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Physical Sciences and Mathematics Commons

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Theory and Algorithms

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Machine learning

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Full-Text Articles in Physical Sciences and Mathematics

Regulating Machine Learning: The Challenge Of Heterogeneity, Cary Coglianese Feb 2023

Regulating Machine Learning: The Challenge Of Heterogeneity, Cary Coglianese

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Machine learning, or artificial intelligence, refers to a vast array of different algorithms that are being put to highly varied uses, including in transportation, medicine, social media, marketing, and many other settings. Not only do machine-learning algorithms vary widely across their types and uses, but they are evolving constantly. Even the same algorithm can perform quite differently over time as it is fed new data. Due to the staggering heterogeneity of these algorithms, multiple regulatory agencies will be needed to regulate the use of machine learning, each within their own discrete area of specialization. Even these specialized expert agencies, though, …


Algorithm Vs. Algorithm, Cary Coglianese, Alicia Lai Jan 2022

Algorithm Vs. Algorithm, Cary Coglianese, Alicia Lai

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Critics raise alarm bells about governmental use of digital algorithms, charging that they are too complex, inscrutable, and prone to bias. A realistic assessment of digital algorithms, though, must acknowledge that government is already driven by algorithms of arguably greater complexity and potential for abuse: the algorithms implicit in human decision-making. The human brain operates algorithmically through complex neural networks. And when humans make collective decisions, they operate via algorithms too—those reflected in legislative, judicial, and administrative processes. Yet these human algorithms undeniably fail and are far from transparent. On an individual level, human decision-making suffers from memory limitations, fatigue, …


From Negative To Positive Algorithm Rights, Cary Coglianese, Kat Hefter Jan 2022

From Negative To Positive Algorithm Rights, Cary Coglianese, Kat Hefter

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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 …