In insurance, disputes related to word meaning arise from a lack of clarity around rules governing the benefits and exclusions of insurance policies. Understanding the open texture and fluidity of language use then warrants investigation, particularly as we transition to using formal logic and programming languages to draft and construct legal documents. Accordingly, we investigate the vagueness of policy wording across three branches: (1) elasticity; (2) categorical ambiguity and vagueness; and (3) logical coherence.

In effect, we ask: where is/are the locus(i) of “vagueness” and is it entirely linguistic? If so, is it specifically the open texture of language that is explanatory of the information asymmetries an average consumer is plagued by? Put differently, what is it that the lay person does not know about their insurance coverage?

In short, our research aims to provide insight and contribute to the development of (1) a common insurance semantics; and (2) systematic detection of clauses that lead to possible interpretational disputes. Furthermore, we hope to build tools that could better enable detecting variability in interpretation as well as contradiction at the document level.

We suggest that in better identifying (and perhaps measuring) the sources of “vagueness,” such as assessing the interpretation gap between lay and expert understanding, we could support advancing computable contracts that offer insight into coverage gaps, risk exposure, and increased transparency in the processing of claims. In effect, this could enable both new entry and engagement points with insurance policies.

Project Lead:
Megan Ma