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Articles 1 - 5 of 5
Full-Text Articles in Physical Sciences and Mathematics
On Environmental, Climate Change & National Security Law, Mark P. Nevitt
On Environmental, Climate Change & National Security Law, Mark P. Nevitt
All Faculty Scholarship
This Article offers a new way to think about climate change. Two new climate change assessments — the 2018 Fourth National Climate Assessment (NCA) and the United Nations Intergovernmental Panel’s Special Report on Climate Change — prominently highlight climate change’s multifaceted national security risks. Indeed, not only is climate change a “super wicked” environmental problem, it also accelerates existing national security threats, acting as both a “threat accelerant” and “catalyst for conflict.” Further, climate change increases the intensity and frequency of extreme weather events while threatening nations’ territorial integrity and sovereignty through rising sea levels. It causes both internal displacement …
Environmental Soft Law As A Governance Strategy, Cary Coglianese
Environmental Soft Law As A Governance Strategy, Cary Coglianese
All Faculty Scholarship
Soft law governance relies on nongovernmental institutions that establish and implement voluntary standards. Compared with traditional hard law solutions to societal and economic problems, soft law alternatives promise to be more politically feasible to establish and then easier to adapt in the face of changing circumstances. They may also seem more likely to be flexible in what they demand of targeted businesses and other entities. But can soft law actually work to solve major problems? This Article considers the value of soft law governance through the lens of three major voluntary, nongovernmental initiatives that address environmental concerns: (1) ISO 14001 …
Deploying Machine Learning For A Sustainable Future, Cary Coglianese
Deploying Machine Learning For A Sustainable Future, Cary Coglianese
All Faculty Scholarship
To meet the environmental challenges of a warming planet and an increasingly complex, high tech economy, government must become smarter about how it makes policies and deploys its limited resources. It specifically needs to build a robust capacity to analyze large volumes of environmental and economic data by using machine-learning algorithms to improve regulatory oversight, monitoring, and decision-making. Three challenges can be expected to drive the need for algorithmic environmental governance: more problems, less funding, and growing public demands. This paper explains why algorithmic governance will prove pivotal in meeting these challenges, but it also presents four likely obstacles that …
Decarbonization In Democracy, Shelley Welton
Decarbonization In Democracy, Shelley Welton
All Faculty Scholarship
Conventional wisdom holds that democracy is structurally ill-equipped to confront climate change. As the story goes, because each of us tends to dismiss consequences that befall people in other places and in future times, “the people” cannot be trusted to craft adequate decarbonization policies, designed to reduce present-day, domestic carbon emissions. Accordingly, U.S. climate change policy has focused on technocratic fixes that operate predominantly through executive action to escape democratic politics — with vanishingly little to show for it after a change in presidential administration. To help craft a more durable U.S. climate change strategy, this Article scrutinizes the purported …
Regulation Of Algorithmic Tools In The United States, Christopher S. Yoo, Alicia Lai
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 …