
On March 8 and 9, 2025, the Program on Negotiation (PON) convened leading practitioners and scholars on artificial intelligence (AI) and negotiation to present their cutting-edge research and discuss innovations in the field. The summit was also the culmination of a student AI negotiation bot competition, held by MIT. Chaired by Jared Curhan and Jonathan Gratch, the AI negotiation summit included panels on AI as a researcher, negotiator or mediator, coach, teacher, and uses of AI in the field. To check out full videos of all the summit panels, click here.
You can also read the research abstracts on AI negotiation presented at the summit. The presenters were:
AI Negotiation Competitions
Panel Leader: Jared Curhan (MIT)
- The MIT AI Negotiation Competition
Jared Curhan, Massachusetts Institute of Technology - The Melting Pot Contest
Joel Leibo, Google DeepMind and Kings College - The Automated Negotiating Agents Competition
Jonathan Mell, University of Central Florida - Discussant
Robert Axelrod, University of Michigan
AI as a Researcher
Panel Leader: Ray Friedman (Vanderbilt)
- Developing a Large Language Model for Coding Negotiation Transcripts
Ray Friedman, Vanderbilt University - AI as Explorer: Quantifying Conversations with Natural Language Processing
Emily Hu, University of Pennsylvania - Let’s Negotiate! Using AI as a Partner in Negotiation Research
Gale Lucas, University of Southern California - LLMs and the Erosion of Human Variance
Zhivar Sourati, University of Southern California
AI as a Negotiator and Mediator
Panel Leader: Jonathan Gratch (USC)
- A Brief History of AI Negotiators
Jonathan Gratch, University of Southern California - Smooth-Talking Bots: AI Negotiators Make Better Impressions
Michelle Vaccaro, Massachusetts Institute of Technology - What We Learned from Teaching AI to Negotiate
Mike Lewis, Meta AI Research - Opportunities and Challenges in AI Mediators
Min Kyung Lee, University of Texas – Austin
AI as a Coach
Panel Leader: Michael Morris (Columbia)
- ACE: A LLM-Based Negotiation Coaching System
Michael Morris, Columbia University - Does AI Coaching Improve Negotiation Outcomes? Evaluating Warmth, Dominance, and Individual Traits in Negotiation
Harang Ju, Massachusetts Institute of Technology - AI Knows a Deal When It Sees One
Peter Carnevale, University of Southern California - AI as the Fourth Party in Empowering Self-Represented Litigants
Amy Schmitz, The Ohio State University
AI as a Teacher
Panel Leader: Lawrence Susskind (MIT)
- The Negotiation Skills Assessment: Developing and Validating an AI-Powered Measure of Negotiation Proficiency
Laura Wang, Massachusetts Institute of Technology - Virtual Agents for Personalized Negotiation Training
Emmanuel Dorley, University of Florida - Negotiation Coaching Bots and Backtable Bots: Using GenAI to Improve Human-to-Human Interactions in Multiparty Negotiation Instruction
Samuel “Mooly” Dinnar, Massachusetts Institute of Technology
AI in the Field
Panel Leader: Jeanne Brett (Northwestern)
- NegotiAge: Teaching Caregivers to Negotiate Conflict
Jeanne Brett, Northwestern University - “ChatGPT, Don’t Tell Me What to Do”: Designing AI for Context Analysis in Humanitarian Frontline Negotiations
Zilin Ma, Harvard University - The Habermas Machine: AI Can Help Humans Find Common Ground in Democratic Deliberation
Michiel Bakker, Massachusetts Institute of Technology
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TNRC negotiation exercises and teaching materials are designed for educational purposes. They are used in college classroom settings or corporate training settings; used by mediators and facilitators seeking to introduce their clients to a process or issue; and used by individuals who want to enhance their negotiation skills and knowledge.
Negotiation exercises and role-play simulations introduce participants to new negotiation and dispute resolution tools, techniques and strategies. Our videos, books, case studies, and periodicals are also a helpful way of introducing students to key concepts while addressing the theory and practice of negotiation.
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