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Regulating New Tech: Problems, Pathways, And People, Cary Coglianese
Regulating New Tech: Problems, Pathways, And People, Cary Coglianese
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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. …
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
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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
Transparency And Algorithmic Governance, Cary Coglianese, David Lehr
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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 …
Optimizing Government For An Optimizing Economy, Cary Coglianese
Optimizing Government For An Optimizing Economy, Cary Coglianese
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Much entrepreneurial growth in the United States today emanates from technological advances that optimize through contextualization. Innovations as varied as Airbnb and Uber, fintech firms and precision medicine, are transforming major sectors in the economy by customizing goods and services as well as refining matches between available resources and interested buyers. The technological advances that make up the optimizing economy create new challenges for government oversight of the economy. Traditionally, government has overseen economic activity through general regulations that aim to treat all individuals equally; however, in the optimizing economy, business is moving in the direction of greater individualization, not …