Human-Centered Leadership in an AI World
The future of work is arriving faster than ever, driven by generative AI, automation, and even quantum technologies. MIT Sloan faculty will present cutting-edge research and insights on three of the most pressing questions shaping the future workforce. Drawing on MIT Sloan’s tradition of management science, analytical rigor, and leadership development, this faculty showcase will highlight how organizations can harness innovation responsibly, develop resilient teams, and seize opportunities in a rapidly evolving economy.
Tuesday, April 14
5:30–7:30 p.m. | Showcase and Post-Reception
7:30 p.m. | Dean’s Circle Toast
Samberg Conference Center, MIT Building E52, 6th Floor
50 Memorial Drive, Cambridge, MA 02142
Featured Speakers
Swati Gupta
Class of 1947 Career Development Associate Professor
Swati Gupta is the Class of 1947 Career Development Associate Professor and an Associate Professor at the MIT Sloan School of Management in the Operations Research and Statistics Group. Her work focuses on deep theoretical questions in optimization…
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Danielle Li
David Sarnoff Professor of Management of Technology
Danielle Li is the David Sarnoff Professor of Management of Technology and a Professor at the MIT Sloan School of Management, as well as a Faculty Research Fellow at the National Bureau of Economic Research. Her research interests are in economics…
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Roberto Rigobon
Society of Sloan Fellows Professor of Management
Roberto Rigobon is the Society of Sloan Fellows Professor of Applied Economics at the MIT Sloan School of Management, a research associate with the National Bureau of Economic Research, and a Visiting Professor at IESA (Venezuela).Roberto is a…
Learn MoreFaculty Presentations:
Navigating Complex Decision Tradeoffs: Portfolios for Human–AI Decision-Making
Swati Gupta, PhD ’17, Class of 1947 Career Development Associate Professor; Associate Professor, Operations Research and Statistics
AI is reshaping how we design decision systems—allowing us to express tasks and build data-driven pipelines in natural language at an unprecedented scale. Yet there is rarely a single mathematical model that faithfully captures these language-based inputs; instead, we face a vast space of plausible formulations. Across all domains, decision-makers must navigate competing priorities without prematurely committing to one model of the world. This talk will present recent research on constructing portfolios of high-quality, representative solutions that span a broad range of possible formulations.
Who Owns Your Expertise? Scaling Knowledge Without Expropriation
Danielle Li, PhD 12’, David Sarnoff Professor of Management of Technology; Professor, Technological Innovation, Entrepreneurship, and Strategic Management
AI models are trained on examples generated by human labor: customer support calls, code written by engineers, medical notes produced by physicians. By storing and recombining human experience and judgment, these systems turn individual skill into durable, reusable “knowledge capital.” But when worker expertise is embedded in models, who owns the value it generates, and what use is left for workers themselves? This talk discusses how workers can share in the returns when their knowledge is codified and scaled. The aim is not to slow innovation, but to design institutions that let knowledge grow without expropriating the people who created it.
The EPOCH of AI: Which Human Capabilities Complement AI?
Roberto Rigobon, PhD ’97, Society of Sloan Fellows Professor of Management; Professor, Applied Economics
Together with MIT Sloan postdoctoral associate Isabella Loaiza, Professor Roberto Rigobon developed a framework to identify the human capabilities that complement AI today and in the future. The research builds on the differences between human cognition and AI’s underlying architecture—revealing a striking parallel between AI’s limitations and insights from psychological, neurological, and statistical perspectives. This talk will examine the actions humans perform today that will remain essential regardless of how AI evolves and concludes with a discussion on how society can prepare for this transition.