Publication | Open Access
The ‘rule of law’ implications of data-driven decision-making: a techno-regulatory perspective
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2018
Year
Human BehaviourEngineeringLawMoral EnterpriseData-driven InnovationTechnology LawData ScienceManagementData-driven Decision MakingData IntegrationData GovernanceData ManagementDecision TheoryPublic PolicyRule LawDecision Support SystemsTechnology PolicyInformation ManagementAutomated Decision-makingTechno-regulatory PerspectiveResponsible Data ManagementDecision-makingData Practice‘ RuleData-driven Decision-makingDecision ScienceRegulationDecision Technology
Techno‑regulation, particularly data‑driven automated decision‑making, is reshaping public‑sector governance but creates tensions with the rule of law’s demand for clear, normative, and accountable processes. The paper examines how such data‑driven ADM challenges the rule of law by undermining its normative, causative, and moral foundations.
Techno-regulation is a prominent mechanism for regulating human behaviour. One type of techno-regulation concerns automated decision-making with legal effects. While automated decision-making (ADM) systems in the public domain have traditionally been based on conscious design of decisional norms, increasingly, Data Science methodologies are used to devise these norms. This data-driven approach causes frictions with the underlying principle of public-sector decision-making, namely adherence to the rule of law. In this paper we discuss three major challenges data-driven ADM poses to the Rule Law: law as a normative enterprise, law as a causative enterprise and law as a moral enterprise.