The ghost in the legal machine : algorithmic governmentality, economy, and the practice of law

Harkens, Adam (2018) The ghost in the legal machine : algorithmic governmentality, economy, and the practice of law. Journal of Information, Communication and Ethics in Society, 16 (1). pp. 16-31. ISSN 1477-996X (https://doi.org/10.1108/JICES-09-2016-0038)

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Abstract

Purpose: This paper aims to investigate algorithmic governmentality – as proposed by Antoinette Rouvroy – specifically in relation to law. It seeks to show how algorithmic profiling can be particularly attractive for those in legal practice, given restraints on time and resources. It deviates from Rouvroy in two ways. First, it argues that algorithmic governmentality does not contrast with neoliberal modes of government in that it allows indirect rule through economic calculations. Second, it argues that critique of such systems is possible, especially if the creative nature of law can be harnessed effectively. Design/methodology/approach: This is a conceptual paper, with a theory-based approach, that is intended to explore relevant issues related to algorithmic governmentality as a basis for future empirical research. It builds on governmentality and socio-legal studies, as well as research on algorithmic practices and some documentary analysis of reports and public-facing marketing of relevant technologies. Findings: This paper provides insights on how algorithmic knowledge is collected, constructed and applied in different situations. It provides examples of how algorithms are currently used and how trends are developing. It demonstrates how such uses can be informed by socio-political and economic rationalities. Research limitations/implications: Further empirical research is required to test the theoretical findings. Originality/value : This paper takes up Rouvroy’s question of whether we are at the end(s) of critique and seeks to identify where such critique can be made possible. It also highlights the importance of acknowledging the role of political rationalities in informing the activity of algorithmic assemblages.