About

Jared R. Curhan is the Gordon Kaufman Professor of Management and a Professor of Work and Organization Studies at the MIT Sloan School of Management. He specializes in the psychology of negotiation and conflict resolution, with a focus on the feelings and judgments concerning the instrumental outcome, the process, the self, and the relationship in negotiation settings. Curhan has pioneered a social psychological approach to the study of 'subjective value' in negotiation, utilizing the Subjective Value Inventory (SVI) to examine the precursors, processes, and long-term consequences of subjective value. His research also explores the role of artificial intelligence in negotiation and creativity. He is the Faculty Director of MIT’s Behavioral Research Lab and serves as Vice Chair for Research and a member of the Executive Committee of the Program on Negotiation at Harvard Law School. Curhan founded the Program for Young Negotiators, Inc., which promotes negotiation training in primary and secondary schools, and authored the book 'Young Negotiators.' He has received multiple awards for his teaching excellence, including the MIT Teaching with Technology Award and the MIT Sloan Jamieson Prize. His educational background includes an AB in psychology from Harvard University and an MS and PhD in psychology from Stanford University.

Research topics

• Sociology
• Social Science
• Political Science
• Psychology
• Social psychology
• Computer Science
• Law
• Artificial Intelligence
• Epistemology
• Business
• Aesthetics
• Marketing
• Philosophy

Selected publications

• Personality Engineering with AI Agents: A New Methodology for Negotiation Research

  ArXiv.org · 2026-05-19

  articleOpen accessSenior author

  According to canonical negotiation theory, people's success in a negotiation depends on how well they balance competing demands--empathizing and asserting, demonstrating concern for other and concern for self, being soft on the people and hard on the problem. Yet people struggle to manage these tensions, so researchers have lacked the ability to rigorously test the field's prescriptions under controlled conditions. AI agents do not face the same limitations, and their precision, repertoire, consistency, and scalability enable a new class of experiments to contribute to negotiation theory. In this article, we introduce personality engineering: a methodology that uses AI agents to precisely parameterize, manipulate, and evaluate negotiator personality. We propose using the interpersonal circumplex--and its two core dimensions of warmth and dominance--as a foundational coordinate system for the field. This approach offers both a rigorous methodology for testing classic negotiation theories and a practical guide for designing the personalities of AI negotiation agents.

  PublisherOA PDF

• Personality Engineering with AI Agents: A New Methodology for Negotiation Research

  arXiv (Cornell University) · 2026-05-19

  preprintOpen accessSenior author

  According to canonical negotiation theory, people's success in a negotiation depends on how well they balance competing demands--empathizing and asserting, demonstrating concern for other and concern for self, being soft on the people and hard on the problem. Yet people struggle to manage these tensions, so researchers have lacked the ability to rigorously test the field's prescriptions under controlled conditions. AI agents do not face the same limitations, and their precision, repertoire, consistency, and scalability enable a new class of experiments to contribute to negotiation theory. In this article, we introduce personality engineering: a methodology that uses AI agents to precisely parameterize, manipulate, and evaluate negotiator personality. We propose using the interpersonal circumplex--and its two core dimensions of warmth and dominance--as a foundational coordinate system for the field. This approach offers both a rigorous methodology for testing classic negotiation theories and a practical guide for designing the personalities of AI negotiation agents.

  PublisherDOI

• Advancing AI Negotiations: New Theory and Evidence from a Large-Scale Autonomous Negotiations Competition

  SSRN Electronic Journal · 2025-01-01 · 4 citations

  preprintOpen accessSenior author
  PublisherDOI

• Advancing AI Negotiations: New Theory and Evidence from a Large-Scale Autonomous Negotiations Competition

  2025-07-09 · 1 citations

  preprintOpen accessSenior author

  We conducted an International AI Negotiation Competition in which participants designed and refined prompts for AI negotiation agents. We then facilitated over 180,000 negotiations between these agents across multiple scenarios with diverse characteristics and objectives. Our findings revealed that principles from human negotiation theory remain crucial even in AI-AI contexts. Surprisingly, warmth—a traditionally human relationship-building trait—was consistently associated with superior outcomes across all key performance metrics. Dominant agents, meanwhile, were especially effective at claiming value. Our analysis also revealed unique dynamics in AI-AI negotiations not fully explained by existing theory, including AI-specific technical strategies like chain-of-thought reasoning, prompt injection, and strategic concealment. When we applied natural language processing (NLP) methods to the full transcripts of all negotiations we found positivity, gratitude and question-asking (associated with warmth) were strongly associated with reaching deals as well as objective and subjective value, whereas conversation lengths (associated with dominance) were strongly associated with impasses. The results suggest the need to establish a new theory of AI negotiation, which integrates classic negotiation theory with AI-specific negotiation theories to better understand autonomous negotiations and optimize agent performance.

