Law Commons^™

Frontiers In Precision Medicine Iv: Artificial Intelligence, Assembling Large Cohorts, And The Population Data Revolution, Adam Bress, Rich Albrechtsen, Monika Baker, Jorge L. Contreras, Zachary Fica, Austin Gamblin, Chelsea Ratcliff, Bianca E. Rich, Matt A. Szaniawski, Alyssa Thorman, Chad Vansant-Webb, Willard Dere

Utah Law Faculty Scholarship

Large cohort studies and more recently electronic medical records (EMR) are being used to collect massive amounts of genetic information. Implementation of artificial intelligence has become increasingly necessary to interpret this data with the goal of augmenting patient care. While it is impossible to predict what the future holds, policy makers are challenged to create guiding principles and responsibly roll out these new technologies. On March 22, 2019, the University of Utah hosted its fourth annual Precision Medicine Symposium focusing on artificial intelligence, assembling large cohorts, and the population data revolution. The symposium brought together experts in medicine, science, law …

How U.S. Government Policy Documents Are Addressing The Increasing National Security Implications Of Artificial Intelligence, Bert Chapman

Libraries Faculty and Staff Presentations

Artificial intelligence is affecting many areas of our lives and governmental policy. National security is one arena in which artificial intelligence is playing an increasingly important and controversial role. U.S. Government and military agencies are producing a steadily expanding corpus of publicly available literature on this topic. This literature documents how these agencies have this topic's national security implications historically and currently while also addressing potentially emerging national security issues where artificial intelligence will intersect with national security. This presentation demonstrates examples of the growing variety of publicly available national security artificial intelligence literature while also addressing the implications of …

Open Banking: Regulatory Challenges For A New Form Of Financial Intermediation In A Data-Driven World, Nydia Remolina

Centre for AI & Data Governance

Data has taken immense importance in the last years. Consider the amount of data that is being collected worldwide every day, industries are reshaping their activities into a data-driven business. The digital transformation of all industries, portent of the fourth industrial revolution, is creating a new kind of economy based on the datafication of almost any aspect of human social, political and economic activity as a result of the information generated by the numerous daily routines of digitally connected individuals and technology. The financial services industry is part of this trend. Embracing the digital revolution and creating the right foundations …

It's Not The Robot's Fault! Russian And American Perspectives On Responsibility For Robot Harms, Bryant Walker Smith, Andrey Neznamov

Faculty Publications

No abstract provided.

Ok, Google, Will Artificial Intelligence Replace Human Lawyering?, Amy Vorenberg, Julie A. Oseid, Melissa Love Koenig

Law Faculty Scholarship

Will Artificial Intelligence (AI) replace human lawyering? The answer is no. Despite worries that AI is getting so sophisticated that it could take over the profession, there is little cause for concern. Indeed, the surge of AI in the legal field has crystalized the real essence of effective lawyering. The lawyer’s craft goes beyond what AI can do because we listen with empathy to clients’ stories, strategize to find that story that might not be obvious, thoughtfully use our imagination and judgment to decide which story will appeal to an audience, and creatively tell those winning stories.

This article reviews …

Medical Ai And Contextual Bias, W. Nicholson Price Ii

Articles

Artificial intelligence will transform medicine. One particularly attractive possibility is the democratization of medical expertise. If black-box medical algorithms can be trained to match the performance of high-level human experts — to identify malignancies as well as trained radiologists, to diagnose diabetic retinopathy as well as board-certified ophthalmologists, or to recommend tumor-specific courses of treatment as well as top-ranked oncologists — then those algorithms could be deployed in medical settings where human experts are not available, and patients could benefit. But there is a problem with this vision. Privacy law, malpractice, insurance reimbursement, and FDA approval standards all encourage developers …

How To Address The Ai Governance Discussion? What Can We Learn From Singapore’S Ai Strategy?, Nydia Remolina Leon, Josephine Seah

Centre for AI & Data Governance

The following research piece explores how Singapore is addressing the AI Governance discussion. First, the document broadly provides some background to the Singapore’s AI strategy; second, it explains exactly what the Model AI Governance Framework is and how Singapore is addressing the AI Governance discussion; third, it compares Singapore’s approach with other jurisdictions’ and how important it is to contribute to the international debate on AI governance; and fourth, the document mentions some challenges ahead and observations on what is missing from current conversations about AI.

