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DTSTART;TZID=America/New_York:20261008T150000
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UID:7795-1791471600-1791475200@bridge2ai.org
SUMMARY:NIH Bridge2AI Training WG Learning Module | Data Privacy and Federated Learning: Private Insights into GenAI Use by Dr. Peter Kairouz
DESCRIPTION:NIH Bridge2AI Training WG Learning Module | Data Privacy and Federated Learning: Private Insights into GenAI Use by Dr. Peter Kairouz\nScheduled: Oct 8\, 2026 at 12:00 PM to 1:00 PM\, Local Phoenix Time |  https://arizona.zoom.us/j/86095514301\n\n\n\n\nDr. Peter Kairouz is a Research Scientist at Google\, where he leads groundbreaking research initiatives focused on distributed\, robust\, and privacy-preserving machine learning. After earning his Ph.D. in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign and serving as a Postdoctoral Research Fellow at Stanford University’s Information Systems Laboratory\, he has established himself as a significant voice on data privacy\, differential privacy\, and federated learning architecture. He is widely recognized for his foundational theoretical contributions\, including defining optimal bounds for privacy loss under sequential execution via the composition theorem for differential privacy\, and for co-authoring seminal field guides and reference frameworks like Advances and Open Problems in Federated Learning.\n\nContinuing to push the boundaries of AI safety\, Dr. Kairouz’s recent work investigates complex vulnerabilities in modern generative systems\, such as context hijacking threats in conversational agents (highlighted by his pioneering work on AirGapAgent) and the systematic flaws of ad-hoc heuristics in GenAI analytics. By championing mathematically rigorous alternatives like Provably Private Insights\, he bridges the critical gap between high-performance machine learning and uncompromised user data security at scale. An active leader in the research community\, he has served as general chair for premier workshops on federated learning and analytics\, and brings an extraordinary depth of vision to the future of trustworthy\, decentralized AI ecosystems.\n\nLEARNING OBJECTIVES\n\n\nEvaluate Heuristic Vulnerabilities: Analyze how ad-hoc\, heuristic-based privacy protections (such as PII redaction and k-anonymity) fail against sophisticated data extraction methods like the CLIOPATRA attack.\nUnderstand Provably Private Frameworks: Examine the architecture and principles of Provably Private Insights (PPI) as a mathematically guaranteed alternative to heuristics for secure AI analytics.\nExplore Secure Deployment Technologies: Learn how integrating Trusted Execution Environments (TEEs)\, secure LLMs\, and Differential Privacy enables scalable\, privacy-preserving data extraction in real-world applications.
URL:https://bridge2ai.org/event/7795/
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DTSTART;TZID=America/New_York:20261008T150000
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CREATED:20261004T234705Z
LAST-MODIFIED:20261004T234705Z
UID:7810-1791471600-1791475200@bridge2ai.org
SUMMARY:Bridge2AI Discussion Forum on Emerging ELSI Issues: “AI\, Augmented Intelligence\, in Healthcare"
DESCRIPTION:Please join us on Thursday\, October 8 2026 at 12pm-1pm PST/3pm-4pm EST for the discussion forum: “AI\, Augmented Intelligence\, in Healthcare”\, by Dr. Vincent Liu\, MD\, MS. \n\n\n\n\nArtificial intelligence is rapidly progressing from tools that generate predictions to systems that perform work and increasingly participate in care delivery. This talk explores how trust\, workflow integration\, and rigorous real-world evaluation\, rather than model capability alone\, are becoming the key determinants of healthcare AI impact using examples from traditional AI\, generative AI\, and into agentic AI. \n\n\n\n\n\nVincent Liu\, MD\, MS is Chief Data Officer for The Permanente Medical Group and a Research Scientist with the Kaiser Permanente Division of Research. A pulmonary-critical care physician\, health services researcher\, and AI leader\, Dr. Liu’s work focuses on the development\, implementation\, and rigorous evaluation of artificial intelligence in real-world healthcare settings. His research has spanned predictive analytics\, sepsis and deterioration detection\, ambient AI documentation\, and large-scale evaluation of AI-enabled care delivery\, including leadership of the Augmented Intelligence in Medicine and Healthcare Initiative (AIM-HI) and participation in ARPA-H programs evaluating agentic AI in clinical care. He is nationally recognized for advancing evidence-based approaches to healthcare AI that improve patient outcomes while emphasizing trust\, workflow integration\, safety\, and equity. \n\n\n\n\n\nMeeting ID: 941 6437 8982
URL:https://bridge2ai.org/event/bridge2ai-discussion-forum-on-emerging-elsi-issues-ai-augmented-intelligence-in-healthcare/
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