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- HAI at Five Conference: Celebrating 5 Years of Impact
- HAI at Five
- 2024 AI+Education Summit: Advancing Human Learning with AI Technologies
- New Horizons in Generative AI: Science, Creativity, and Society
- 2023 HAI Congressional Bootcamp
- Creativity in the Age of AI: Stanford HAI Spring Symposium
- AI+Education Summit: AI in the Service of Teaching and Learning
- Tanner Lecture
- 2022 HAI Fall Conference on AI in the Loop: Humans in Charge
- 2022 HAI Congressional Bootcamp
- AI and the Economy Symposium
- 2022 HAI Spring Conference on Key Advances in Artificial Intelligence
- Data-Centric AI Virtual Workshop
- Stanford HAI Fall Conference: Four Radical Proposals for a Better Society
- Hoffman-Yee Symposium 2021
- AI100 Virtual Event
- Workshop on Foundation Models
- Intelligence Augmentation: AI Empowering People to Solve Global Challenges (Spring Conference)
- HAI Directors' Conversations
- HAI Grant Recipients
- Triangulating Intelligence: Melding Neuroscience, Psychology, and AI
- Digital Economy Lab Seminars
- Stanford HAI Highlights
- COVID + AI: The Road Ahead
- HAI Research Seminars
- COVID-19 and AI: A Virtual Conference by Stanford HAI
- Stanford HAI Events
- Lightning Talks: Stanford HAI Symposium 2019
- Stanford HAI Symposium 2019
- Stanford OVAL Workshop
- Stanford HAI 2019 Fall Conference
HAI Seminar with David Sandolow: AI for Good – Reducing Greenhouse Gas Emissions
27.11.2024
In this seminar, authors of the second edition of the Artificial Intelligence for Climate Change Mitigation Roadmap, including David Sandolow, presented insights from the book.
Expanding on the initial edition, the roadmap explores how AI technologies can help reduce greenhouse gas emissions in nine sectors including power, manufacturing and transportation. Key considerations include quantifying uncertainty, establishing causal relationships, and leveraging generative methods to unlock incremental and transformative opportunities.
This seminar took place at Stanford University on November 20, 2024.
HAI Seminar with Russell Wald: Expanding Academia's Role in Public Sector AI
21.01.2025
AI has captured public attention and become a focal point for policymakers. Concerns about AI have evolved from niche academic discussions to widespread public discourse, influencing legislative actions worldwide. Currently, the focus is mainly on industry-driven AI products, sidelining the broader AI ecosystem and societal impacts. This industry-centric approach marginalizes academia and civil society, potentially skewing AI governance toward industry interests rather than public good. To address this, diverse stakeholder involvement is essential in AI development. Robust academic research is crucial for human-centered AI, driving scientific curiosity, training future AI leaders, and providing policymakers with an objective understanding of AI.
In this seminar, HAI Executive Director Russell Wald discussed how governments must boost investment in public sector AI research and propose policies to balance industry dominance with significant academic contributions.
This seminar took place at Stanford University on January 15, 2025.
HAI Seminar with Juan Lavista Ferres: AI in Action
25.10.2024
Dr. Juan Lavista Ferres' talk explored the transformative role of artificial intelligence in tackling global challenges, as detailed in the "AI for Good" book. Shifting the conversation beyond conventional AI topics, Dr. Lavista Ferres presented real-world applications of AI, from biodiversity conservation to disaster response, showcasing how the technology is being used to drive ethical and impactful change.
Through powerful examples, this talk emphasizes the potential of AI to solve pressing societal issues and inspire dialogue on the responsible use of today’s technology. With smartphones now exceeding the computing power that once sent astronauts to the moon, the tools to address global challenges are within reach, demanding urgent and innovative solutions.
This seminar was recorded on October 23, 2024 at Stanford University.
HAI Seminar: Intersectional Biases in Generative Language Models and Their Psychosocial Impacts
24.10.2024
The rapid emergence of generative AI technologies has been shaped by a wave of early excitement and hope for a broad range of use cases. Yet, the impacts of the latest models on historically marginalized communities is still relatively understudied, including the potential for sociotechnical harm.
In this session, Faye-Marie Vassel, STEM Education, Equity, and Inclusion Postdoctoral Fellow at HAI, and Evan Shieh, Executive Director and AI Researcher at Young Data Scientists League, presented a line of research uncovering intersectional biases in generative language models when they are used for open-ended writing, drawing connections between their synthetic text outputs and known linguistic patterns that have psychosocial impacts for diverse learners in educational settings.
This seminar was recorded on October 16, 2024 at Stanford University.
HAI Seminar with Sheng Wang: Generative AI for Multimodal Biomedicine
08.11.2024
In this seminar, Sheng Wang, Assistant Professor in the School of Computer Science and Engineering at the University of Washington Seattle, introduced three recent works towards building multimodal biomedicine foundation models: GigaPath, the first whole-slide pathology foundation model that can handle gigapixel-level pathology images; OCTCube, the first 3D OCT retinal imaging foundation model; and BiomedParse, a multi-modal foundation model that integrates 9 major biomedical imaging modalities by projecting all of them into the text space.
The presentation was followed by a discussion on how multi-modal generative AI can advance future medical applications through multi-agent framework and integration with multi-omics datasets.
This seminar was recorded on November 6, 2024 at Stanford University.
Stanford HAI AI4ALL Information Session
17.12.2024
Learn about Stanford AI4ALL 2025 in our online info session - discover opportunities, ask questions, and get excited about the future of AI.
The Future of Third-Party AI Evaluation Workshop
28.10.2024
For more: https://sites.google.com/view/third...