Accountable Artificial Intelligence: Holding Algorithms to Account

By Madalina Busuioc. PAR. Public Administration Review, 2020

433 citations recorded by the source corpus.

Abstract Artificial intelligence (AI) algorithms govern in subtle yet fundamental ways the way we live and are transforming our societies. The promise of efficient, low‐cost, or “neutral” solutions harnessing the potential of big data has led public bodies to adopt algorithmic systems in the provision of public services. As AI algorithms have permeated high‐stakes aspects of our public existence—from hiring and education decisions to the governmental use of enforcement powers (policing) or liberty‐restricting decisions (bail and sentencing)—this necessarily raises important accountability questions: What accountability challenges do AI algorithmic systems bring with them, and how can we safeguard accountability in algorithmic decision‐making? Drawing on a decidedly public administration perspective, and given the current challenges that have thus far become manifest in the field, we critically reflect on and map out in a conceptually guided manner the implications of these systems, and the limitations they pose, for public accountability.

Subfields: Artificial Intelligence, Health Informatics, Safety Research

View Paper: https://www.semanticscholar.org/paper/2a36e7eb3c5da0581fcb917c64169fd7bcfb79f2

Citations in the corpus

• Accountability in artificial intelligence: what it is and how it works (2023, neutral): “Poor administration of these problems causes two opposite effects: accountability gaps , where no one is held accountable, or accountability surpluses , where procedures are inefficiently accumulated (Bovens 2007; Busuioc 2021).”