AI and the Future of Work Conference

May 20–21, 2026
The Wharton School
Philadelphia, PA

Wharton Human-AI Research hosted AI and the Future of Work, a two-day academic conference focused on how AI is reshaping the nature of work and employment. The conference convened at The Wharton School, bringing together leading scholars, industry researchers, and practitioners to examine emerging research, share empirical insights, and engage in critical dialogue on the evolving relationship between AI, organizations, and the workforce.

— Presenters —

Please note that not all presenters have papers available to share.

David Almog
PhD Candidate, Kellogg School of Management
Barriers to AI Adoption: Image Concerns at Work

James Alvarez Mourey
Associate Professor of Marketing, Associate Dean of Graduate Programs, DePaul University
“The AI Acceptance Gap: Identity-Based Judgments of AI-Assisted Work”

Anirudh Bajaj
Product Manager, Microsoft
“What Every AI Job Study Gets Wrong: A Framework for Predicting How Much AI Will Actually Transform Each Occupation”

Matt Beane
Associate Professor, UC Santa Barbara
Hedging with Talent: How Selection Under Uncertainty Reshapes Automation’s Workforce Effects

Seth Gordon Benzell
Assistant Professor, Chapman University Argyros College of Business and Economics
Automation Experiments and Inequality

Anandhi Bharadwaj
Professor, Emory University
Pricing of Multidimensional Skills in the IT Labor Market: Complementarities between AI and Traditional IT Skills

Michael Blank
Assistant Professor of Finance, Stanford University
The Household Impact of Generative AI: Evidence from Internet Browsing Behavior

Tommaso Bondi
Assistant Professor of Marketing, Cornell University
Skill Atrophy and AI Productivity Measurement

Bharat Chandar
Postdoctoral Researcher, Stanford University
“AI and Labor Around the World”

Wei Chen
Associate Professor, University of Connecticut
“The Missing Middle: Workflow Design as the Key to Effective AI Agents”

Kanghyun (Simon) Cho
PhD Candidate, Temple University
“When Code Writes the Coder: The Delegation-Validation Trap in Vibe Coding”

Sahiba Chopra
PhD Candidate, UC Berkeley
“Effort Opacity”

Andrea Contigiani
Assistant Professor, Ohio State University
“Entrepreneurship, Experimentation, and Generative AI: Evidence from ChatGPT”

Chris Dellarocas
Richard C. Shipley Professor of Information Systems, Boston University
“Does AI Reduce Employer Reliance on Master’s Degrees? Evidence from Labor Market Flows”

Paramveer Dhillon
Associate Professor, University of Michigan
Readers Prefer Outputs of AI Trained on Copyrighted Books over Expert Human Writers

Sorour Fatemi
Visiting Assistant Professor, Cal State Monterey Bay College of Business
“Do Large Language Models Gamble Like Humans? Risk Preferences, Episodic Memory, and Demographic Stereotypes in LLM Decision-Making”

Alex Fogelson
Research Assistant, MIT FutureTech
“The Rapid Growth of AI Foundation Model Usage in Science”

Morgan Frank
Assistant Professor, University of Pittsburgh
AI-Exposed Jobs Deteriorated Before ChatGPT

Sanchaita Hazra
PhD Candidate, University of Utah
Accepted with Minor Revisions: Value of AI-Assisted Scientific Writing

Zezhen (Dawn) He
Postdoctoral Associate, Sloan School of Management, MIT
“Mental Models and Personalization of Model Selection”

David Holtz
Assistant Professor, Columbia Business School
“The Diffusion of ChatGPT Within Firms: Evidence from Enterprise Usage Data”

Moh Hosseinioun
Postdoctoral Fellow, Kellogg School of Management
“Reorganization of Work: Evidence from Software Firms”

Xinlan (Emily) Hu
Postdoctoral Associate, Massachusetts Institute of Technology
“Designing Optimal Human-AI Collaboration Processes for Complex Decision Tasks”

Ben Hyman
Economist, UCLA
How Retrainable Are AI-Exposed Workers?

