Document Type
Article
Publication Date
2022
Abstract
Artificial intelligence, or “AI,” is raising alarm bells. Advocates and scholars propose policies to constrain or even prohibit certain AI uses by governmental entities. These efforts to establish a negative right to be free from AI stem from an understandable motivation to protect the public from arbitrary, biased, or unjust applications of algorithms. This movement to enshrine protective rights follows a familiar pattern of suspicion that has accompanied the introduction of other technologies into governmental processes. Sometimes this initial suspicion of a new technology later transforms into widespread acceptance and even a demand for its use. In this paper, we show how three now-accepted technologies—DNA analysis, breathalyzers, and radar speed detectors—traversed a path from initial resistance to a positive right that demands their use. We argue that current calls for a negative right to be free from digital algorithms may dissipate over time, with the public and the legal system eventually embracing, if not even demanding, the use of AI. Increased recognition that the human-based status quo itself leads to unacceptable errors and biases may contribute to this transformation. A negative rights approach, after all, may only hamper the development of technologies that could lead to improved governmental performance. If AI tools are allowed to mature and become more standardized, they may also be accompanied by greater reliance on qualified personnel, robust audits and assessments, and meaningful oversight. Such maturation in the use of AI tools may lead to demonstrable improvements over the status quo, which eventually might well justify assigning a positive right to their use in the performance of governmental tasks.
Keywords
Public administration, artificial intelligence, machine learning, algorithmic regulation, information technology, public administration, government regulation, criminal justice, law enforcement, risk assessment, public opinion
Publication Title
William & Mary Bill of Rights Journal
Repository Citation
Coglianese, Cary and Hefter, Kat, "From Negative to Positive Algorithm Rights" (2022). All Faculty Scholarship. 2914.
https://scholarship.law.upenn.edu/faculty_scholarship/2914
Included in
Administrative Law Commons, Artificial Intelligence and Robotics Commons, Constitutional Law Commons, Public Administration Commons, Science and Technology Studies Commons, Theory and Algorithms Commons
Publication Citation
30 Wm. & Mary Bill Rts. J. 883 (2022)