  PublisherDOI

• Advancing AI Negotiations: New Theory and Evidence from a Large-Scale Autonomous Negotiations Competition

  2025-03-11 · 1 citations

  preprintOpen accessSenior author

  We conducted an International AI Negotiation Competition in which participants designed and refined prompts for AI negotiation agents. We then facilitated over 180,000 negotiations between these agents across multiple scenarios with diverse characteristics and objectives. Our findings revealed that principles from human negotiation theory remain crucial even in AI-AI contexts. Surprisingly, warmth—a traditionally human relationship-building trait—was consistently associated with superior outcomes across all key performance metrics. Dominant agents, meanwhile, were especially effective at claiming value. Our analysis also revealed unique dynamics in AI-AI negotiations not fully explained by existing theory, including AI-specific technical strategies like chain-of-thought reasoning, prompt injection, and strategic concealment. When we applied natural language processing (NLP) methods to the full transcripts of all negotiations we found positivity, gratitude and question-asking (associated with warmth) were strongly associated with reaching deals as well as objective and subjective value, whereas conversation lengths (associated with dominance) were strongly associated with impasses. The results suggest the need to establish a new theory of AI negotiation, which integrates classic negotiation theory with AI-specific negotiation theories to better understand autonomous negotiations and optimize agent performance.

  PublisherOA PDFDOI

• Relational and Economic Outcomes in Negotiation

  Academy of Management Proceedings · 2025-07-01

  article

  Negotiation is a critical element of managerial and interpersonal interactions, shaping outcomes that extend beyond the immediate agreement to influence relationships, trust, and collaboration. This symposium focuses on the relational aspects of negotiations, examining how dynamics such as trust, reputation, and rapport affect negotiation strategies, outcomes, and long-term relationships. Across five papers, the presenters explore the nuanced ways in which relational factors influence negotiation behavior and outcomes. Together, these studies underscore the importance of prioritizing relational outcomes in negotiation theory and practice to achieve more equitable, sustainable, and effective agreements. This symposium offers valuable insights for scholars and practitioners seeking to enhance both relational and economic outcomes in negotiations.

  PublisherDOI

• Supermind Ideator: How Scaffolding Human-AI Collaboration Can Increase Creativity

  2024-06-27 · 23 citations

  articleOpen access

  Previous efforts to support creative problem-solving have included (a) techniques such as brainstorming and design thinking to stimulate creative ideas, and (b) software tools to record and share these ideas. Now, generative AI technologies can suggest new ideas that might never have occurred to the users, and users can then select from these ideas or use them to stimulate even more ideas. To explore these possibilities, we developed a system called Supermind Ideator that uses a large language model (LLM) and adds prompts, fine tuning, and a specialized user interface in order to help users reformulate their problem statements and generate possible solutions. This provides scaffolding to guide users through a set of creative problem-solving techniques, including some techniques specifically intended to help generate innovative ideas about designing groups of people and/or computers (“superminds”). In an experimental study, we found that people using Supermind Ideator generated significantly more innovative ideas than those generated by people using ChatGPT or people working alone. Thus our results suggest that the benefits of using LLMs for creative problem-solving can be substantially enhanced by scaffolding designed specifically for this purpose.

  PublisherDOI

• Supermind Ideator: How scaffolding Human-AI collaboration can increase creativity

  Collective Intelligence · 2024-10-01 · 7 citations

  articleOpen access

  Previous efforts to support creative problem-solving have included (a) techniques such as brainstorming and design thinking to stimulate creative ideas, and (b) software tools to record and share these ideas. Now, generative AI technologies can suggest new ideas that might never have occurred to the users, and users can then select from these ideas or use them to stimulate even more ideas. To explore these possibilities, we developed a system called Supermind Ideator that uses a large language model (LLM) and adds prompts, fine tuning, and a specialized user interface in order to help users reformulate their problem statements and generate possible solutions. This provides scaffolding to guide users through a set of creative problem-solving techniques, including some techniques specifically intended to help generate innovative ideas about designing groups of people and/or computers (“superminds”). In an experimental study, we found that people using Supermind Ideator generated significantly more innovative ideas than those generated by people using ChatGPT or people working alone. Thus our results suggest that the benefits of using LLMs for creative problem-solving can be substantially enhanced by scaffolding designed specifically for this purpose.