An Agent-Based Model Of Financial Benchmark Manipulation, Gabriel Virgil Rauterberg, Megan Shearer, Michael Wellman

Articles

Financial benchmarks estimate market values or reference rates used in a wide variety of contexts, but are often calculated from data generated by parties who have incentives to manipulate these benchmarks. Since the the London Interbank Offered Rate (LIBOR) scandal in 2011, market participants, scholars, and regulators have scrutinized financial benchmarks and the ability of traders to manipulate them. We study the impact on market quality and microstructure of manipulating transaction-based benchmarks in a simulated market environment. Our market consists of a single benchmark manipulator with external holdings dependent on the benchmark, and numerous background traders unaffected by the benchmark. …

Algorithms And Human Freedom, Richard Warner, Robert Sloan

All Faculty Scholarship

Predictive analytics such as data mining, machine learning, and artificial intelligence drive algorithmic decision making. Its "all-encompassing scope already reaches the very heart of a functioning society". Unfortunately, the legal system and its various tools developed around human decisionmakers cannot adequately administer accountability mechanisms for computer decision making. Antiquated approaches require modernization to bridge the gap between governing human decision making and new technologies. We divide the bridge-building task into three questions. First, what features of the use of predictive analytics significantly contribute to incorrect, unjustified, or unfair outcomes? Second, how should one regulate those features to make outcomes more …

Digital Market Perfection, Rory Van Loo

Faculty Scholarship

Google’s, Apple’s, and other companies’ automated assistants are increasingly serving as personal shoppers. These digital intermediaries will save us time by purchasing grocery items, transferring bank accounts, and subscribing to cable. The literature has only begun to hint at the paradigm shift needed to navigate the legal risks and rewards of this coming era of automated commerce. This Article begins to fill that gap first by surveying legal battles related to contract exit, data access, and deception that will determine the extent to which automated assistants are able to help consumers to search and switch, potentially bringing tremendous societal benefits. …

Rise Of The Robot Lawyers?, Milan Markovic

Faculty Scholarship

The advent of artificial intelligence has provoked considerable speculation about the future of the American workforce, including highly educated professionals such as lawyers and doctors. Although most commentators are alarmed by the prospect of intelligent machines displacing millions of workers, this is not so with respect to the legal sector. Media accounts and some legal scholars envision a future where intelligent machines perform the bulk of legal work, and legal services are less expensive and more accessible. This future is purportedly at hand as lawyers struggle to compete with technologically savvy alternative legal service providers.

This Article challenges the notion …

Artificial Intelligence In The Medical System: Four Roles For Potential Transformation, W. Nicholson Price Ii

Articles

Artificial intelligence (AI) looks to transform the practice of medicine. As academics and policymakers alike turn to legal questions, including how to ensure high-quality performance by medical AI, a threshold issue involves what role AI will play in the larger medical system. This Article argues that AI can play at least four distinct roles in the medical system, each potentially transformative: pushing the frontiers of medical knowledge to increase the limits of medical performance, democratizing medical expertise by making specialist skills more available to non-specialists, automating drudgery within the medical system, and allocating scarce medical resources. Each role raises its …

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 …

Artificial Intelligence And Law: An Overview, Harry Surden

Publications

Much has been written recently about artificial intelligence (AI) and law. But what is AI, and what is its relation to the practice and administration of law? This article addresses those questions by providing a high-level overview of AI and its use within law. The discussion aims to be nuanced but also understandable to those without a technical background. To that end, I first discuss AI generally. I then turn to AI and how it is being used by lawyers in the practice of law, people and companies who are governed by the law, and government officials who administer the …

Law's Halo And The Moral Machine, Bert I. Huang

Faculty Scholarship

How will we assess the morality of decisions made by artificial intelli­gence – and will our judgments be swayed by what the law says? Focusing on a moral dilemma in which a driverless car chooses to sacrifice its passenger to save more people, this study offers evidence that our moral intuitions can be influenced by the presence of the law.

