Abstract The campus ombuds occupies a distinct niche in the dispute resolution landscape—confidential, informal, independent, and neutral—yet the American higher-education version of the role was built on a structural flaw present from its inception. This article traces the ombuds concept from its Swedish origins as an instrument of parliamentary oversight to its adoption on American campuses amid the crises of the late 1960s, showing how Eastern Montana College's 1966 template, in which the ombuds answered to the president it might criticize, was copied without scrutiny in a pattern of mimetic isomorphism that made structural vulnerability endemic to the profession. Warnings from early scholars and stronger models proposed at Princeton and elsewhere went unheeded. As the campus crises that prompted adoption receded, the unprotected function experienced marginalization and closure. Drawing on contracts and correspondence obtained through public-records requests, the article examines the recent rise of outsourced ombuds services—including arrangements at Iowa State, MSU Denver, UMass Amherst, and UC Berkeley—as an existential threat that exploits this inherited vulnerability, substituting a commercially convenient simulacrum for genuine institutional commitment and endangering the populations least able to surface concerns through formal channels.
Abstract Negotiation theory and practice have long been guided by the assumption that negotiators should seek the best possible outcome, whether through value claiming, value creation, or long-term relational optimization. Yet negotiators often stop short of what they could attain. Such behavior is typically interpreted as the result of cognitive bias, inexperience, or strategic failure and therefore viewed as inefficient. We argue that negotiators may instead follow a logic of sufficiency rather than maximization, seeking outcomes that are good enough and ceasing further value pursuit once that threshold is reached. Drawing on philosophical debates about sufficientarianism, reasonable contentment, and the meaning of “enough,” we develop sufficiency as a distinct orientation in negotiation. We introduce the sufficiency point as a multidimensional stopping criterion and distinguish it from reservation and aspiration points. We further show how sufficiency can alter negotiation dynamics, stakeholder effects, and the evaluation of Pareto efficiency. From this perspective, value left on the table is not necessarily a sign of failure but may reflect a deliberate judgment that further gains are neither necessary nor worth pursuing. Finally, we argue that sufficiency invites a reconsideration of rationality in negotiation by showing that maximization within a given decision frame need not be pursued once an outcome is judged sufficient.
When Robert Axelrod organized his 1979 tournament of repeated Prisoner's Dilemma strategies, few anticipated that the winning approach would be so simple or "nice": Tit-for-Tat, a strategy built on cooperation rather than aggression, outperformed far more sophisticated rivals, a result that reshaped thinking across economics, political science, and evolutionary biology. By creating a common arena in which diverse strategies could compete against each other, Axelrod's competition also showed that bottom-up discovery through structured comparison could surface findings that deductive theory alone may not anticipate. Four decades later, artificial intelligence (AI) has transformed what this method can do by expanding the scale, complexity, and realism with which negotiation strategies can be systematically compared. The Program on Negotiation (PON) AI Negotiation Summit showcased three such competitions-the Massachusetts Institute of Technology (MIT) AI Negotiation Competition, the Melting Pot and Concordia Contests, and the Automated Negotiating Agent Competition (ANAC)-each designed around distinct assumptions about environment structure, agent architecture, and evaluation criteria. Taken together, they demonstrate that negotiation competitions are powerful tools for generating discovery at scale, benchmarking strategies across multiple criteria, and advancing the science of negotiation.
Emerging advances in artificial intelligence-especially large language models-raise the prospect of AI systems acting as full participants in negotiation rather than merely supporting tools. This article surveys the evolution of automated negotiators and mediators and outlines three foundational design choices that shape their effectiveness, and indeed, how "effectiveness" is defined: whether systems should follow rational decision-making or mirror human relational and emotional behavior; whether people should delegate negotiation to autonomous agents or participate in the negotiation process; and how systems should balance self-interest with joint gains. Although these choices were once treated as dichotomous, recent systems increasingly integrate elements of each. These developments aim to align strategic decision-making with relational communication in ways that human counterparts judge as procedurally fair. The article illustrates these trends through four contributions presented at the 2025 AI Negotiation Summit at MIT, hosted by the Program on Negotiation at Harvard Law School.
