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Full-Text Articles in Law
Algorithmic Governance From The Bottom Up, Hannah Bloch-Wehba
Algorithmic Governance From The Bottom Up, Hannah Bloch-Wehba
Faculty Scholarship
Artificial intelligence and machine learning are both a blessing and a curse for governance. In theory, algorithmic governance makes government more efficient, more accurate, and more fair. But the emergence of automation in governance also rests on public-private collaborations that expand both public and private power, aggravate transparency and accountability gaps, and create significant obstacles for those seeking algorithmic justice. In response, a nascent body of law proposes technocratic policy changes to foster algorithmic accountability, ethics, and transparency.
This Article examines an alternative vision of algorithmic governance, one advanced primarily by social and labor movements instead of technocrats and firms. …
Content Moderation As Surveillance, Hannah Bloch-Wehba
Content Moderation As Surveillance, Hannah Bloch-Wehba
Faculty Scholarship
Technology platforms are the new governments, and content moderation is the new law, or so goes a common refrain. As platforms increasingly turn toward new, automated mechanisms of enforcing their rules, the apparent power of the private sector seems only to grow. Yet beneath the surface lies a web of complex relationships between public and private authorities that call into question whether platforms truly possess such unilateral power. Law enforcement and police are exerting influence over platform content rules, giving governments a louder voice in supposedly “private” decisions. At the same time, law enforcement avails itself of the affordances of …
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 …
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 …
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.