The Value of Proactive Data for Intelligent Contracts

Intelligent Contracts (iContracts) is a new branch of research at the intersection of AI and law. It has many challenges, among which including the quality of data used. In our research we focus on generating and including quality Proactive Control Data (PCD) to improve iContracts, which is a novel research scope in literature. Our scope is defined by the main challenge in regards to emerging legal technologies. Currently, the legal system is more reactive than proactive, leading to high consequential legal costs. By shifting the focus to proactiveness, we discuss and improve upon the available methodologies (Bow-Tie Method and Logocratic Method) and technologies (Ontology Engineering, Software Engineering and Large Language Models [LLMs]) to demonstrate a higher degree of proactiveness in iContracts. Our results are threefold. First, we prove that the generation of PCD is possible with the development of a prototype that leverages the foundations of the Bow-Tie Method. Second, we demonstrate that the impact of PCD on contract drafting is significant, as the explicit inclusion of PCD in prompt engineering alters significantly the content of an LLM-drafted contract. Third, we show how the quality of PCD can be assessed and improved upon with the application of the Logocratic Method. The discussion highlights the feasibility of the research with available technologies. Ultimately, the implementation of our research depends on organisational considerations and resource allocation. We conclude that the generation of PCD is feasible, their impact on contract drafting is significant and their quality assessment is both possible and novel.