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Digital Transformation of the Legal Educational Space. How Does Artificial Intelligence Affect the Training of Law Students?

Kirill Yu. MolodykoTashkent State University of Law (Tashkent, Uzbekistan)
BRICS Law Journaljournal2026en
ABI

Аннотация

This article examines three issues related to the use of artificial intelligence in legal education, based primarily on an analysis of the American experience. The first issue is how the use of artificial intelligence changes the assessment of law school students. I take the position that there is no need to get caught up in an “arms race” between the programs used by students and those used by teachers, but rather that it is advisable to return to assessment based, as a rule, on written work in class and oral responses in class. I draw attention to the incorrect formalistic use of Turnitin in post-Soviet law schools and propose measures to remedy this situation. The second part covers the issue of AI law students’ use of AI in classroom discussions. The third part focuses on the experience of using video cameras in classrooms in US and EU. In this part of the article, I analyze the approaches used in American universities and high schools, since the experience of the latter can largely be applied to universities, except for the consent of students’ parents. I argue that the use of video cameras in law school classrooms should be significantly restricted. Since the legislation of post-Soviet countries does not currently regulate this issue, this gives law schools the opportunity to develop a balanced policy on the use of video cameras in classrooms, through a broad dialogue between the administration, faculty, students, and local representatives of civil society. Law schools should serve as an example for other departments at traditional universities, as only law schools within universities have the qualifications to develop these rules. Universities that are the first to develop and adopt such a sensible policy will gain significant image advantages over other law schools that do not.

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