ABSTRACT
‘You can think of transaction costs broadly as pain-in-the-ass costs. All platforms reduce these costs in some way’ – Alex Moazed, author of Modern Monopolies.
In the United States, thousands of viable claims routinely drown in a sea of transaction costs. If you’re a customer wronged by a company, chances are you have little practical legal recourse. Hire a lawyer? Good luck – an hour of attorney time might exceed the value of your claim. Small claims court? Maybe – but it’s rarely worth the time, effort, stress, and risk. Class actions aren’t under your control, and anyway, that seven-dollar check is barely worth the trip to the post office. Then again, none of that is even on the table: remember that forced-arbitration clause on page 39 of that clickwrap agreement? And of course, the arbitration fee is thrice the value of your claim.
Ballooning transaction costs create problems for companies contracting with one another as well, where the combination of uncertainty, time, litigation or arbitration fees, and asymmetrical power dynamics routinely leads to bad outcomes and suboptimal dispute resolution.
But new technologies bring new solutions, and major developments in artificial intelligence, deep learning, and computational statistics offer a powerful and elegant way to drastically reduce the transaction costs associated with resolving a wide array of claims. In this article, I draw from advancements and fundamental principles in the fields of Computer Science, Artificial Intelligence, Economics, and Medicine to propose a novel platform and methodology for using currently available technology to slash transaction costs and enable the vindication of a wide array of claims that, today, are functionally unresolvable.
Crucially, this article is not about incorporating AI into the justice system, or inserting it into forced arbitration, as others have thoughtfully written about. Instead, I propose and predict a novel, contracts-based private mechanism enabling parties to voluntarily resolve a wide array of disputes through a flexible AI platform that has a known margin of error that the parties would accept at the outset, in exchange for a combination of reduced transaction costs, the chance to resolve a dispute that might otherwise be irremediable, and finality. I further and relatedly argue that, if successfully implemented, such a platform would lead to a rapid shift in how a range of disputes are resolved, and that it would change the use cases for class actions and mass arbitrations for the better.
Henderson, Zachary, Artificial Intelligence, Probabilistic Dispute Resolution, and the Small-Claims Wasteland (July 31, 2024).
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