Corpus Linguistics, LLM AIs, and the Future of Ordinary Meaning

Politics

Thomas Lee and Jesse Egbert | 10.15.2024 7:32 AM

Modern textualism is built on at least three central pillars. Textualists credit the ordinary meaning of the language of law because such meaning: (1) can reasonably be discerned by determinate, transparent methods; (2) is fairly attributable to the public who is governed by it; and (3) is expected to constrain judges from crediting their own views on matters of legislative policy.

To fulfill these goals, textualist judges expected to show their work—to cite reliable evidence to support their conclusions on how legal words or phrases are commonly used by the public. Judicial intuition is a starting point. But judges who ask the parties and public to take their subjective word for it are not engaged in transparent textual analysis; cannot reliably be viewed as protecting public reliance interests; and may (at least subconsciously) be advancing their own views on legislative policy.

The Snell concurrence acknowledges these concerns (as do the academic pieces it relies on). But the tools it advances (AI LLMs) fall short of fulfilling these key premises. Corpus linguistic tools, by contrast, are up to the task.

We show how in our draft article. In Part III we investigate the empirical questions in Snell through the tools of corpus linguistics. We performed transparent searches aimed at assessing (a) how the term "landscaping" is commonly used in public language; and (b) whether people commonly use the term "landscaping" when they speak of the installation of in-ground trampolines. Our results are granular and nuanced. They stand in contrast to the conclusory assertions of AI chatbots—conclusions that gloss over legal questions about the meaning of "ordinary meaning" and make it........

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