Artificial intelligence has already begun to transform negotiation research, teaching, coaching, mediation, competition, and practice. Much of this progress has occurred in what Joel Leibo, drawing on Leonard Savage's distinction, characterized as "small-world" settings: relatively well-specified environments in which payoffs, rules, parties, issues, and evaluation criteria can be sufficiently enumerated to permit precise modeling, simulation, coding, benchmarking, or optimization. These advances are real and important. AI systems can analyze transcripts, support deliberate practice, generate and evaluate negotiation strategies, facilitate structured dialogue, and permit systematic comparison among competing approaches at scales previously unimaginable. By contrast, "larger-world" negotiations are characterized by less well-defined or less-fully-specified versions of these tasks.Yet for negotiation, the small-world / large-world continuum carries a further strategic implication. The most important frontier for AI and negotiation lies not only in building systems that make better moves within relatively fixed "games." Rather, this wider frontier for AI consists of building systems that help negotiators decide whether the apparent game should be accepted as fixed or be structurally changed in favorable ways by participants or interested third parties who would benefit thereby. Many consequential negotiations unfold toward the larger-world end of this continuum, where the parties, interests, issues, Best Alternatives to Negotiated Agreements ("BATNAs"), action sequences, and process choices are uncertain, dynamic, and subject to purposive change by what we might call "entrepreneurial negotiators." In these settings, the central challenge is not simply optimization within a well-defined structure, but judgment about the conditions in which the actual and potential structure itself may need to be discovered, challenged, or redesigned in favorable ways. The next stage of AI-and-negotiation work should be what Raiffa calls "asymmetrically prescriptive." This means generating optimal advice "against" either 1) known negotiating counterpart(s) or 2) careful descriptions of "nature" as if it were an impersonal other side. Ideally, this prescriptive advice should be theoretically and empirically grounded, practically oriented, and designed to assist human negotiators as they diagnose and shape the game advantageously . Properly guided, AI can help negotiators think strategically and act opportunistically in the face of uncertainty, complexity, and evolving possibilities. Poorly guided, AI may compress negotiation toward largely irrelevant averages, reproduce biases, overfit to narrow scenarios, and/or encourage premature confidence in badly specified games. The task before scholars and practitioners is therefore not merely to ask whether AI can negotiate, but whether AI can help human beings negotiate more wisely when the negotiation itself may not yet have been fully imagined and specified.
In March 2025 the Program on Negotiation at Harvard Law School hosted a two-day summit at MIT on AI and negotiation. One panel at the summit explored several approaches to designing and using AI as a teacher. This article discusses the papers presented on that panel.The summit made clear that AI already has transformed how negotiation is studied, taught, and practiced-by enhancing preparation, encouraging deeper analysis, facilitating consensus-building, enhancing training access, and offering real-time coaching. Each of these developments offers both opportunities and pitfalls. When designing negotiation courses or training programs, instructors must make a number of pedagogical choices: What readings will students be assigned? What learning points will instructors cover in lectures and in-class conversation? What in-class exercises or role-play simulations will be assigned? What kinds of written reflections should instructors ask students to submit following each role-play? What prescriptive lessons do instructors want students to draw from role-plays and debriefings? In this article, the author offers answers to all these questions, especially in regard to the pros and cons of using GenAI assistance of various kinds.
Artificial intelligence is increasingly embedded in the practice, study, and teaching of negotiation, creating the need for a clear conceptual vocabulary for this emerging field. In this article, we propose a spatial and functional framework, identifying four primary roles AI may occupy in negotiation: as agent in front of the negotiator, as coach beside the negotiator, as backtable support behind the negotiator, and as mediator or facilitator between the parties. We also identify three broader domains in which AI is transforming the negotiation field: teaching, research, and real-world implementation. Although these categories are analytically distinct, they often overlap in practice, especially in field settings where multiple AI functions are integrated within the same system. By organizing these roles and domains within a single framework, we seek to clarify how AI is revolutionizing negotiation, and how its various applications relate to one another.The significance of AI in negotiation lies not only in what these systems can do, but in how they are designed and positioned relative to human judgment, institutional context, and the conduct of negotiation itself. Drawing on the contributions in this special issue, we examine how AI is reshaping processes, expanding access to training, reorienting empirical research, and supporting practitioners in complex environments. At the same time, these developments raise enduring questions about delegation, transparency, equity, accountability, and the preservation of human judgment. We argue that the most promising trajectory for AI in negotiation is one of complementarity: systems designed to augment human capabilities, preserve meaningful human involvement, and strengthen negotiation practice rather than displace the human capacities that give it meaning. By clarifying roles and articulating normative principles for design and use, this framework offers both an analytic foundation for the field and guidance for its responsible development.