Called To Serve: Elevating Human-Performed Caregiver And Volunteer Work In An Era Of Ai-Robotic Technologies, Hilary G. Escajeda

Journal Articles

Although the status quo of the traditional female caregiver has managed to muddle forward, it may begin to unwind as increasingly capable technologies dislodge humans from full-time employment and compel a redefinition of valuable work. Given this backdrop, this Essay seeks to open a dialogue for developing thoughtful, modem tax policies. Part I outlines the vocational endeavors of historically female community members who serve as caregivers and social volunteers. Next, Part II summarizes the economic value of volunteer and caregiver services. Part III examines whether tax policies should adopt a more expansive definition of beneficial occupations, as artificial intelligence (AI) …

Power, Process, And Automated Decision-Making, Ari Ezra Waldman

Articles & Chapters

Many decisions that used to be made by humans are now made by machines. And yet, automated decision-making systems based on “big data” – powered algorithms and machine learning are just as prone to mistakes, biases, and arbitrariness as their human counterparts. The result is a technologically driven decision-making process that seems to defy interrogation, analysis, and accountability and, therefore, undermines due process. This should make algorithmic decision-making an illegitimate source of authority in a liberal democracy. This Essay argues that algorithmic decision-making is a product of the neoliberal project to undermine social values like equality, nondiscrimination, and human flourishing …

Transparency And Algorithmic Governance, Cary Coglianese, David Lehr

All Faculty Scholarship

Machine-learning algorithms are improving and automating important functions in medicine, transportation, and business. Government officials have also started to take notice of the accuracy and speed that such algorithms provide, increasingly relying on them to aid with consequential public-sector functions, including tax administration, regulatory oversight, and benefits administration. Despite machine-learning algorithms’ superior predictive power over conventional analytic tools, algorithmic forecasts are difficult to understand and explain. Machine learning’s “black-box” nature has thus raised concern: Can algorithmic governance be squared with legal principles of governmental transparency? We analyze this question and conclude that machine-learning algorithms’ relative inscrutability does not pose a …

When Ais Outperform Doctors: Confronting The Challenges Of A Tort-Induced Over-Reliance On Machine Learning, A. Michael Froomkin, Ian Kerr, Joelle Pineau

Articles

Someday, perhaps soon, diagnostics generated by machine learning (ML) will have demonstrably better success rates than those generated by human doctors. What will the dominance of ML diagnostics mean for medical malpractice law, for the future of medical service provision, for the demand for certain kinds of doctors, and in the long run for the quality of medical diagnostics itself?

This Article argues that once ML diagnosticians, such as those based on neural networks, are shown to be superior, existing medical malpractice law will require superior ML-generated medical diagnostics as the standard of care in clinical settings. Further, unless implemented …

What Genetic Testing Teaches About Long-Term Predictive Health Analytics Regulation, Sharona Hoffman

Faculty Publications

The ever-growing phenomenon of predictive health analytics is generating significant excitement, hope for improved health outcomes, and potential for new revenues. Researchers are developing algorithms to predict suicide, heart disease, stroke, diabetes, cognitive decline, future opioid abuse, and other ailments. The researchers include not only medical experts, but also commercial enterprises such as Facebook and LexisNexis, who may profit from the work considerably. This Article focuses on long-term disease predictions (predictions regarding future illnesses), which have received surprisingly little attention in the legal and ethical literature. It compares the robust academic and policy debates and legal interventions that followed the …

Regulation Of Artificial Intelligence In Selected Jurisdictions, Jenny Gesley, Tariq Ahmad, Edouardo Soares, Ruth Levush, Gustavo Guerra, James Martin, Kelly Buchanan, Laney Zhang, Sayuri Umeda, Astghik Grigoryan, Nicolas Boring, Elin Hofverberg, Clare Feikhert-Ahalt, Graciela Rodriguez-Ferrand, George Sadek, Hanibal Goitom

Copyright, Fair Use, Scholarly Communication, etc.

