TrAC Seminar (Hybrid) – Young M Lee

Detail

Date: November 11, 2025

Time: 1:00 – 2:00 PM CT

Location: 2004 Black Engineering or https://iastate.zoom.us/j/99289273148?pwd=XjAQaloJufOfkbYMb48Clci2NWWNR2.1&from=addon

Title: Safety of AI Systems

Abstract: Artificial Intelligence (AI) is advancing at an unprecedented pace, driving transformative changes across industries through automation, predictive analytics, intelligent decision-making, and operational efficiency. Yet, these remarkable advancements also introduce critical risks that, if left unmanaged, can compromise safety and public trust. This seminar discusses the importance of AI safety—the practice of designing, developing, and deploying AI systems in a manner that ensures reliability, ethical integrity, and the prevention of unintended harm. It examines key categories of AI risk, including bias and discrimination, lack of transparency, cybersecurity vulnerabilities, misuse of generative AI, and overreliance on autonomous systems. The talk explores major international AI standards, such as ISO/IEC JTC 1/SC 42 publications; regulatory frameworks including the EU GDPR and EU AI Act; and guidelines such as the NIST AI Risk
Management Framework. It introduces a structured framework of AI safety principles, encompassing technical, ethical, and governance dimensions, each with defined safety requirements aligned with international standards, regulations, and guidelines. The talk aims to provide insights into the evolving landscape of AI adoption, underscoring the need for a balanced approach that fosters both innovation and
responsibility. Ultimately, it advocates a standards-grounded, proactive approach to achieving safe, trustworthy, and human-centric AI systems that advance technology for the benefit of humanity.

Speaker Bio: Dr. Young M. Lee is technical leader and principal engineer for Artificial Intelligence at UL Solutions, where he leads AI safety initiatives, helps customers in developing and deploying safe AI products, and shapes the future of AI safety standards and certification services. Dr. Lee previously held the position of Distinguished Fellow and Director of AI at Johnson Controls for 6 years, where he led a global team of AI scientists in developing industrial AI solutions utilizing AI/ML and optimization technologies, including energy
prediction, energy optimization, fault detection, failure prediction, equipment control, and predictive maintenance applications. Prior to that, Dr. Lee dedicated 15 years to the IBM T.J. Watson Research Center as a Research Staff Member, Research Manager, and IBM Master Inventor. There, he was involved in the development of industrial applications that integrated AI/ML, mathematical modeling, optimization, and simulation. Earlier in his career, Dr. Lee spent over 10 years at BASF, a chemical company, where he established and led the Mathematical Modeling Group, driving the development of numerous AI, optimization, and simulation models for various manufacturing and supply chain processes. Dr. Lee is currently a technical advisory committee member of Pacific Northwest National Laboratory (PNNL)
providing technical advice in AI/ML, optimization model and simulation model to PNNL scientists for a U.S. Dept of Energy funded, multi-year project. He actively contributes to national and international AI standards development through participation in organizations such as ISO/IEC JTC 1/SC 42, IECEE, AIQI Consortium, and ANSI. Dr. Lee earned his B.S., M.S., and Ph.D. degrees from Columbia University. He has published six book chapters and over 80 refereed technical papers. As a prolific innovator, he is listed as the inventor on more than 100 patents.