This article discusses the projects presented on the "AI in the Field" panel at the March 2025 AI Negotiation Summit. The projects addressed distinct domains of social conflict: family caregiving, humanitarian frontline negotiations, and democratic deliberation. In contrast to current discourse surrounding autonomous "AI agents" intended to replace human roles, the research presented in this panel explicitly focused on human-AI collaboration. Across all three studies, participants engaged productively with AI systems designed to support decision-making and conflict management. The deliberative democracy project showed that AI-supported deliberation could promote opinion change and movement toward common ground on some divisive sociopolitical issues. The frontline negotiators study demonstrated that a structured AI system improved efficiency compared with negotiators self-prompting ChatGPT; its interactive interface enabled users to pose questions, generate multiple options, and assess risks across several dimensions, supporting deeper analysis and counterfactual reasoning. The caregivers study showed evidence of learning, behavioral change, and use in social conflict beyond the training context. Each project also addressed the risk of negative social consequences associated with AI systems by using multidisciplinary teams, grounding interventions in established theory, conducting extensive formative research, and maintaining human oversight of system behavior. Together, the studies provide proof-of-concept evidence that carefully designed AI systems can enhance human capacity to address social conflict while preserving human judgment and minimizing the risks of human dependency and unintended social harm.
Artificial intelligence promises to reshape negotiation education, not by replacing human judgment but by augmenting it. While research on automated coaching varies on many dimensions, a salient axis is temporal-whether the coaching occurs before, during, or after the negotiation of a focal deal. This temporal taxonomy also serves to elucidate differences between the projects presented at the AI Negotiation Summit in March 2025. These projects drew on AI for providing pertinent legal information, prompting negotiation strategies, interpreting negotiation agreements, and identifying tactical missed opportunities. Potentially AI coaching could widen access to negotiation training for many populations that could benefit from it. Yet it also raises questions about authenticity, bias, and ethics. Drawing analogies to autonomous driving technology, we argue that the optimal uses of AI coaching lie in complementarity: AI coaching should expand human capacity for rigorous preparation, active perspective taking, and creative problem-solving-while leaving voice, agency, and responsibility where they belong: with human negotiators. We argue that it can also level the playing field in extending educational access to less privileged populations.
This article explores ways in which AI tools can help negotiation scholars do their research, drawing on presentations delivered by Ray Friedman, Emily Hu, Gale Lucas, and Zhivar Sourati at the AI Negotiation Summit at MIT. AI can be used to automate transcript coding, applying negotiation-specific (e.g., "substantiation") or general language (e.g,. "politeness" or "turn taking") codes. AI can be trained to act as confederates in negotiation studies, providing human-like language patterns with high levels of consistency for experimental control, and there is potential for AI to act as subjects in negotiation studies. In these ways AI can help scholars conduct research more efficiently and effectively. However, there are still great challenges, such as the inability of AI to produce human-like behavior.
The contexts in which we at the Centre on Conflict & Collaboration and our students work are marked by chronic sociopolitical tensions between citizens and authorities and identity groups with each other. They are characterized by overwhelmed institutions and ongoing contestation with respect to authority, legitimacy, and even the appropriate use of violence. Thus, "getting to yes" in the workplace, community, or civic space is not only harder, with higher stakes; it is frequently undermined by prevailing systems dynamics. To better serve those working to facilitate positive change, we have advanced a framework for understanding and action to address the challenges of collaborative solution generation in such tumultuous and conflictual places. While readily recognizable to those familiar with interest-based problem-solving, the framework is distinctive in its recognition of the inevitable influence of negative systems dynamics and its positioning of even mundane negotiations as iterative exercises in broader world building. It thus situates every collaborative endeavor within the broader web of societal relations; invites negotiators to worry less about their agreement and more about the challenges of positive progress within contested spaces; and reflects an understanding of every negotiation process as consensus-based institution building. This repositions our collaborative engagement as the building of a coalition committed to the exercise of non-dominating power. This is the story of how we came to understand the need for such a pedagogical framework, what it looks like, our experience with it, and our hopes for it.
Green mega-infrastructure projects are increasingly central to the global green energy transition. Yet they often generate conflict when stakeholder engagement fails to address underlying issues of identity, recognition, and belonging. These dynamics unfold against a backdrop of institutional logics that prioritize efficiency, planning authority, and investment security. This article re-examines stakeholder engagement through the lens of negotiation theory, arguing that existing frameworks often remain conflict-blind and reduce identity to procedural categories. Drawing on Rothman’s ARIA framework, it extends the logic of interest-based negotiation by introducing a relational, identity-sensitive approach to conflict in green mega-infrastructure project governance. Accordingly, the article advances the concept of identity narratives—dynamic and relational storylines through which actors, communities, and developers alike articulate identity claims of belonging, legitimacy, and recognition in conflict. It integrates this typology within the ARIA framework by structuring antagonism, resonance, invention, and action around contested identities to promote a more recognition-sensitive approach to stakeholder engagement.