Brian Jabarian
Marks Fellow and Incoming Assistant Professor at Carnegie Mellon University, University of Chicago Booth School of Business
“Choice as Signal: Designing AI Adoption in Labor Market Screening”

Xi Kang
Assistant Professor, Vanderbilt University
“Working Alongside Algorithms: How Parallel AI Deployment Affects Mutual Fund Analysts’ Performance”

Daniel Keum
Professor, Columbia Business School
Positional Technology: Organizational Hierarchy and Employee Engagement with AI and Automation

Samsun Knight
Assistant Professor, University of Toronto
The Effect of AI on Marketing Employment: Evidence from 90M+ Online Employment Records

Aakriti Kumar
Postdoctoral Researcher, Kellogg School of Management, Northwestern University
Practicing with Language Models Cultivates Human Empathic Communication

Kevin Lee
Assistant Professor of Marketing, University of Michigan, Ross School of Business
Agentic Interactions

Brandon Lepine
PhD Candidate, UC Santa Barbara
Precision Proactivity: Measuring Cognitive Load in Real-World AI-Assisted Work

Junjie Luo
PhD Student, School of Medicine, Johns Hopkins University
“Can Agentic AI Learn from Experimental Data to Design Superior Interventions? Evidence from Patient Messaging”

Dalbert Ma
PhD Student, London Business School
“The System-Level Cost of Algorithmic Coordination”

Zilin Ma
Postdoctoral Fellow, Harvard Business School
“Entrepreneurial Problem Choice: Measurement and the Effects of Artificial Intelligence”

Benjamin Manning
PhD Candidate, Massachusetts Institute of Technology
“General Social Agents”

Cassandra Merritt
Postdoctoral Scholar, University of Notre Dame
Managers as Gatekeepers in the Age of AI

Leon Musolff
Assistant Professor, The Wharton School
Coding Agents: Adoption, Learning, and Productivity Effects

Jiarui (Jerry) Qian
PhD Candidate, University of Virginia
AI in the Lab: AlphaFold2’s Impacts on Human-Produced Knowledge

Adam Quinn
Postdoctoral Associate, Science History Institute
“The Past and Future of Digital Automation: AI’s Labor Impacts in Historical Context”

Neel Rakholia
Data Scientist, OpenAI
“The Diffusion of ChatGPT Within Firms: Evidence from Enterprise Usage Data”

Raphael Raux
Postdoctoral Associate, MIT Sloan
Human Learning About AI

Peyman Shahidi
PhD Candidate, Massachusetts Institute of Technology
Chaining Tasks, Redefining Work: A Theory of AI Automation

Neha Sharma
Assistant Professor, University of Pennsylvania
Generative AI Shifts Technical Knowledge Production Toward Recombinant Novelty

Fangchen Song
PhD Candidate, The University of Texas at Austin
“AI and the Skill Gap: Evidence from a Large-Scale Field Experiment”

Koleman Strumpf
Professor of Economics, Wake Forest University
How AI Reshapes Human Content Creation: The Case of Wikipedia

K. Sudhir
Professor, Yale School of Management
The Production-to-Orchestration Shift: How Generative AI Reorganizes Knowledge Work

Michelle Vaccaro
PhD Candidate, Massachusetts Institute of Technology
“Advancing AI Negotiations: A Large-Scale Autonomous Negotiation Competition”

Lei Wang
Assistant Professor, Indiana University Bloomington
When AI Supports Emotionally Demanding Service Work: Experimental Evidence from Customer Service Interactions

Qi Wang
Postdoctoral Associate, Questrom School of Business, Boston University
“When Does Clinical AI Substitute for Experience? AI Exposure, Medical Reasoning, and Workforce Flows in U.S. Hospitals”

Xiupeng Wang
Assistant Teaching Professor, D’Amore-McKim School of Business, Northeastern University
AI’s Job Shakeup: Analyzing the Uneven Impact of AI Adoption on Labor Demand

Zachary Wojtowicz
Postdoctoral Fellow, MIT
“Artificial Intelligence and the Reorganization of Work: Evidence from Software Firms”

Xingqi (Maggie) Ye
PhD Candidate, UC Berkeley
“Addicted to AI: How Generative AI Leads to Voluntary Work Intensification”

Alev Yildirim
Assistant Professor, Queens College, CUNY
“Organizational Exposure to Generative AI and Its Impact on Employee Satisfaction”

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