Nagesh Gulkotwar, Program Manager, Google Inc., USA

Title of the Talk :
Trust Calibration and Cognitive Outpacing: Operationalizing Meaningful Human Control in AI-Augmented Program Leadership

Abstract of Talk:
As AI systems assume larger roles in program leadership workflows, a recurring operational problem has emerged: the speed and volume of AI-generated analysis frequently outpaces the cognitive capacity of human decision-makers, a condition referred to as cognitive outpacing. This talk examines how cognitive outpacing affects trust dynamics between human leaders and AI systems, and why miscalibrated trust—whether over-reliance that leads to uncritical acceptance of AI outputs, or under-trust that results in systematic underutilization—poses measurable risks to decision quality in high-stakes program environments. Drawing on principles from situational awareness theory, shared mental model research, and recent AI safety evaluation findings, this talk outlines a set of operational mechanisms for maintaining calibrated trust under conditions of information asymmetry between human and AI partners.
The discussion focuses on the concept of Meaningful Human Control (MHC) and how it can be operationalized in practice rather than treated as a policy abstraction. Specific attention is given to the tracking condition—ensuring AI systems remain responsive to the moral and contextual reasoning of human operators—and the tracing condition—ensuring that outcomes of AI-supported decisions can be attributed to informed human judgment. The talk proposes the notion of MHC-compatible trust zones: bounded operating ranges within which trust levels permit productive collaboration without eroding the vigilance required for effective human oversight. Implications for organizational governance, audit trail design, and the emerging regulatory landscape around AI-assisted decision-making are discussed, with reference to evaluation approaches that assess collaborative process quality rather than isolated AI performance metrics.

Bio : Nagesh Gulkotwar is a Program Manager at Google Inc., where he manages the integration of advertisements across search surfaces including AI Mode, Google Lens, and image and job search verticals. His work at Google over the past four years has focused on generative AI integration, risk intelligence, and search monetization within the Ads Journeys team. Prior to Google, he worked at Deloitte for over four years, managing IT transformation and compliance modernization projects for enterprise clients. He has eleven years of professional experience across technology, financial services, and consulting. His research interests include LLM-augmented recommender systems, trust-based modeling, and ethical AI evaluation frameworks.
He holds a Master of Science degree in Information systems and has published scholarly articles and co-authored preprints on prompt bias in large language models, agentic AI in financial services, and privacy-preserving human-AI retail interaction. He is a Distinguished fellow at SCRS and serves as a peer reviewer for the Information Processing & Management journal and for Manning Publications. He also contributes to the academic community as an IEEE Senior Member. He received the Excellence in Business Leadership in IT & ITES award at the 7th Global Business Leadership Awards & Summit.