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

Author:

C. Thompson Neil1ORCID,Luo Xueyun2ORCID,McKenzie Brian3,Richardson Edana4ORCID,Flanagan Brian4ORCID

Affiliation:

1. MIT Computer Science & Artificial Intelligence Laboratory, MIT Initiative on the Digital Economy, Cambridge, Massachusetts 02139;

2. SC Johnson College of Business, Cornell University, Ithaca, New York 14853;

3. Critical Skills Programme, Maynooth University, W23 F2H6 County Kildare, Ireland;

4. School of Law and Criminology, Maynooth University, W23 F2H6 County Kildare, Ireland

Abstract

User-generated content, for example, on Wikipedia, is easily accessed but has uncertain reliability. This makes it attractive to use but also creates risk, so there should be limits to who uses Wikipedia and for what purposes. In this paper, we use a randomized control trial to show that Wikipedia’s influence extends to judicial decision making, a field that is highly professional and supposed to follow strict procedures. This causal evidence further emphasizes the widespread influence of Wikipedia and other frequently accessed user-generated content on important social outcomes. Our findings also reveal boundaries to user-generated content’s influence. Although Wikipedia’s influence does extend to courts of “first instance” (where the case is first decided), it does not extend to higher courts (Court of Appeals, Supreme Court). These results suggest that normative prohibitions do seem to be sufficient to keep Wikipedia from influencing the most-important, well-resourced parts of law but that these prohibitions are insufficient in areas where time and resource pressures are greater. By showing that Wikipedia is influencing such an important and formal domain, our paper reinforces the importance of improving the accuracy and reliability of user-generated content, especially in domains with far-reaching societal consequences. Because there is no obvious way to prevent individuals from taking advantage of user-generated content professionally or nonprofessionally, our findings also contribute to the ongoing discussion of how to build public repositories of knowledge into more reliable storehouses.

Publisher

Institute for Operations Research and the Management Sciences (INFORMS)

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