s Ethical Artificial Intelligence Team
Omer Reingold, The Rajeev Motwani Professor of Computer Science at Stanford University.