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Optimization in Mediation and Artificial Intelligence

As far as I can tell, the development and deployment of artificial intelligence (AI) is the biggest technical advance for mediators and mediation since the original adoption of email in the 1980’s and the commercialization of the web in the 1990’s. AI is that important.

The reason that AI is such a big deal for mediators and mediation is that our “secret sauce” has long been the concept of “optimization” or “maximization.” We don’t simply help disputants achieve “barely sufficient settlement.” Rather, our service goal is to help disputants achieve “most capable solutions.” In fact, it is the embedded goal in mediation of “doing the best that can be done” that, along with participant decision-making control, most differentiates mediation from both litigation and arbitration. Litigation and arbitration do not optimize, they simply decide, commonly with a “winner” and a “loser.”

The stimulus to optimize solutions often comes from the mediator. Once parties come to realize that they simply are not going to “get their way” on everything, an adjusted mediation goal commonly becomes, “OK, so how can we get each of you as much of what you want, even if that cannot be done perfectly.” With such an adjusted and mutualized problem-solving statement, parties commonly come to realize that the most effective way to negotiate is often to “give” the other party a good measure of what they want, if only as an inducement and incentive for them to “return the favor” as part of an upward spiral of agreed-upon future arrangements.

Prior to the introduction of AI, one of the most valuable functions of a mediator has been to so be a source of “wisdom” in terms of how other similar situated participants have most capably resolved such challenging issues. Commonly, the wise mediator avoids recommending the consideration of any “single solution,” preferring instead to offer possible exchanges or package deals that may have worked for others. A mediator’s accumulated awareness and wisdom of how other similarly situated participants have successfully resolved things is one of our most powerful “tricks of our trade.” Knowing that neither party is willing to “cave” in to the other’s demands, a mediator offering approaches to maximize each participants satisfaction is a welcome relief, if not a saving grace.

I used to think that parties came to mediation wanting to “win” or “prevail.” What I have learned over the years is that a successful mediation does not have a “winner.” There needs to be good value for each participant to achieve resolution. It is not so much that participants need to “win,” as they are absolutely unwilling to “lose.” Participants want to be smart, not dumb or played for a chump or a fool.

Another lesson I have learned is that participants in mediation are always reporting to someone. It might be their business colleagues, or family members, or a new partner, or friends, but everyone in mediation knows that they will be “reporting” on the results of mediation to someone that they care about and cares about them. Hence, to settle, each participant needs to come up with a rationale, or at least a rationalization, for why they are willing to enter into a less than perfect mediated resolution.

Without a face-saving rationale that can be shared with significant others, participants will simply not agree. They will only agree when they can explain to themselves and to significant others why they are agreeing to a resolution with someone who until very recently was “the enemy.” By positively highlighting what each participant gets from a settlement, a mediator helps each participant to form a personalized rationale for settling. Without such a tailored settlement explanation (set of face-saving rationales), people simply will not settle. They will not agree to something that they cannot comfortably explain to themselves and to important others.

Which brings us back to the concept of “optimization” more generally. Critical for the mediator (and reader) is to understand that optimization is not limited to substantive settlement issues and arrangements. Optimization also applies to such facets as:

  • achieving a most effective (optimized) rapport with each participant
  • most capably communicating (visual, auditory, kinesthetic) with each participant
  • most effectively using metaphors and analogies with each participant
  • most capably assisting each participant to have the experience of “being heard” (acknowledged and appreciated)
  • most effectively implementing new arrangements with impacted others

And so, the main purpose of this article is to first suggest that AI will in relatively short time become a valuable tool for both mediators and mediation participants to explore optimized solutions. In fact, we as a mediation community can build our own AI mediation engines to embrace and generate optimized arrangements and approaches. By basing our AI systems on most relevant and valuable settlement information, including arrangements that have worked best for similarly situated others, we can ever more effectively bring concepts of optimization into our mediations and to the world. Whether as a tool for mediators or an idea generator for participants, AI engines will support mediators and the mediation process to bring the highest levels of participant satisfaction possible.

This is in fact the time for mediators and mediation programs to get a bit”greedy” in being sure that developed AI mediation engines do not simply seek to optimize the substantive terms of a settlement. To be most effective, and to continue changing both individuals and the world for the better, mediation AI engines also need to consider the full individual that is participating in a mediation, including how to best get along, how to best communicate and how to best hear from them.

In sum, AI offers the potential for mediators and mediation to ever-improve our optimizing nature, both substantively and relationally. As mediation continues forward as the one dispute resolution process that truly champions empowered participants and optimizing solutions, it seems that AI offers an unprecedented opportunity to bring the best of mediation to a ready world. My read is that mediation’s “secret sauce of optimization” will soon be extended by capable AI systems. With the assistance of AI, “optimized solutions” are soon to become a much needed social expectation.


James (Jim) Melamed

Jim Melamed co-founded in 1996 along with John Helie and served as CEO of through June 2020 (25 years).  Jim is currently Board Chair and General Counsel for Resourceful Internet Solutions, Inc. (RIS), home to,, and other leading dispute resolution sites. During Jim's 25-year tenure,… MORE >

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