Attorney bargaining has traditionally taken place in the shadow of trial as litigants adjust tactics-and their inclination to negotiate a settlement-based on their forecast of the outcome of a trial and its associated costs. Lawyers bargaining on the verge of trial have traditionally relied on their intuition, knowledge of precedent, and previous interactions with the presiding judge and opposing counsel to forecast trial outcomes and litigation costs. Today, however, technology that leverages legal data is moving the practice of law into the shadow of the trends and patterns apparent in aggregated litigation data. This Article describes the tools that facilitate this paradigm shift and examines how lawyers use these tools to forecast litigation outcomes and reduce Coasean bargaining costs in both litigation and transactional fields. This Article also explores some of the risks associated with bargaining in the shadow of big data, and it offers guidance to lawyers leveraging these tools to improve their practice.
This discussion pushes beyond the cartoonish image of big data as a mechanical fortuneteller-predicting who will win or lose a case, supposedly eliminating research or deliberation. This Article also debunks the alarmist cliches about newfangled technologies eliminating jobs. Demand for lawyers who are capable of effective bargaining when confronted by big data will continue to increase as the legal profession catches up to the data-centric approach found in other industries. Ultimately, this Article paints a portrait of what big data really means for practicing attorneys, and it provides a framework for exploring the theoretical implications of lawyering in the era of information analytics.
Dru Stevenson and Nicholas J. Wagoner,
Bargaining in the Shadow of Big Data,
67 Fla. L. Rev.
Available at: https://scholarship.law.ufl.edu/flr/vol67/iss4/7