Levering AI in the Service of Contract Interpretation

Contract interpretation canons and theories continue to evolve. The latest foray seeks to lever AI.

In a recent article, Generative Interpretation, the authors, David Hoffman (Penn) and Yonathan Arbel (Alabama), advance a new approach designed to assist in determining contracting parties’ meaning. The authors' impulse behind generative interpretation, is, according to them, "simple:" they apply large language models (LLMs) to contractual texts and extrinsic evidence to predict what the parties would have said at contracting about what they meant. The paper's abstract follows.

“We introduce generative interpretation, a new approach to estimating contractual meaning using large language models. As AI triumphalism is the order of the day, we proceed by way of grounded case studies, each illustrating the capabilities of these novel tools in distinct ways. Taking well-known contracts opinions, and sourcing the actual agreements that they adjudicated, we show that AI models can help factfinders ascertain ordinary meaning in context, quantify ambiguity, and fill gaps in parties’ agreements. We also illustrate how models can calculate the probative value of individual pieces of extrinsic evidence.

After offering best practices for the use of these models given their limitations, we consider their implications for judicial practice and contract theory. Using LLMs permits courts to estimate what the parties intended cheaply and accurately, and as such generative interpretation unsettles the current interpretative stalemate. Their use responds to efficiency-minded textualists and justice-oriented contextualists, who argue about whether parties will prefer cost and certainty or accuracy and fairness. Parties—and courts—would prefer a middle path, in which adjudicators strive to predict what the contract really meant, admitting just enough context to approximate reality while avoiding unguided and biased assimilation of evidence. As generative interpretation offers this possibility, we argue it can become the new workhorse of contractual interpretation.”