Social and Behavioral Sciences Commons^™

The U.S. Endangered Species Act And Agency Discretion: The Role Of Public Commenting During The Rulemaking Process, Krista Helmstadter Lyons

Boise State University Theses and Dissertations

The most recent International Union for Conservation of Nature (IUCN) Red List classifies 40,084 out of the 142,577 evaluated species as threatened with extinction, with 1,962 of those species identified in the United States. The U.S. Endangered Species Act (ESA) was enacted in 1973 to protect and recover threatened and endangered species from extinction. The ESA federal listing process can be lengthy and arduous, taking years for a species to be proposed for listing. During the process the U.S. Fish and Wildlife Service (FWS) seeks comments from the public and peer reviewers on the proposed rule. Previous research debates the …

Moving Toward Personalized Law, Cary Coglianese

All Faculty Scholarship

Rules operate as a tool of governance by making generalizations, thereby cutting down on government officials’ need to make individual determinations. But because they are generalizations, rules can result in inefficient or perverse outcomes due to their over- and under-inclusiveness. With the aid of advances in machine-learning algorithms, however, it is becoming increasingly possible to imagine governments shifting away from a predominant reliance on general rules and instead moving toward increased reliance on precise individual determinations—or on “personalized law,” to use the term Omri Ben-Shahar and Ariel Porat use in the title of their 2021 book. Among the various technological, …

Algorithm Vs. Algorithm, Cary Coglianese, Alicia Lai

All Faculty Scholarship

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, …

Regulating New Tech: Problems, Pathways, And People, Cary Coglianese

All Faculty Scholarship

New technologies bring with them many promises, but also a series of new problems. Even though these problems are new, they are not unlike the types of problems that regulators have long addressed in other contexts. The lessons from regulation in the past can thus guide regulatory efforts today. Regulators must focus on understanding the problems they seek to address and the causal pathways that lead to these problems. Then they must undertake efforts to shape the behavior of those in industry so that private sector managers focus on their technologies’ problems and take actions to interrupt the causal pathways. …

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 …

Regulation Of Algorithmic Tools In The United States, Christopher S. Yoo, Alicia Lai

All Faculty Scholarship

Policymakers in the United States have just begun to address regulation of artificial intelligence technologies in recent years, gaining momentum through calls for additional research funding, piece-meal guidance, proposals, and legislation at all levels of government. This Article provides an overview of high-level federal initiatives for general artificial intelligence (AI) applications set forth by the U.S. president and responding agencies, early indications from the incoming Biden Administration, targeted federal initiatives for sector-specific AI applications, pending federal legislative proposals, and state and local initiatives. The regulation of the algorithmic ecosystem will continue to evolve as the United States continues to search …

Transparency And Algorithmic Governance, Cary Coglianese, David Lehr

All Faculty Scholarship

Machine-learning algorithms are improving and automating important functions in medicine, transportation, and business. Government officials have also started to take notice of the accuracy and speed that such algorithms provide, increasingly relying on them to aid with consequential public-sector functions, including tax administration, regulatory oversight, and benefits administration. Despite machine-learning algorithms’ superior predictive power over conventional analytic tools, algorithmic forecasts are difficult to understand and explain. Machine learning’s “black-box” nature has thus raised concern: Can algorithmic governance be squared with legal principles of governmental transparency? We analyze this question and conclude that machine-learning algorithms’ relative inscrutability does not pose a …

Why Law Now Needs To Control Rather Than Follow Neo-Classical Economics, John William Draper

Librarian Scholarship at Penn Law

Selfish utilitarianism, neo-classical economics, the directive of short-term income maximization, and the decision tool of cost-benefit analysis fail to protect our species from the significant risks of too much consumption, pollution, or population. For a longer-term survival, humanity needs to employ more than cost-justified precaution.

This article argues that, at the global level, and by extension at all levels of government, we need to replace neo-classical economics with filters for safety and feasibility to regulate against significant risk. For significant risks, especially those that are irreversible, we need decision tools that will protect humanity at all scales. This article describes …

A Framework For Understanding Property Regulation And Land Use Control From A Dynamic Perspective, Donald J. Kochan

Donald J. Kochan

Book Review, Scott Hogan

RISK: Health, Safety & Environment (1990-2002)

Review of: ROBERT A. SHANLEY, PRESIDENTIAL INFLUENCE AND ENVIRONMENTAL POLICY. (Greenwood Press, 1992) [163 pp.] Abbreviations, acknowledgements, index, introduction, notes, selected bibliography. LC 92-15584; ISBN 0-313-25883-X. [$45.00 cloth. 88 Post Road West; Westport CT 06881.]

Restoring Faith In Natural Resource Policy-Making: Incorporating Direct Participation Through Alternative Dispute Resolution Processes, Kaleen Cottingham, University Of Colorado Boulder. Natural Resources Law Center

Books, Reports, and Studies

8 p. ; 28 cm