Algorithmic accountability in public administration: the GDPR paradox

Abstract

The EU General Data Protection Regulation ("GDPR") is often represented as a larger than life behemoth that will fundamentally transform the world of big data. Abstracted from its constituent parts of corresponding rights, responsibilities, and exemptions, the operative scope of the GDPR can be unduly aggrandized, when in reality, it caters to the specific policy objectives of legislators and institutional stakeholders. With much uncertainty ahead on the precise implementation of the GDPR, academic and policy discussions are debating the adequacy of protections for automated decision-making in GDPR Articles 13 (right to be informed of automated treatment), 15 (right of access by the data subject), and 22 (safeguards to profiling). Unfortunately, the literature to date disproportionately focuses on the impact of AI in the private sector, and deflects any extensive review of automated enforcement tools in public administration. Even though the GDPR enacts significant safeguards against automated decisions, it does so with deliberate design: to balance the interests of data protection with the growing demand for algorithms in the administrative state. In order to facilitate inter-agency data flows and sensitive data processing that fuel the predictive power of algorithmic enforcement tools, the GDPR decisively surrenders to the procedural autonomy of Member States to authorize these practices. Yet, due to a dearth of research on the GDPR's stance on government deployed algorithms, it is not widely known that public authorities can benefit from broadly worded exemptions to restrictions on automated decision-making, and even circumvent remedies for data subjects through national legislation. The potential for public authorities to invoke derogations from the GDPR must be contained by the fundamental guarantees of due process, judicial review, and equal treatment. This paper examines the interplay of these principles within the prospect of algorithmic decision-making by public authorities.