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Distributed Governance Of Medical Ai, W. Nicholson Price Ii
Distributed Governance Of Medical Ai, W. Nicholson Price Ii
SMU Science and Technology Law Review
Artificial intelligence (AI) has the potential to democratize expertise in medicine, bring expertise previously limited to specialists to a variety of health-care settings. But AI can easily falter, and making sure that AI works well across that variety of settings is a challenging task. Centralized governance, such as review by the Food and Drug Administration, can only do so much, since system performance will depend on the particular health-care setting and how the AI system is integrated into setting-specific clinical workflows. This Essay presents the need for distributed governance, where some oversight tasks are undertaken in localized settings. It points …
Moving From Harm Mitigation To Affirmative Discrimination Mitigation: The Untapped Potential Of Artificial Intelligence To Fight School Segregation And Other Forms Of Racial Discrimination, Andrew Gall
Catholic University Journal of Law and Technology
No abstract provided.
Artificial Intelligence In Canadian Healthcare: Will The Law Protect Us From Algorithmic Bias Resulting In Discrimination?, Bradley Henderson, Colleen M. Flood, Teresa Scassa
Artificial Intelligence In Canadian Healthcare: Will The Law Protect Us From Algorithmic Bias Resulting In Discrimination?, Bradley Henderson, Colleen M. Flood, Teresa Scassa
Canadian Journal of Law and Technology
In this article, we canvas why AI may perpetuate or exacerbate extant discrimination through a review of the training, development, and implementation of healthcare-related AI applications and set out policy options to militate against such discrimination. The article is divided into eight short parts including this introduction. Part II focuses on explaining AI, some of its basic functions and processes, and its relevance to healthcare. In Part III, we define and explain the difference and relationship between algorithmic bias and data bias, both of which can result in discrimination in healthcare settings, and provide some prominent examples of healthcare-related AI …