  PublisherDOI

• Humans + AI: Organizational Behavior Research on Human-Machine Interactions

  Academy of Management Proceedings · 2024-07-09

  article

  The new era of industry 4.0 has empowered organizations to revolutionize the workplace through artificial intelligence (AI). As AI becomes more ubiquitous and ingrained in both organizational and daily life, new questions arise about the dynamics of human-AI interactions and its implications for management and society. The current symposium seeks to shed light on critical aspects of these AI-driven changes, taking a focused perspective on research at the intersection of technology and organizational behavior. The five papers featured in this symposium delve into the multifaceted and complex nature of human-AI interactions, collectively exploring how people navigate and develop relationships with AI systems. The papers investigate influential topics such as ethical beliefs and considerations toward AI, the impact of AI on individual attitudes and behaviors, and the evolution of human-AI partnerships within organizations. Together, the papers contribute to the growing body of knowledge on AI and human behavior, offering new insights into the challenges and opportunities that arise as people work in an increasingly artificial workplace. Is AI Capable of Autonomous Ethical Decision-Making? It Depends on Whether You Think Like an Engine Author: Mahak Nagpal; U. of St. Thomas Author: David De Cremer; Northeastern U., D'Amore-McKim School of Business Author: Alain Van Hiel; Ghent U. Author: Shane Schweitzer; Northeastern U., D'Amore-McKim School of Business Artificial Intelligence Promotes Ethical Fading in Negotiation Author: Amanda Plummer Weirup; Babson College Author: Lily Morse; U. of Denver Author: McKenzie Rees; Brigham Young U. Smooth-Talking Bots: AI Negotiators Make Better Impressions Author: David Fang; Stanford U. Author: Mohammed Alsobay; MIT Sloan School of Management Author: Abdullah Almaatouq; Massachusetts Institute of Technology Author: Jared R. Curhan; MIT Sloan School of Management The Diverging Disparity Effect in Socially Interactive Artificial Intelligence: An Emotional Perspec Author: Mehran Bahmani; Schulich School of Business, York U. Author: Laura Rees; Oregon State U. Commitment Issues: Platform and Job Design in Algorithmically Managed Contexts Author: Allen Brown; Carnegie Mellon U. - Tepper School of Business Author: Christopher Dishop; Carnegie Mellon U. - Tepper School of Business Author: Andrew Kuznetsov; Carnegie Mellon U. Author: Ping-Ya Chao; Carnegie Mellon U. Author: Anita Williams Woolley; Carnegie Mellon U.

  PublisherDOI

• New Directions for the Study of Gender and Identity in Negotiation Interactions

  Academy of Management Proceedings · 2023-07-24

  article

  Gender issues have long been a prominent topic in negotiation research and decades of research have established foundational knowledge of how gender shapes negotiation outcomes (Bowles et al., 2022). However, the scholarly understanding of gender effects in negotiation is far from complete. In this symposium, we present five projects that point to new research directions by (1) incorporating non-western samples and examining cultural influences, (2) moving beyond the gender binary and exploring intersectionality issues, and (3) proposing new research methodologies and paradigms. Damned If You Are Culturally Ideal: Backlash against Relational Women among Chinese Negotiators Author: Wen Shan; Singapore U. of Social Sciences Author: Josh Keller; UNSW Sydney Author: Shira Mor; Mona Lisa Consulting Author: Zhaleh Semnani-Azad; California State U., Northridge The Interplay of Gender and Perceived Sexual Orientation at the Bargaining Table Author: Sreedhari Desai; U. of North Carolina Author: Brian Gunia; Johns Hopkins U. Beyond the Binary: Anticipating Negotiations with Genderqueer Partners Author: Negin Toosi; California State U., East Bay Author: Katrina Gardner; California State U., East Bay How Gender and Status Shape Informal Negotiations Author: Ashley Whillans; Harvard Business School Author: Hannah Riley Bowles; Harvard U. Unpacking Gender Differences in Negotiation: Distinguishing Actor and Partner Effects Author: Jared R. Curhan; MIT Sloan School of Management Author: Bushra Sarah Guenoun; Harvard Business School

  PublisherDOI

Recent grants

• Consequences of Subjective Value in Negotiations

  NSF · $197k · 2006–2010

Frequent coauthors

• Hillary Anger Elfenbein

  Washington University in St. Louis

  19 shared

• Noah Eisenkraft

  Duke University

  11 shared

• Ashley D. Brown

  10 shared

• Max H. Bazerman

  9 shared

• Kathleen L. Valley

  9 shared

• Don A. Moore

  9 shared

• Lee Ross

  6 shared

• Aiwa Shirako

  New York University

  5 shared

Labs

• Behavioral Research LabPI

Awards & honors

• 2019 Teaching with Digital Technology Award from MIT