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Risk assessment

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Full-Text Articles in Social and Behavioral Sciences

From Negative To Positive Algorithm Rights, Cary Coglianese, Kat Hefter Jan 2022

From Negative To Positive Algorithm Rights, Cary Coglianese, Kat Hefter

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Artificial intelligence, or “AI,” is raising alarm bells. Advocates and scholars propose policies to constrain or even prohibit certain AI uses by governmental entities. These efforts to establish a negative right to be free from AI stem from an understandable motivation to protect the public from arbitrary, biased, or unjust applications of algorithms. This movement to enshrine protective rights follows a familiar pattern of suspicion that has accompanied the introduction of other technologies into governmental processes. Sometimes this initial suspicion of a new technology later transforms into widespread acceptance and even a demand for its use. In this paper, we …


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

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

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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 …


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

Deploying Machine Learning For A Sustainable Future, Cary Coglianese

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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 …


Risk Equity: A New Proposal, Matthew D. Adler Jan 2008

Risk Equity: A New Proposal, Matthew D. Adler

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What does distributive justice require of risk regulators? Various executive orders enjoin health and safety regulators to take account of “distributive impacts,” “equity,” or “environmental justice,” and many scholars endorse these requirements. But concrete methodologies for evaluating the equity effects of risk regulation policies remain undeveloped. The contrast with cost-benefit analysis--now a very well developed set of techniques --is stark. Equity analysis by governmental agencies that regulate health and safety risks, at least in the United States, lacks rigor and structure. This Article proposes a rigorous framework for risk-equity analysis, which I term “probabilistic population profile analysis” (PPPA). PPPA is …


Policy Analysis For Natural Hazards: Some Cautionary Lessons From Environmental Policy Analysis, Matthew D. Adler Nov 2006

Policy Analysis For Natural Hazards: Some Cautionary Lessons From Environmental Policy Analysis, Matthew D. Adler

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How should agencies and legislatures evaluate possible policies to mitigate the impacts of earthquakes, floods, hurricanes and other natural hazards? In particular, should governmental bodies adopt the sorts of policy-analytic and risk assessment techniques that are widely used in the area of environmental hazards (chemical toxins and radiation)? Environmental hazards policy analysis regularly employs proxy tests, in particular tests of technological “feasibility,” rather than focusing on a policy’s impact on well-being. When human welfare does enter the analysis, particular aspects of well-being, such as health and safety, are often given priority over others. “Individual risk” tests and other features of …