User-Generated Content Shapes Judicial Reasoning: Evidence from a Randomized Control Trial on Wikipedia

Neil C. Thompson (), Xueyun Luo (), Brian McKenzie (), Edana Richardson () and Brian Flanagan ()
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Neil C. Thompson: MIT Computer Science & Artificial Intelligence Laboratory, MIT Initiative on the Digital Economy, Cambridge, Massachusetts 02139
Xueyun Luo: SC Johnson College of Business, Cornell University, Ithaca, New York 14853
Brian McKenzie: Critical Skills Programme, Maynooth University, Maynooth, W23 F2H6 County Kildare, Ireland
Edana Richardson: School of Law and Criminology, Maynooth University, Maynooth, W23 F2H6 County Kildare, Ireland
Brian Flanagan: School of Law and Criminology, Maynooth University, Maynooth, W23 F2H6 County Kildare, Ireland

Information Systems Research, 2024, vol. 35, issue 4, 1948-1964

Abstract: Legal professionals have access to many different sources of knowledge, including user-generated Wikipedia articles that summarize previous judicial decisions (i.e., precedents). Although these Wikipedia articles are easily accessible, they have unknown provenance and reliability, and therefore using them in professional settings is problematic. Nevertheless, Wikipedia articles influence legal judgments, as we show using a first-of-its-kind randomized control trial on judicial decision making. We find that the presence of a Wikipedia article about Irish Supreme Court decisions makes it meaningfully more likely that the corresponding case will be cited as a precedent by judges in subsequent decisions. The language used in the Wikipedia article also influences the language used in judgments. These effects are only present for citations by the High Court and not for the higher levels of the judiciary (Court of Appeal and Supreme Court). The High Court faces larger caseloads, so this may indicate that settings with greater time pressures encourage greater reliance on Wikipedia. Our results add to the growing recognition that Wikipedia and other frequently accessed sources of user-generated content have profound effects on important social outcomes and that these effects extend farther than previously seen—into high-stakes settings where norms are supposed to restrict their use.

Keywords: Wikipedia; user-generated content; knowledge diffusion; law and economics; randomized control trial (search for similar items in EconPapers)
Date: 2024
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