{"id":24089,"date":"2026-02-06T13:55:46","date_gmt":"2026-02-06T18:55:46","guid":{"rendered":"https:\/\/www.law.georgetown.edu\/georgetown-law-journal\/in-print\/volume-114\/volume-114-issue-1-november-2025\/large-language-models-for-legal-interpretation-dont-take-their-word-for-it\/"},"modified":"2026-02-06T14:01:51","modified_gmt":"2026-02-06T19:01:51","slug":"large-language-models-for-legal-interpretation-dont-take-their-word-for-it","status":"publish","type":"page","link":"https:\/\/www.law.georgetown.edu\/georgetown-law-journal\/in-print\/volume-114\/volume-114-issue-1-november-2025\/large-language-models-for-legal-interpretation-dont-take-their-word-for-it\/","title":{"rendered":"Large Language Models for Legal Interpretation? Don\u2019t Take Their Word for It"},"content":{"rendered":"<p><em>Recent breakthroughs in statistical language modeling have impacted countless domains, including the law. Chatbot applications such as ChatGPT, Claude, and DeepSeek\u2014which incorporate \u201clarge\u201d neural network-based language models (LLMs) trained on vast swathes of internet text\u2014process and generate natural language with remarkable fluency. Recently, scholars have proposed adding AI chatbot applications to the legal interpretive toolkit. These suggestions are no longer theoretical: in 2024, a U.S. judge queried LLM chatbots to interpret a disputed insurance contract and the U.S. Sentencing Guidelines.<\/em><\/p>\n<p><em>We assess this emerging practice from a technical, linguistic, and legal perspective. This Article explains the design features and product development cycles of LLM-based chatbot applications, with a focus on properties that may promote their unintended misuse\u2014or intentional abuse\u2014by legal interpreters. Next, we argue that legal practitioners run the risk of inappropriately relying on LLMs to resolve legal interpretive questions. We conclude with guidance on how such systems\u2014and the language models which underpin them\u2014can be responsibly employed alongside other tools to investigate legal meaning.<\/em><\/p>\n<p>Continue reading <a href=\"https:\/\/www.law.georgetown.edu\/georgetown-law-journal\/wp-content\/uploads\/sites\/26\/2026\/02\/Waldon_Schneider_Wilcox_Zeldes_Tobia_Large-Language-Models-for-Legal-Interpretation-Dont-Take-Their-Word-for-It.pdf\"><em>Large Language Models for Legal Interpretation? Don\u2019t Take Their Word for It<\/em><\/a>.<\/p>\n<a href=\"https:\/\/www.law.georgetown.edu\/georgetown-law-journal\/wp-content\/uploads\/sites\/26\/2026\/02\/Waldon_Schneider_Wilcox_Zeldes_Tobia_Large-Language-Models-for-Legal-Interpretation-Dont-Take-Their-Word-for-It.pdf\" class=\"pdfemb-viewer\" style=\"\" data-width=\"max\" data-height=\"max\" data-toolbar=\"bottom\" data-toolbar-fixed=\"off\">Waldon_Schneider_Wilcox_Zeldes_Tobia_Large-Language-Models-for-Legal-Interpretation-Dont-Take-Their-Word-for-It<\/a>\n","protected":false},"excerpt":{"rendered":"<p>Recent breakthroughs in statistical language modeling have impacted countless domains, including the law. Chatbot applications such as ChatGPT, Claude, and DeepSeek\u2014which incorporate \u201clarge\u201d neural network-based language models (LLMs) trained on [&hellip;]<\/p>\n","protected":false},"author":16434,"featured_media":0,"parent":24071,"menu_order":2,"comment_status":"closed","ping_status":"closed","template":"abstract.php","meta":{"_acf_changed":false,"_price":"","_stock":"","_tribe_ticket_header":"","_tribe_default_ticket_provider":"","_tribe_ticket_capacity":"0","_ticket_start_date":"","_ticket_end_date":"","_tribe_ticket_show_description":"","_tribe_ticket_show_not_going":false,"_tribe_ticket_use_global_stock":"","_tribe_ticket_global_stock_level":"","_global_stock_mode":"","_global_stock_cap":"","_tribe_rsvp_for_event":"","_tribe_ticket_going_count":"","_tribe_ticket_not_going_count":"","_tribe_tickets_list":"[]","_tribe_ticket_has_attendee_info_fields":false,"footnotes":"","_tec_slr_enabled":"","_tec_slr_layout":""},"class_list":["post-24089","page","type-page","status-publish","hentry"],"acf":[],"ticketed":false,"_links":{"self":[{"href":"https:\/\/www.law.georgetown.edu\/georgetown-law-journal\/wp-json\/wp\/v2\/pages\/24089","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.law.georgetown.edu\/georgetown-law-journal\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.law.georgetown.edu\/georgetown-law-journal\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.law.georgetown.edu\/georgetown-law-journal\/wp-json\/wp\/v2\/users\/16434"}],"replies":[{"embeddable":true,"href":"https:\/\/www.law.georgetown.edu\/georgetown-law-journal\/wp-json\/wp\/v2\/comments?post=24089"}],"version-history":[{"count":2,"href":"https:\/\/www.law.georgetown.edu\/georgetown-law-journal\/wp-json\/wp\/v2\/pages\/24089\/revisions"}],"predecessor-version":[{"id":24093,"href":"https:\/\/www.law.georgetown.edu\/georgetown-law-journal\/wp-json\/wp\/v2\/pages\/24089\/revisions\/24093"}],"up":[{"embeddable":true,"href":"https:\/\/www.law.georgetown.edu\/georgetown-law-journal\/wp-json\/wp\/v2\/pages\/24071"}],"wp:attachment":[{"href":"https:\/\/www.law.georgetown.edu\/georgetown-law-journal\/wp-json\/wp\/v2\/media?parent=24089"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}