Press Room
My research and commentary regularly appear in public discussions about technology, AI, and the future of work. I’m available for interviews, background conversations, and rapid-response commentary.
Media Interview
NPR (KUOW)
April 5, 2025
Interview on how AI exposure differs across workers, why regional labor impacts vary, and what policymakers should monitor as adoption accelerates.
Presentation
Chapman University Panel
Speaking Session · 60 minutes
A panel of Chapman University experts discussing how AI is reshaping labor demand in Southern California, which jobs are most affected, and how workers and firms can prepare for the rapidly changing future of work.
Finding: AI exposure varies significantly by demographics and region, creating uneven labor market effects.
Why it matters: Policymakers need targeted interventions, not one-size-fits-all responses to AI adoption.
Finding: API adoption drives measurable firm growth through platform openness, but introduces governance tradeoffs.
Why it matters: Helps explain why API access restrictions are at the center of major antitrust disputes.
Finding: Coordinated blocking of piracy sites meaningfully shifts users toward legal consumption.
Why it matters: Provides empirical evidence for policy debates about judicial site blocking.
Finding: Machine learning models can detect conflict-related infrastructure destruction at scale from satellite imagery.
Why it matters: Won the BBVA Foundation Award; enables monitoring in areas where ground access is impossible.
“AI won’t replace jobs—it will replace tasks. The question is which tasks, for whom, and how fast.”
— On AI and labor market disruption
“The firms that win in the AI era won’t be the ones that automate the most—they’ll be the ones that figure out how to combine human judgment with machine speed.”
— On AI workforce strategy
Jonathan Hersh is an economist and machine learning scientist at Chapman University. His research on AI’s impact on work has been published in Management Science, PNAS, and NeurIPS, and featured on NPR’s Weekend Edition. He is the author of the forthcoming book AI-Proof Jobs and writes Artificially Optimistic.
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Jonathan Hersh is an Associate Professor of Economics and Management Science at the Argyros School of Business at Chapman University. His research focuses on how artificial intelligence is transforming business, labor, and society, with particular emphasis on workforce dynamics and managerial decision-making. He applies machine learning to unstructured data—such as text, images, and satellite imagery—to develop predictive and causal models that inform strategy and policy in data-scarce environments.
Professor Hersh has worked as a machine learning scientist at Workhelix, a Series A startup focused on AI workforce strategy, and as a data scientist for the World Bank and the Inter-American Development Bank. His research has been published in leading journals including Management Science, MIS Quarterly, the Proceedings of the National Academy of Sciences, and NeurIPS.
In 2023, he received the BBVA Foundation Award for Best Contribution from Statistics and Operations Research Using Data Science and Big Data for his work using AI to estimate war-related infrastructure damage. He has been featured on NPR’s Weekend Edition, Bloomberg, and The Economist.
He is the author of the forthcoming book AI-Proof Jobs: Future-Proof Your Career with Skills AI Can’t Replace and writes the newsletter Artificially Optimistic. Professor Hersh holds a Ph.D. in Economics from Boston University, and degrees from the University of Chicago and the Wharton School of the University of Pennsylvania. He teaches machine learning and data science courses to undergraduate and MBA students, and previously taught at MIT and Wellesley College.
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