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The Administrative State and Artificial Intelligence: Toward an Internal Law of Administrative Algorithms
Abstract
The administrative state is gradually embracing artificial intelligence (AI) algorithms. The advent of the so-called automated state has raised concerns over accountability, transparency, and fairness and engendered proposals for legal regulation. Yet the notion that algorithms are not merely technical instruments but encode social behavior embedded in a bureaucratic context has largely been missing from the discourse. This Article identifies algorithms as sociotechnical systems embedded in an organizational context, which can function as bureaucratic governance instruments. It argues that external legal institutions, whether legislative endeavors or judicial review, lack the capacity, insight, and perspective to achieve meaningful accountability in reviewing the administrative use of AI algorithms.
The Article suggests moving beyond seeing algorithms as a distinct phenomenon to regulate, to a more holistic view of algorithms as a bureaucratic challenge, which entails confronting inconsistencies, inaccuracies, and administrative culture, while taking account of institutional design. By doing so, it follows in the footsteps of scholars of internal administrative law, comprising of the complex set of rules, guidelines, and procedures of the bureaucracy, and highlights internal governance as means of improving outcomes and ensuring accountability. It also discusses the points of contention and outlines the doctrinal questions of administrative law that are likely to occupy judges and lawyers when dealing with internal governance with AI in the government.
Concurrently, this Article uncovers the internal law of administrative algorithms, which is emerging from a set of informal documents developed in the federal government. The Article reviews this corpus and distills the main tenets of responsible and trustworthy AI that will guide how administrative agencies design and implement their AI systems in the foreseeable future and imbues general principles with actionable goals.
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