We’re more than halfway through our Exploring Artificial Intelligence @ UW–Madison summer webinar series. Catch up on any sessions you missed with the recordings below as we continue our #AISummer. 😎
Session 1 — A Generative AI Briefing
Gartner technologists Dan Stoneman and David Bruce gave a broad overview of generative AI, offering examples of how it can be used in higher education and business, including content creation, data analysis, cybersecurity and research assistance. They also covered risks like bias, factual inaccuracies, privacy concerns and the digital divide.
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Session 2 — AI from Foundations to Applications
Professor Kyle Cranmer led a panel of faculty experts Rose Cersonsky, Joao Dorea, Kangwook Lee and Sharon Li in a discussion about the different ways they are investigating machine learning, large language models, transformers, and other foundational technologies that make AI possible. The panel covered a range of topics spanning AI hype versus reality, AI foundations, safety and applications in different domains like language, materials and agriculture.
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Session 3 — Opportunities & Challenges with Geospatial AI
Song Gao, associate professor of geography and director of UW’s Geospatial Data Science Lab, gave an overview of how AI has advanced geospatial sciences and highlighted challenges like biases, heterogeneity, weak reproducibility when transferring models across regions, and location privacy.
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Session 4 — From Breakthroughs to Empowerment: UW–Madison’s AI Contributions & Accessibility
UW Professor Jerry Zhu and data science facilitator Christopher Endemann led a discussion about how UW–Madison is conducting cutting-edge AI research across numerous departments, focusing on making AI faster, cheaper, more accurate and aligned with human values. A panel of students from UW’s Data Science Hub meetups joined to talk about their work and opportunities for people to develop AI skills and connect with experts across domains.
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Session 5 — AI Ethics & Privacy
UW–Madison faculty members Kaiping Chen and Yonatan Mintz discussed research into how to make AI systems ethical, unbiased and aligned with our values. They shared examples of bias in GPT-3 and the different ways prejudice can infect AI systems, from the training data to the engineers’ own biases. They talked about how we need careful system design and participatory processes to ensure AI empowers people and preserves individual rights.
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Session 6 — AI in Action: Intelligent Systems & Business Operations
Professor Laura Albert, chair of Industrial & Systems Engineering at in the College of Engineering, discussed AI’s role in business operations and systems, highlighting a 911 call center and UPS route optimization as examples. She covered 7 AI takeaways, including intelligence being a moving target, AI coming in many forms, and the need for quality data.
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Session 7 — Workday AI/ML: Different by Design
Gina Guillaume-Joseph and Dan Wesley from Workday discussed how Workday uses AI and machine learning in their products, with examples of skills matching for hiring and training employees. Workday works to ensure data privacy through security protocols like SOC audits and gets customer permission to use aggregated non-identifiable data to train algorithms, allowing real-time updates. The webinar concluded with a demonstration of Workday’s talent management and expense software featuring AI capabilities.
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Session 8 — AI & Medical Imaging
Dr. Alan McMillan, a professor in the Department of Radiology in the School of Medicine and Public Health, discussed how radiologists are using AI as an assistive technology to save time analyzing medical imaging like MRI and PET scans. He reviewed sample projects showing AI improving scan efficiency and analyzing additional health data from existing scans. McMillan emphasized the need for thoughtful evaluation before applying AI clinically to ensure safety, interpretability and avoid bias.
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Session 9 — Generative AI at Microsoft
Nick Switanek, principal data scientist working on artificial intelligence at Microsoft, gave a brief survey of how the company is developing generative AI models and integrating them into its portfolio of products and services. Switanek introduced and contextualized the solution patterns for AI applications that Microsoft and its customers commonly use, and discussed Microsoft’s principles for responsible AI before closing with a discussion about emerging trends.
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Session 10 — Town Hall on Teaching & Learning
John Zumbrunnen, UW–Madison vice provost for teaching & learning, led a conversation about the challenges and opportunities generative artificial intelligence presents for teaching and learning at the college level. Panelists Emily Hall, Nathan Jung, Jonathan Klein, Kathy Prem, Tonya Schmidt and Tamara Walker discussed policies, principles and best practices and fielded audience questions.
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Read a recap article about session 10
Session 11 — AI in Healthcare: Evolving Care Landscapes
A panel discussion with representatives from Epic Systems, UW Health and the School of Medicine and Public Health about how AI is reshaping healthcare. This webinar explored practical AI innovations and discussed their impact on providers and patients—including how ChatGPT is in “an in-basket near you” through a combination of Epic’s dedication to a vision and UW Health’s expertise in implementation science.
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Session 12 — AI in Biomedical Health
Lightning talks about biomedical applications of artificial intelligence from UW–Madison researchers working to develop algorithms and models to help us better understand the human body, improve communication and create treatments that improve and save lives.
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Session 12 with audio descriptions: coming soon