Rethinking the field of automatic prediction of court decisions

Masha Medvedeva; Martijn Wieling; Michel Vols

doi:10.1007/s10506-021-09306-3

Rethinking the field of automatic prediction of court decisions

Masha Medvedeva^*
, Martijn Wieling
, Michel Vols

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

91 Citations (Scopus)

276 Downloads (Pure)

Abstract

In this paper, we discuss previous research in automatic prediction of court decisions. We define the difference between outcome identification, outcome-based judgement categorisation and outcome forecasting, and review how various studies fall into these categories. We discuss how important it is to understand the legal data that one works with in order to determine which task can be performed. Finally, we reflect on the needs of the legal discipline regarding the analysis of court judgements.

Original language	English
Pages (from-to)	195–212
Journal	Artificial Intelligence and Law
Volume	31
Early online date	25-Jan-2022
DOIs	https://doi.org/10.1007/s10506-021-09306-3
Publication status	Published - 2023

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Rethinking the field of automatic prediction of court decisionsFinal publisher's version, 704 KBLicence: CC BY

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EVICT : The Impact of the International Right to Housing on National Legal Discourse: Using Data Science Techniques to Analyse Eviction Litigation
Vols, M. (PI), Wieling, M. (Researcher), Bruijn, M. (Postdoc), Hoops, B. (CoPI), Roorda, B. (Member), Mohammadi, M. (Postdoc), Quintiá Pastrana, A. (Postdoc), Whitehouse, L. (Advisor), Schmid, C. (Advisor), van Dijck, G. (Advisor), Arts, K. (Advisor), Prakken, H. (Advisor), de Vries, J. (Advisor) & Zauner-Lohmeyer, K. (Advisor)
01/01/2021 → …
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Rethinking the field of automatic prediction of court decisions

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EVICT : The Impact of the International Right to Housing on National Legal Discourse: Using Data Science Techniques to Analyse Eviction Litigation

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