Research

Paper

AI LLM February 27, 2026

"Make It Sound Like a Lawyer Wrote It": Scenarios of Potential Impacts of Generative AI for Legal Conflict Resolution

Authors

Kimon Kieslich, Natali Helberger, Nicholas Diakopoulos

Abstract

Generative AI (GenAI) tools are transforming critical societal domains, including the legal sector. While these tools create opportunities such as increased efficiency and potential improvements in access to justice, they also present new challenges, such as the risk of inaccurate legal advice and questions about the legitimacy of legal decisions. However, the full impact remains to be seen and ultimately depends on the way GenAI tools are implemented and used by both, legal professionals and citizens. This makes anticipating and managing the positive and negative impacts of GenAI use in the legal domain challenging but also important to guide the digital transformation of the legal sector into a societally desirable direction. In this paper, we set out to explore the spectrum of possible impacts of GenAI in the legal domain, examining how this technology is anticipated being used and the potential implications this might have for the legal sector and society. Using a scenario writing method, we surveyed participants in the EU and US including both citizens and legal professionals about the potential impact of generative AI on legal conflict resolution. Respondents were tasked with writing a narrative drawing on their experience or expertise about a future in which AI is used throughout the legal process. We qualitatively analysed the prevalence of risk and benefit themes, as well as the types of anticipated legal tasks. We then compared these findings based on expertise status (legal experts versus citizens) and regional regulatory background (the EU with the EU AI Act versus the US with an industry self-regulatory approach). Finally, we describe the emerging trade-offs that will affect decision-makers in the legal sector.

Metadata

arXiv ID: 2602.24130
Provider: ARXIV
Primary Category: cs.CY
Published: 2026-02-27
Fetched: 2026-03-02 06:04

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Raw Data (Debug)
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