Implementing and managing Algorithmic Decision-Making in the public sector

This paper examines the current evolution of Artificial Intelligence (AI) systems for “algorithmic decision-making” (ADM) in the public sector (§1). In particular, it will focus on the challenges brought by such new uses of AI in the field of governance and public administration. From a review of the rising global scholarship on the matter, three strands of research are hereby expanded. First, the technical approach (§2). To close the gaps between law, policy and technology, it is indeed necessary to understand what an AI system is and why and how it can affect decision-making. Second, the legal and “algor-ethical” approach (§3). This is aimed at showing the big picture wherein the governance concerns arise – namely, the wider framework of principles and key-practices needed to secure a good use of AI in the public sector against its potential risks and misuses. Third, as the core subject of this analysis, the governance approach stricto sensu (§4). This aims to trace back the renowned issue of the “governance of AI” to essentially four major sets of challenges which ADM poses in the public management chain: (i) defining clear goals and responsibilities; (ii) gaining competency and knowledge; (iii) managing and involving stakeholders; (iv) managing and auditing risks.