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Full-Text Articles in Law
Comments Of The Cordell Institute On Ai Accountability, Neil M. Richards, Woodrow Hartzog, Jordan Francis
Comments Of The Cordell Institute On Ai Accountability, Neil M. Richards, Woodrow Hartzog, Jordan Francis
Scholarship@WashULaw
These comments are a response to the National Telecommunications and Information Administration's 2023 request for comment on AI accountability (AI Accountability RFC, NTIA–2023–0005).
Responding to NTIA’s recent inquiry into AI assurance and accountability, we offer two main arguments regarding the importance of substantive legal protections. First, a myopic focus on concepts of transparency, bias mitigation, and ethics (for which procedural compliance efforts such as audits, assessments, and certifications are proxies) is insufficient when it comes to the design and implementation of accountable AI systems. We call rules built around transparency and bias mitigation “AI half-measures,” because they provide the appearance …
Securitizing Digital Debts, Christopher K. Odinet
Securitizing Digital Debts, Christopher K. Odinet
Faculty Scholarship
The promise of financial technology (“fintech”) and artificial intelligence (“AI”) in broadening access to financial products and services continues to capture the imagination of policymakers, Wall Street, and the public. This has been particularly true in the realm of fintech credit where platform companies increasingly provide online loans to consumers, students, and small businesses by harnessing AI underwriting and alternative data. In 2019 alone fintech lenders represented nearly 50% of total non-credit card, unsecured consumer loan balances in the United States. One of the most prevalent ways fintech credit firms operate is by securitizing the online loans they help originate. …
Data-Informed Duties In Ai Development, Frank A. Pasquale
Data-Informed Duties In Ai Development, Frank A. Pasquale
Faculty Scholarship
Law should help direct—and not merely constrain—the development of artificial intelligence (AI). One path to influence is the development of standards of care both supplemented and informed by rigorous regulatory guidance. Such standards are particularly important given the potential for inaccurate and inappropriate data to contaminate machine learning. Firms relying on faulty data can be required to compensate those harmed by that data use—and should be subject to punitive damages when such use is repeated or willful. Regulatory standards for data collection, analysis, use, and stewardship can inform and complement generalist judges. Such regulation will not only provide guidance to …
Substantiating Big Data In Health Care, Nathan Cortez
Substantiating Big Data In Health Care, Nathan Cortez
Faculty Journal Articles and Book Chapters
Predictive analytics and "big data" are emerging as important new tools for diagnosing and treating patients. But as data collection becomes more pervasive, and as machine learning and analytical methods become more sophisticated, the companies that traffic in health-related big data will face competitive pressures to make more aggressive claims regarding what their programs can predict. Already, patients, practitioners, and payors are inundated with claims that software programs, "apps," and other forms of predictive analytics can help solve some of the health care system's most pressing problems. This article considers the evidence and substantiation that we should require of these …