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Artificial Intelligence and Robotics

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Administrative Law In The Automated State, Cary Coglianese Jan 2021

Administrative Law In The Automated State, Cary Coglianese

All Faculty Scholarship

In the future, administrative agencies will rely increasingly on digital automation powered by machine learning algorithms. Can U.S. administrative law accommodate such a future? Not only might a highly automated state readily meet longstanding administrative law principles, but the responsible use of machine learning algorithms might perform even better than the status quo in terms of fulfilling administrative law’s core values of expert decision-making and democratic accountability. Algorithmic governance clearly promises more accurate, data-driven decisions. Moreover, due to their mathematical properties, algorithms might well prove to be more faithful agents of democratic institutions. Yet even if an automated state were …


Could A Robot Be District Attorney?, Stephen E. Henderson Jun 2019

Could A Robot Be District Attorney?, Stephen E. Henderson

Stephen E Henderson

No abstract provided.


Artificial Intelligence And Role-Reversible Judgment, Stephen E. Henderson, Kiel Brennan-Marquez Dec 2017

Artificial Intelligence And Role-Reversible Judgment, Stephen E. Henderson, Kiel Brennan-Marquez

Stephen E Henderson

As intelligent machines begin more generally outperforming human experts, why should humans remain ‘in the loop’ of decision-making?  One common answer focuses on outcomes: relying on intuition and experience, humans are capable of identifying interpretive errors—sometimes disastrous errors—that elude machines.  Though plausible today, this argument will wear thin as technology evolves.

Here, we seek out sturdier ground: a defense of human judgment that focuses on the normative integrity of decision-making.  Specifically, we propose an account of democratic equality as ‘role-reversibility.’  In a democracy, those tasked with making decisions should be susceptible, reciprocally, to the impact of decisions; there ought to …