Law Commons^™

Meaningful Choice: A History Of Consent And Alternatives To The Consent Myth, Charlotte A. Tschider

Faculty Publications & Other Works

Although the first legal conceptions of commercial privacy were identified in Samuel Warren and Louis Brandeis’s foundational 1890 article, The Right to Privacy, conceptually, privacy has existed since as early as 1127 as a natural concern when navigating between personal and commercial spheres of life. As an extension of contract and tort law, two common relational legal models, U.S. privacy law emerged to buoy engagement in commercial enterprise, borrowing known legal conventions like consent and assent. Historically, however, international legal privacy frameworks involving consent ultimately diverged, with the European Union taking a more expansive view of legal justification for processing …

Legal Opacity: Artificial Intelligence’S Sticky Wicket, Charlotte A. Tschider

Faculty Publications & Other Works

Proponents of artificial intelligence (“AI”) transparency have carefully illustrated the many ways in which transparency may be beneficial to prevent safety and unfairness issues, to promote innovation, and to effectively provide recovery or support due process in lawsuits. However, impediments to transparency goals, described as opacity, or the “black-box” nature of AI, present significant issues for promoting these goals.

An undertheorized perspective on opacity is legal opacity, where competitive, and often discretionary legal choices, coupled with regulatory barriers create opacity. Although legal opacity does not specifically affect AI only, the combination of technical opacity in AI systems with legal opacity …

Ai's Legitimate Interest: Towards A Public Benefit Privacy Model, Charlotte A. Tschider

Faculty Publications & Other Works

Health data uses are on the rise. Increasingly more often, data are used for a variety of operational, diagnostic, and technical uses, as in the Internet of Health Things. Never has quality data been more necessary: large data stores now power the most advanced artificial intelligence applications, applications that may enable early diagnosis of chronic diseases and enable personalized medical treatment. These data, both personally identifiable and de-identified, have the potential to dramatically improve the quality, effectiveness, and safety of artificial intelligence.

Existing privacy laws do not 1) effectively protect the privacy interests of individuals and 2) provide the flexibility …