From June 10 to 13, 2026, Michael Fang, a Fellow of the National Center for Technology and Dispute Resolution (NCTDR), participated in a series of academic and professional events on artificial intelligence and online dispute resolution (ODR) in Cambridge and Boston, Massachusetts. These included the 2026 International Forum on Online Dispute Resolution at Harvard University, followed by the conference Arbitration and Mediation in the Age of AI and the VibeODR Hackathon at Suffolk University Law School. Researchers, judges, arbitrators, mediators, lawyers, legal technology specialists, and ODR platform developers from more than thirty countries participated.

The events showed that artificial intelligence is no longer merely a tool for improving legal efficiency. It is changing how legal services are delivered, how disputes are prevented and resolved, and how law schools prepare students for practice. During the series, Fang delivered a presentation at the Harvard ODR Forum and exchanged views with faculty members, dispute resolution professionals, and legal technology practitioners. Drawing on these firsthand observations, this article examines how AI is reshaping legal education and the competencies law firms increasingly seek in law graduates.

On June 11, the annual ODR Forum was held at Harvard University. The event was organized by NCTDR, with the Program on Negotiation at Harvard Law School (PON) participating in the opening session. Nicole Bryant, Executive Director of PON, welcomed the participants and thanked Colin Rule for his central contribution to organizing the forum.

Nicole Bryant’s acknowledgment of Colin Rule also carried broader symbolic significance. It can be understood as recognizing the work of NCTDR and the wider ODR community in advancing ODR across e-commerce, courts, and dispute resolution institutions. It also signaled ODR’s growing influence as the field enters a new stage shaped by artificial intelligence. The forum’s location at Harvard and PON’s participation further indicated that AI and ODR have entered the agenda of leading institutions concerned with dispute resolution and legal education.

Bryant explained that PON has a forty-three-year history and a structure covering research, teaching, publication, and emerging-scholar development. It has a fourteen-member executive committee and approximately seventy affiliated faculty members. It promotes scholarship through Negotiation Journal, develops teaching materials through the Teaching Negotiation Resource Center, and supports doctoral students and younger scholars through fellowships and other research opportunities.

PON also works across institutional and disciplinary boundaries. Although based at Harvard Law School, it maintains connections with other Harvard schools, MIT, Tufts University, and the broader Greater Boston academic community. MIT Professor Larry Susskind serves as PON’s Vice Chair for Instruction and contributes to its teaching resources. This network allows negotiation and dispute resolution research to connect with public policy, organizational decision-making, technology, and social governance.

Artificial intelligence is becoming part of this network. Bryant noted that PON held an Artificial Intelligence and Negotiation Summit at MIT in 2025, co-chaired by MIT Professor and PON Executive Committee member Jared Curhan and University of Southern California Professor Jonathan Gratch. Because AI developed so rapidly, the 2025 discussion already required updating in 2026. PON is therefore preparing another summit for 2027 and inviting proposals on AI, negotiation, mediation, and dispute resolution.

Holding the summit at MIT reflects interdisciplinary integration rather than a lack of AI capacity at Harvard. AI and ODR involve legal responsibility, data compliance, human-machine communication, procedural design, platform governance, and public legal services. No single law school or discipline can address all of these issues. Harvard’s strengths in negotiation and dispute resolution complement MIT’s expertise in technology and innovation, illustrating a broader movement from self-contained legal training toward an educational ecosystem linking law, technology, and social problems.

A similar trend can be seen at Stanford Law School. Stanford Professor Janet Martinez participated in the 2026 ODR events and had visited the Hangzhou Internet Court shortly after its establishment in 2017, examining it as an important ODR court practice. Her interest shows that leading U.S. scholars do not limit ODR research to domestic experience. The Hangzhou Internet Court has become part of a global conversation connecting U.S. legal scholarship, China’s internet justice practices, and the development of digital justice.

Stanford Law School’s Legal Innovation through Frontier Technology Lab, or liftlab, further reflects attention to the future of the legal profession. Rather than focusing only on automating legal research or document production, liftlab explores how AI may change the organization of legal work, expand access to legal services, and reshape the social role of law. Harvard and Stanford approach the issue through different institutional strengths, but both demonstrate that AI and ODR have become central to legal research, curriculum design, and professional training.