Comparative Summary

This report examines the emerging regulatory and policy landscape surrounding artificial intelligence (AI) in jurisdictions around the world and in the European Union (EU). In addition, a survey of international organizations describes the approach that United Nations (UN) agencies and regional organizations have taken towards AI. As the regulation of AI is still in its infancy, guidelines, ethics codes, and actions by and statements from governments and their agencies on AI are also addressed. While the country surveys look at various legal issues, including data protection and privacy, transparency, human oversight, surveillance, public administration and services, autonomous vehicles, …

Expanding Access To Remedies Through E-Court Initiatives, Amy J. Schmitz

Faculty Publications

Virtual courthouses, artificial intelligence (AI) for determining cases, and algorithmic analysis for all types of legal issues have captured the interest of judges, lawyers, educators, commentators, business leaders, and policymakers. Technology has become the “fourth party” in dispute resolution through the growing field of online dispute resolution (ODR), which includes the use of a broad spectrum of technologies in negotiation, mediation, arbitration, and other dispute resolution processes. Indeed, ODR shows great promise for expanding access to remedies, or justice. In the United States and abroad, however, ODR has mainly thrived within e-commerce companies like eBay and Alibaba, while most public …

A Note On Science, Legal Research And Artificial Intelligence, Sean Goltz, Giulia Dondoli

Research outputs 2014 to 2021

This paper discusses the principles of scientific research and in turn review legal research that was done using Artificial Intelligence arguing that it is the tools (Artificial Intelligence) that take center stage while the meaning (legal research) is left back stage. In turn, this kind of research does not adhere to the fundamentals of scientific research nor comply with scientific and industry ethical codes.

Data-Centric Technologies: Patent And Copyright Doctrinal Disruptions, Tabrez Y. Ebrahim

Faculty Scholarship

Data-centric technologies create information content that directly controls, modifies, or responds to the physical world. This information content resides in the digital world yet has profound economic and societal impact in the physical world. 3D printing and artificial intelligence are examples of data-centric technologies. 3D printing utilizes digital data for eventual printing of physical goods. Artificial intelligence learns from data sets to make predictions or automated decisions for use in physical applications and systems. 3D printing and artificial intelligence technologies are based on digital foundations, blur the digital and physical divide, and dramatically improve physical goods, objects, products, or systems. …

Automation And Predictive Analytics In Patent Prosecution: Uspto Implications And Policy, Tabrez Y. Ebrahim

Faculty Scholarship

Artificial-intelligence technological advancements bring automation and predictive analytics into patent prosecution. The information asymmetry between inventors and patent examiners is expanded by artificial intelligence, which transforms the inventor-examiner interaction to machine-human interactions. In response to automated patent drafting, automated office-action responses, "cloems" (computer-generated word permutations) for defensive patenting, and machine-learning guidance (based on constantly updated patent-prosecution big data), the United States Patent and Trademark Office (USPTO) should reevaluate patent-examination policy from economic, fairness, time, and transparency perspectives. By conceptualizing the inventor-examiner relationship as a "patenting market," economic principles suggest stronger efficiencies if both inventors and the USPTO have better information …

Automatically Extracting Meaning From Legal Texts: Opportunities And Challenges, Kevin D. Ashley

Articles

This paper examines impressive new applications of legal text analytics in automated contract review, litigation support, conceptual legal information retrieval, and legal question answering against the backdrop of some pressing technological constraints. First, artificial intelligence (Al) programs cannot read legal texts like lawyers can. Using statistical methods, Al can only extract some semantic information from legal texts. For example, it can use the extracted meanings to improve retrieval and ranking, but it cannot yet extract legal rules in logical form from statutory texts. Second, machine learning (ML) may yield answers, but it cannot explain its answers to legal questions or …

Using Ai To Analyze Patent Claim Indefiniteness, Dean Alderucci, Kevin D. Ashley

Articles

In this Article, we describe how to use artificial intelligence (AI) techniques to partially automate a type of legal analysis, determining whether a patent claim satisfies the definiteness requirement. Although fully automating such a high-level cognitive task is well beyond state-of-the-art AI, we show that AI can nevertheless assist the decision maker in making this determination. Specifically, the use of custom AI technology can aid the decision maker by (1) mining patent text to rapidly bring relevant information to the decision maker attention, and (2) suggesting simple inferences that can be drawn from that information.

We begin by summarizing the …