An Uncommon Task: Participatory Design in Legal AI

• Main Authors: Delgado, Fernando, Barocas, Solon, Levy, Karen
• Format: Journal Article
• Language: English
• Published: 08-03-2022
• Subjects: Computer Science - Artificial Intelligence; Computer Science - Computers and Society; Computer Science - Human-Computer Interaction; Computer Science - Information Retrieval
• DOI: 10.48550/arxiv.2203.06246

In Proceedings of the ACM on Human-Computer Interaction, 6, CSCW1,
Article 51 (April 2022), 23 pages Despite growing calls for participation in AI design, there are to date few
empirical studies of what these processes look like and how they can be
structured for meaningful engagement with domain experts. In this paper, we
examine a notable yet understudied AI design process in the legal domain that
took place over a decade ago, the impact of which still informs legal
automation efforts today. Specifically, we examine the design and evaluation
activities that took place from 2006 to 2011 within the TeXT Retrieval
Conference's (TREC) Legal Track, a computational research venue hosted by the
National Institute of Standards and Technologies. The Legal Track of TREC is
notable in the history of AI research and practice because it relied on a range
of participatory approaches to facilitate the design and evaluation of new
computational techniques--in this case, for automating attorney document review
for civil litigation matters. Drawing on archival research and interviews with
coordinators of the Legal Track of TREC, our analysis reveals how an
interactive simulation methodology allowed computer scientists and lawyers to
become co-designers and helped bridge the chasm between computational research
and real-world, high-stakes litigation practice. In analyzing this case from
the recent past, our aim is to empirically ground contemporary critiques of AI
development and evaluation and the calls for greater participation as a means
to address them.