Out of their minds: legal theory in neural networks

Author: Hunter, D.

Source: Artificial Intelligence and Law, Volume 7, Number 2-3, September 1999 , pp. 129-151(23)

Publisher: Springer

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Abstract:

This paper examines the use of connectionism (neural networks) in modelling legal reasoning. I discuss how the implementations of neural networks have failed to account for legal theoretical perspectives on adjudication. I criticise the use of neural networks in law, not because connectionism is inherently unsuitable in law, but rather because it has been done so poorly to date. The paper reviews a number of legal theories which provide a grounding for the use of neural networks in law. It then examines some implementations undertaken in law and criticises their legal theoretical naïvete. It then presents a lessons from the implementations which researchers must bear in mind if they wish to build neural networks which are justified by legal theories.

Keywords: connectionism; legal philosophy; legal theory; neural networks

Document Type: Regular Paper

Affiliations: Law School, University of Melbourne, Australia Tel.: +61 (0) 3 9344 8923; E-mail: d.hunter@law.unimelb.edu.au

Publication date: September 1, 1999

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