Lav Varshney
Title: Engineering Theory for Emerging Tech Strategy and Policy
Abstract: Mathematical engineering theories are useful in numerous ways, whether in providing fundamental relationships between the capabilities of emerging technologies and the resources they require; establishing fundamental benchmarks to evaluate new technologies on absolute scales, rather than only compared to previous technologies; delineating what is possible from what is impossible (and principles for optimal architectures); and giving ideals for pushing industry to build technologies that approach/achieve these limits. Yet, engineering theory is largely ignored in technology strategy and policy. Here, we argue that engineering theory can play dual roles for policy. First as a way to inform policymaking, via methods for net assessment, relationships between capabilities and resources for regulatory policy, and architectures for industrial policy. Second as a policy lever itself, through mechanisms of performativity and by countering philosophies of computational positivism. To make this case, we present vignettes from several areas of emerging tech policy including AI, 6G wireless, semiconductors, and quantum. For example, novel engineering theory can characterize emergent capabilities of AI and alternative paths to artificial general intelligence (AGI) such as information lattice learning. These vignettes will draw on policy work at the White House, with the City of Syracuse, and with the Indian Forest Service.
Bio: Lav Varshney is currently a visiting scholar at the Kellogg School of Management. He is an associate professor of electrical and computer engineering at the University of Illinois Urbana-Champaign, co-founder and CEO of Kocree, Inc., a startup company using novel human-integrated AI in social music co-creativity platforms to enhance human wellbeing across society, and chief scientist of Ensaras, Inc., a startup company focused on AI and wastewater treatment. He also holds appointments at RAND Corporation and at Brookhaven National Laboratory. He has previously been a research staff member at IBM Research and a principal research scientist at Salesforce Research AI. He is a former White House staffer, having served on the National Security Council staff as a White House Fellow, where he contributed to national AI and wireless communications policy. His research interests include information theory, artificial intelligence, and creativity. He received his B.S. degree from Cornell University and his S.M. and Ph.D. degrees from the Massachusetts Institute of Technology.
