From the abstract of Mariano-Florentino Cuéllar’s Cyberdelegation and the Administrative State:
This paper explores questions and trade-offs associated with delegating administrative agency decisions to computer algorithms, neural networks, and similar examples of “artificial intelligence,” and offers the following preliminary observations to further discussion of the opportunities and risks. First, neither conventional expert systems nor neural networks (or other machine learning mechanisms) are in a position to resolve (without human intervention) context-specific debates about society’s goals for regulation or administrative adjudication – and these debates are often inherent in the implementation of statutes. Those goals must also inform whether we assign value to aspects of human cognition that contrast with what computers can (presently) accomplish, or what might be conventionally defined as rational in a decision-theoretic sense. Second, society must consider path-dependent consequences and associated cybersecurity risks that could arise from reliance on computers to make and support decisions. Such consequences include the erosion of individual and organizational knowledge over time. Third, it may prove difficult to limit the influence of computer programs even if they are meant to be mere decision support tools rather than the actual means of making a decision. Finally, heavy reliance on computer programs – particularly adaptive ones that modify themselves over time – may further complicate public deliberation about administrative decisions, because few if any observers will be entirely capable of understanding how a given decision was reached.