Based on seven in-depth country studies, this article explores the nature and challenges of business-community negotiations in the mining sector of Latin America and identifies a common set of institutional, organizational, and structural barriers to conflict resolution that render mutual gains approaches to negotiations rare and difficult to implement. These barriers include a weak rule of law; inequalities in access to justice; power asymmetries; incentives for short-term distributive negotiations rather than long-term value-creating agreements; and deep value differences, all of which feed into zero-sum dynamics in business-community-and even intracommunity-negotiations. Based on a normative-theoretical discussion of the implications of our findings, the article recommends integrating a rights-based approach with inclusive dialogue-based practices in ways that curb the institutional barriers that we identify and may generate incentives for long-term value-creating negotiations between business and communities, as well as sustainable use of natural resources.
Social innovations are at risk at a time when surprise is employed as a unilateral government strategy in order to shrink and refocus government operations. Social innovations involve collective efforts, frequently spanning public and private stakeholders. The needed trust and reciprocal understandings are undercut when government employs the logic of reengineering combined with surprise as a strategy-what we term "Surprise by Design." This contrasts with past federal restructuring initiatives that employed a mix of administrative expertise (top down) and frontline continuous improvement (bottom up) as strategies for negotiated changes. Surprise is a particular type of top-down imposed change, which disrupts patterned roles and routines in order to impose a reconceptualization of how government will function in society. This article documents surprise as a change strategy and identifies needed adjustments to two relevant lateral models for negotiated change. By taking this into account, social innovation initiatives can be more resilient in the face of Surprise by Design.
This article theorizes when and why governments negotiate peace with pro-government militias (PGMs) or "pro-state" paramilitary groups. I argue that negotiations with PGMs are more likely to occur when PGM activities become costly and when domestic and international pressure to account for PGM violence mounts on both sides. While governments support (even if tacitly) PGMs for short-term advantages in counterinsurgency, PGMs often pursue their own agendas and can end up harming state interests, resulting in a shift from support to curtailing PGM activity. I build this argument drawing on examples from around the world and providing initial evidence from the Colombian government's negotiated agreements with the Autodefensas Unidas de Colombia (AUC) in Santa Fe de Ralito in 2003-2005.
In business-to-business environments characterized by uncertainty and interdependence, much of what shapes negotiation outcomes occurs beyond the formal table. Building on the concept of latent negotiations, understood as informal interaction episodes in which negotiation-relevant issues are addressed without explicit framing as negotiation, this study examines the contextual and perceptual conditions that enable such dynamics to emerge. Combining expert interviews with a conjoint analysis among negotiation practitioners, the findings show that face-to-face, one-to-one exchanges embedded in ongoing relationships and involving indirect issue framing are perceived as most conducive, whereas written communication and asymmetric constellations are perceived as less conducive. At the same time, the empirical results indicate that latent negotiations can arise in a range of other interactional forms, underscoring the need to remain attentive to contextual cues in everyday exchanges. The study contributes to negotiation research by conceptualizing negotiation as a continuum of interactions shaped by perception, context, and relational framing.
In this practitioner-focused article, the authors take a close look at Chris Voss's book Never Split the Difference, especially exploring its application to non-hostage negotiations in both the political and business worlds. They conclude that many of the Vossian precepts are difficult to transfer to an environment with structural long-term mutual dependency. They note an ongoing need to create value beyond what is on the table and offer a reinterpretation of BATNA aimed at improving one's slice of the pie by redesigning relationships, while doing full justice to the importance of dependencies, ethics, and value creation in a win-win oriented collaboration.
This article investigates the negotiation process initiated by the establishment of a Special Commission within the Belgian Parliament in 2020, tasked with addressing the country's colonial past. Based on two and a half years of fieldwork conducted within the Commission, the article traces how extensive negotiations, hearings, and meetings-both national and international-led to the signature of an ambitious pre-agreement, before the process ultimately collapsed in a complete and wholly unexpected failure. The analysis underscores how Belgium's deeply rooted societal cleavages-left/right, Francophone/Dutch-speaking, Catholic/secular, monarchist/republican-shaped the process into a distributive and highly emotional conflict.
