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Problematic Interactions Between Ai And Health Privacy, W. Nicholson Price Ii

Articles

Problematic Interactions Between AI and Health Privacy Nicholson Price, University of Michigan Law SchoolFollow Abstract The interaction of artificial intelligence (AI) and health privacy is a two-way street. Both directions are problematic. This Essay makes two main points. First, the advent of artificial intelligence weakens the legal protections for health privacy by rendering deidentification less reliable and by inferring health information from unprotected data sources. Second, the legal rules that protect health privacy nonetheless detrimentally impact the development of AI used in the health system by introducing multiple sources of bias: collection and sharing of data by a small set …

How Can I Tell If My Algorithm Was Reasonable?, Karni A. Chagal-Feferkorn

Michigan Technology Law Review

Self-learning algorithms are gradually dominating more and more aspects of our lives. They do so by performing tasks and reaching decisions that were once reserved exclusively for human beings. And not only that—in certain contexts, their decision-making performance is shown to be superior to that of humans. However, as superior as they may be, self-learning algorithms (also referred to as artificial intelligence (AI) systems, “smart robots,” or “autonomous machines”) can still cause damage.

When determining the liability of a human tortfeasor causing damage, the applicable legal framework is generally that of negligence. To be found negligent, the tortfeasor must have …

Natural Language Processing For Lawyers And Judges, Frank Fagan

Michigan Law Review

A Review of Law as Data: Computation, Text, & the Future of Legal Analysis. Edited by Michael A. Livermore and Daniel N. Rockmore.

Problematic Interactions Between Ai And Health Privacy, W. Nicholson Price Ii

Law & Economics Working Papers

The interaction of artificial intelligence (“AI”) and health privacy is a two-way street. Both directions are problematic. This Article makes two main points. First, the advent of artificial intelligence weakens the legal protections for health privacy by rendering deidentification less reliable and by inferring health information from unprotected data sources. Second, the legal rules that protect health privacy nonetheless detrimentally impact the development of AI used in the health system by introducing multiple sources of bias: collection and sharing of data by a small set of entities, the process of data collection while following privacy rules, and the use of …

New Innovation Models In Medical Ai, Nicholson Price Ii, Rachel Sachs, Rebecca S. Eisenberg

Law & Economics Working Papers

In recent years, scientists and researchers have devoted considerable resources to developing medical artificial intelligence (AI) technologies. Many of these technologies—particularly those which resemble traditional medical devices in their functions—have received substantial attention in the legal and policy literature. But other types of novel AI technologies, such as those that relate to quality improvement and optimizing use of scarce facilities, have been largely absent from the discussion thus far. These AI innovations have the potential to shed light on important aspects of health innovation policy. First, these AI innovations interact less with the legal regimes that scholars traditionally conceive of …

From Automation To Autonomy: Legal And Ethical Responsibility Gaps In Artificial Intelligence Innovation, David Nersessian, Ruben Mancha

Michigan Technology Law Review

The increasing prominence of artificial intelligence (AI) systems in daily life and the evolving capacity of these systems to process data and act without human input raise important legal and ethical concerns. This article identifies three primary AI actors in the value chain (innovators, providers, and users) and three primary types of AI (automation, augmentation, and autonomy). It then considers responsibility in AI innovation from two perspectives: (i) strict liability claims arising out of the development, commercialization, and use of products with built-in AI capabilities (designated herein as “AI artifacts”); and (ii) an original research study on the ethical practices …