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Articles 1 - 3 of 3
Full-Text Articles in Law
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 …
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 …
Transactional Scripts In Contract Stacks, Shaanan Cohney, David A. Hoffman
Transactional Scripts In Contract Stacks, Shaanan Cohney, David A. Hoffman
All Faculty Scholarship
Deals accomplished through software persistently residing on computer networks—sometimes called smart contracts, but better termed transactional scripts—embody a potentially revolutionary contracting innovation. Ours is the first precise account in the legal literature of how such scripts are created, and when they produce errors of legal significance.
Scripts’ most celebrated use case is for transactions operating exclusively on public, permissionless, blockchains: such exchanges eliminate the need for trusted intermediaries and seem to permit parties to commit ex ante to automated performance. But public transactional scripts are costly both to develop and execute, with significant fees imposed for data storage. Worse, bugs …