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Full-Text Articles in Privacy Law

Problematic Interactions Between Ai And Health Privacy, W. Nicholson Price Ii Nov 2021

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 …


Legal Opacity: Artificial Intelligence’S Sticky Wicket, Charlotte A. Tschider Jan 2021

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 Jan 2021

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 …


Submission To The Toronto Police Services Board’S Use Of New Artificial Intelligence Technologies Policy- Leaf And The Citizen Lab, Suzie Dunn, Kristen Mj Thomasen, Kate Robertson, Pam Hrick, Cynthia Khoo, Rosel Kim, Ngozi Okidegbe, Christopher Parsons Jan 2021

Submission To The Toronto Police Services Board’S Use Of New Artificial Intelligence Technologies Policy- Leaf And The Citizen Lab, Suzie Dunn, Kristen Mj Thomasen, Kate Robertson, Pam Hrick, Cynthia Khoo, Rosel Kim, Ngozi Okidegbe, Christopher Parsons

Reports & Public Policy Documents

We write as a group of experts in the legal regulation of artificial intelligence (AI), technology-facilitated violence, equality, and the use of AI systems by law enforcement in Canada. We have experience working within academia and legal practice, and are affiliated with LEAF and the Citizen Lab who support this letter.

We reviewed the Toronto Police Services Board Use of New Artificial Intelligence Technologies Policy and provide comments and recommendations focused on the following key observations:

1. Police use of AI technologies must not be seen as inevitable
2. A commitment to protecting equality and human rights must be integrated …


Contracting For Algorithmic Accountability, Cary Coglianese, Erik Lampmann Jan 2021

Contracting For Algorithmic Accountability, Cary Coglianese, Erik Lampmann

All Faculty Scholarship

As local, state, and federal governments increase their reliance on artificial intelligence (AI) decision-making tools designed and operated by private contractors, so too do public concerns increase over the accountability and transparency of such AI tools. But current calls to respond to these concerns by banning governments from using AI will only deny society the benefits that prudent use of such technology can provide. In this Article, we argue that government agencies should pursue a more nuanced and effective approach to governing the governmental use of AI by structuring their procurement contracts for AI tools and services in ways that …