Within this context, Fang was invited to speak in a breakout session at the Harvard ODR Forum. His presentation was titled “The ODR Chase: AI Liability in China in Light of Raine v. OpenAI.” In the official agenda, he used the fuller title “From ‘The Paper Chase’ to the ODR Chase: AI Liability Disputes and ODR in China.”

Figure 1. Professor Michael Fang delivers his English-language presentation, 

“The ODR Chase: AI Liability in China in Light of Raine v. OpenAI”, at the Harvard ODR Forum.

The Paper Chase is a classic film about student life at Harvard Law School. “Paper” refers to the cases, legal documents, and course materials traditionally studied by law students and also symbolizes an intensive model of legal training centered on written texts. Fang transformed this familiar expression into an “ODR Chase” for the AI era. Traditional legal education emphasized mastering cases, rules, analysis, and legal writing. Today’s lawyers must also track AI risks, define platform responsibility, evaluate digital evidence, understand online procedures, and navigate cross-border dispute resolution.

Using Raine v. OpenAI as a starting point, the presentation examined new forms of harm and liability associated with generative AI and considered how China’s AI governance framework, internet courts, online litigation platforms, and online arbitration mechanisms might prevent, divert, or resolve such disputes. The broader question was not simply how one case should be decided, but whether legal systems can respond promptly and flexibly to emerging AI risks through platform rules, online procedures, and multiple dispute resolution mechanisms.

These issues directly affect the competencies law firms will require. Future lawyers may face disputes involving AI hallucinations, algorithmic misrepresentation, minors’ interactions with AI, platform duties of care, digital evidence, and cross-border AI services. Cross-border matters may involve the location of the platform, user, data, service, and harm, requiring knowledge of jurisdiction, choice of law, data compliance, online arbitration, and enforcement.

The transition from “The Paper Chase” to the “ODR Chase” therefore represents more than a creative title. Traditional legal skills remain indispensable, but lawyers must also identify technological and procedural risks, use digital tools appropriately, understand ODR, and preserve independent factual, legal, and ethical judgment. Law firms will increasingly ask whether graduates can formulate the right questions, recognize the limits of AI outputs, understand clients’ real needs, and connect law, technology, negotiation, and cross-border procedure in workable solutions.

Figure 2. Michael Fang exchanges views with Chris Gibson, Director of the Alternative Dispute Resolution Program at Suffolk Law.

On June 12, Fang attended “Arbitration and Mediation in the Age of AI,” jointly organized by the AAA and Suffolk University Law School in downtown Boston. The conference examined AI’s effects on arbitration, mediation, courts, and ODR, demonstrating cooperation between a major dispute resolution institution and a law school.

In his opening remarks, Suffolk Law Dean Andrew M. Perlman observed that traditional legal education trains students to recognize familiar categories of legal problems. As legal services change, however, students must also learn to identify problems and deliver services in new ways. They should be able to recognize that an established method may not be the most effective way to serve legal employers, clients, or the public. In the AI era, alternative approaches may involve AI tools, online platforms, process design, interdisciplinary collaboration, and ODR.

Perlman also discussed Suffolk’s work in online dispute resolution, including the Online Dispute Resolution Innovation Clinic. With guidance from experienced professionals, the clinic helps courts explore ODR applications; former Massachusetts Family Court Chief Justice John Casey has been an important participant. Perlman nevertheless emphasized that human judgment remains essential when technology enters dispute resolution.

His remarks suggest that a law school should not be evaluated solely by rankings or traditional reputation. Its value also lies in whether it responds to changes in the legal services market and gives students opportunities to work on real problems. Law graduates will increasingly be judged by their ability to understand technology, identify client needs, participate in ODR, and develop implementable solutions.

The conference also prompted reflection on Berkeley Law’s approach to student use of generative AI. During the event, Dr. Chris Draper, a Berkeley graduate, presented “Ethics and Regulation: Governing AI in Dispute Resolution.” Berkeley Law’s policy taking effect in summer 2026 establishes strong default restrictions on using generative AI for graded work and prohibits it in examinations, while allowing instructors to authorize exceptions based on course objectives.

The policy is not simply an anti-AI rule. It seeks to balance two goals: preparing students to use AI effectively and ethically, while ensuring that papers and examinations measure students’ own analysis, writing, and judgment. Students must first develop the ability to perform core legal tasks independently before they can supervise AI reliably and recognize hallucinations, false citations, plagiarism, and other errors. Berkeley’s approach therefore redraws the boundary between learning to use AI and preserving the integrity of legal assessment.