Legalarxiv.

Building a better lawyer: Experimental evidence that artificial intelligence can increase legal work efficiency

Aileen Nielsen, Stavroula Skylaki, Milda Norkute, Alexander Stremitzer

Authors & affiliations

Aileen Nielsen, Stavroula Skylaki, Milda Norkute, Alexander Stremitzer

Affiliations reported at publication:

  • Harvard Law School (Aileen Nielsen)
  • Thomson Reuters Labs (Stavroula Skylaki, Milda Norkute)
  • ETH Zurich, Center for Law and Economics (Alexander Stremitzer)

Journal of Empirical Legal Studies 21(4), 979–1022; first published 17 November 2024

Read the paperPublication source

This entry is based on the publisher’s abstract. Full-text assessment is pending.

What it adds

Separates the effects of AI-generated summaries and text highlighting on legal complaint-reading tasks, connecting interface design to completion time and measured quality.

Read with this limitation

Student complaint-reading tasks do not establish experienced lawyers' performance on client matters or different tasks. The journal's full final text was not accessible in this review. Replication data are available on request rather than through a verified public package.

Jurisdiction tags
United States
Language
English

Research artifacts

Resources linked by the authors.

Follow the source

Selected statements located in the publisher’s abstract. These results have not been independently reproduced here.

  1. The study compares AI-generated summaries and highlighting in an experiment with 206 law students.

    Abstract

  2. The abstract reports faster completion with highlighting and no reduction in measured quality indicators; summaries alone produced no change in performance metrics.

    Abstract
Entry status, source edition & rights
Index entry
Source-linked summary, prepared with agent assistance. Independent scholarly review is pending.
Archive admission
This bibliographic entry does not confer admission to the versioned archive.
Edition inspected
10.1111/jels.12396
Reading coverage
Journal metadata, abstract and data-availability statement inspected; displayed claims refer to this final journal abstract. The separate October 2024 Harvard Discussion Paper 1111 was inspected for methodological context, including PDF pages 11–19 and 34–35, and is explicitly linked as an earlier manuscript. No final-journal full-text review or experiment rerun is asserted.
Rights
External source and manuscript links only. No full text or research data is mirrored; original-host terms apply. Linking an earlier manuscript does not identify it as the final journal edition.
Entry updated
2026-10-15

Source-linked summary · independent assessment pending.

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