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Accepted Paper:
Paper short abstract:
This paper is based on a fieldwork carried out in a French startup offering a “predictive justice” service. It will question the role of the legal experts annotating court decisions in order to feed AI models, and analyze the evolution of this annotation process over time.
Paper long abstract:
This paper is based on a field work conducted in a French startup providing a “predictive justice” tool. This tool allows legal experts to estimate the probable outcome of a case by modeling the decision processes of a panel of a hundred fictional judges. In order to do so, it dwells on the annotation and analysis of past court decisions that feed the artificial intelligence model. Aiming at better understanding how such tools are conceived, this contribution will take as its object the annotation process implemented by the legaltech.
The annotation in itself is handled mostly by law students from outside the company, but the analysis grid is designed by law experts who work for the startup. While this work division was stable over time, the annotation process evolved: after using Excel spreadsheets to analyze court decisions, law students were provided with a software developed by the legaltech.
Based on an interview survey and on a study of documents obtained in the field, this paper will analyze the role and metamorphoses of the annotation process, and show how it has been shaped by the needs of interdisciplinary dialogue. Indeed, the annotation process is at the heart of multiple “translation” (Callon, 1986) processes: mathematicians, developers and law experts have to collaborate to produce a tool both efficient and useful. In this context, the result of the annotation can be seen as an hybrid language, aiming at satisfying both legal reasoning and the needs of computer scientists.
Questioning data annotation for AI: empirical studies
Session 2 Friday 19 July, 2024, -