Using Artificial Intelligence in the Law Review Submissions Process
43 Pages Posted: 23 May 2022
Date Written: May 19, 2022
The use of artificial intelligence to help editors examine law review submissions may provide a way to improve an overburdened system. This Article is the first to explore the promise and pitfalls of using artificial intelligence in the law review submissions process. Technology-assisted review of submissions offers many possible benefits. It can simplify preemption checks, prevent plagiarism, detect failure to comply with formatting requirements, and identify missing citations. These efficiencies may allow editors to address serious flaws in the current selection process, including the use of heuristics that may result in discriminatory outcomes and dependence on lower-ranked journals to conduct the initial review of submissions. Although editors should not rely on a score assigned by an algorithm to decide whether to accept an article, technology-assisted review could increase the efficiency of initial screening and provide feedback to editors on their selection decisions. Uncovering potential human bias in the selection process may encourage editors to develop ways to minimize its harmful effects.
Despite these benefits, using artificial intelligence to streamline the submissions process raises significant concerns. Technology-assisted review may enable efficient implementation of existing biases into the selection process, rather than correcting them. Artificial intelligence systems may rely on considerations that result in discriminatory effects and negatively impact groups that are not adequately represented during development. The tendency to defer to seemingly neutral and often opaque algorithms can increase the risk of adverse outcomes. With careful oversight, however, some of these concerns can be addressed. Even an imperfect system may be worth using in limited situations where the benefits substantially outweigh the potential harms. With appropriate supervision, circumscribed application, and ongoing refinement, artificial intelligence may provide a more efficient and fairer submissions experience for both editors and authors.
Keywords: artificial intelligence, algorithm, analytics, AI, machine learning, data, technology, bias, discrimination, law review, scholarship, publication, citation, research
JEL Classification: O30, C89, I24
Suggested Citation: Suggested Citation