Accountable Artificial Intelligence: Holding Algorithms to Account.

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.

Reputation-Sourced Authority and the Prospect of Unchecked Bureaucratic Power.

We explore the democratic implications of a reputational account of bureaucratic authority. While an influential literature has examined the relevance of reputation-and mutual exchange between principals and agents in public organizations generally-the normative implications of these insights have largely escaped scrutiny. We discuss how reputation-building impacts both the ability and the motivation of principals to oversee administrative policymaking.

A Multidimensional Reputation Barometer for Public Agencies: A Validated Instrument.

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