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Full-Text Articles in Law

Ai In Adjudication And Administration, Cary Coglianese, Lavi M. Ben Dor Jul 2021

Ai In Adjudication And Administration, Cary Coglianese, Lavi M. Ben Dor

Faculty Scholarship at Penn Law

The use of artificial intelligence has expanded rapidly in recent years across many aspects of the economy. For federal, state, and local governments in the United States, interest in artificial intelligence has manifested in the use of a series of digital tools, including the occasional deployment of machine learning, to aid in the performance of a variety of governmental functions. In this paper, we canvas the current uses of such digital tools and machine-learning technologies by the judiciary and administrative agencies in the United States. Although we have yet to see fully automated decision-making find its way into either adjudication ...


Administrative Law In The Automated State, Cary Coglianese Apr 2021

Administrative Law In The Automated State, Cary Coglianese

Faculty Scholarship at Penn Law

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 ...


Contracting For Algorithmic Accountability, Cary Coglianese, Erik Lampmann Jan 2021

Contracting For Algorithmic Accountability, Cary Coglianese, Erik Lampmann

Faculty Scholarship at Penn Law

As local, state, and federal governments increase their reliance on artificial intelligence (AI) decision-making tools designed and operated by private contractors, so too do public concerns increase over the accountability and transparency of such AI tools. But current calls to respond to these concerns by banning governments from using AI will only deny society the benefits that prudent use of such technology can provide. In this Article, we argue that government agencies should pursue a more nuanced and effective approach to governing the governmental use of AI by structuring their procurement contracts for AI tools and services in ways that ...


Deploying Machine Learning For A Sustainable Future, Cary Coglianese May 2020

Deploying Machine Learning For A Sustainable Future, Cary Coglianese

Faculty Scholarship at Penn Law

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 Jan 2020

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

Faculty Scholarship at Penn Law

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 ...


Transparency And Algorithmic Governance, Cary Coglianese, David Lehr Jan 2019

Transparency And Algorithmic Governance, Cary Coglianese, David Lehr

Faculty Scholarship at Penn Law

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 ...


The Tao Of The Dao: Taxing An Entity That Lives On A Blockchain, David J. Shakow Aug 2018

The Tao Of The Dao: Taxing An Entity That Lives On A Blockchain, David J. Shakow

Faculty Scholarship at Penn Law

In this report, Shakow explains how a decentralized autonomous organization functions and interacts with the U.S. tax system and presents the many tax issues that these structures raise. The possibility of using smart contracts to allow an entity to operate totally autonomously on a blockchain platform seems attractive. However, little thought has been given to how such an entity can comply with the requirements of a tax system. The DAO, the first major attempt to create such an organization, failed because of a programming error. If successful examples proliferate in the future, tax authorities will face significant problems in ...


Regulating By Robot: Administrative Decision Making In The Machine-Learning Era, Cary Coglianese, David Lehr Jun 2017

Regulating By Robot: Administrative Decision Making In The Machine-Learning Era, Cary Coglianese, David Lehr

Faculty Scholarship at Penn Law

Machine-learning algorithms are transforming large segments of the economy, underlying everything from product marketing by online retailers to personalized search engines, and from advanced medical imaging to the software in self-driving cars. As machine learning’s use has expanded across all facets of society, anxiety has emerged about the intrusion of algorithmic machines into facets of life previously dependent on human judgment. Alarm bells sounding over the diffusion of artificial intelligence throughout the private sector only portend greater anxiety about digital robots replacing humans in the governmental sphere. A few administrative agencies have already begun to adopt this technology, while ...