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Human-Centered Design To Address Biases In Artificial Intelligence, Ellen W. Clayton, You Chen, Laurie L. Novak, Shilo Anders, Bradley Malin
Human-Centered Design To Address Biases In Artificial Intelligence, Ellen W. Clayton, You Chen, Laurie L. Novak, Shilo Anders, Bradley Malin
Vanderbilt Law School Faculty Publications
The potential of artificial intelligence (AI) to reduce health care disparities and inequities is recognized, but it can also exacerbate these issues if not implemented in an equitable manner. This perspective identifies potential biases in each stage of the AI life cycle, including data collection, annotation, machine learning model development, evaluation, deployment, operationalization, monitoring, and feedback integration. To mitigate these biases, we suggest involving a diverse group of stakeholders, using human-centered AI principles. Human-centered AI can help ensure that AI systems are designed and used in a way that benefits patients and society, which can reduce health disparities and inequities. …
Effectiveness Of The Epa's Regulatory Enforcement: The Case Of Industrial Effluent Standards, W. Kip Viscusi, Wesley A. Magat
Effectiveness Of The Epa's Regulatory Enforcement: The Case Of Industrial Effluent Standards, W. Kip Viscusi, Wesley A. Magat
Vanderbilt Law School Faculty Publications
The EPA water pollution regulations-the focus of this study- represent an interesting departure from past patterns of regulatory failure. First, the nature of the regulations-discharge limits-relates directly to the policy objective of controlling pollution, and there is no potential for offsetting behavioral responses. If the pollution standards are binding and enforced, they should improve water quality. Second, the enforcement effort is so extensive that enforcement should affect firms' compliance. In the pulp and paper industry, which we will analyze, the EPA averages roughly one inspection annually per major pollution source. In addition, firms are required to file monthly discharge monitoring …