Law Commons^™

Legal Dispositionism And Artificially-Intelligent Attributions, Jerrold Soh

Research Collection Yong Pung How School Of Law

It is conventionally argued that because an artificially-intelligent (AI) system acts autonomously, its makers cannot easily be held liable should the system's actions harm. Since the system cannot be liable on its own account either, existing laws expose victims to accountability gaps and need to be reformed. Recent legal instruments have nonetheless established obligations against AI developers and providers. Drawing on attribution theory, this paper examines how these seemingly opposing positions are shaped by the ways in which AI systems are conceptualised. Specifically, folk dispositionism underpins conventional legal discourse on AI liability, personality, publications, and inventions and leads us towards …

Regulating Machine Learning: The Challenge Of Heterogeneity, Cary Coglianese

Faculty Scholarship at Penn Carey Law

Machine learning, or artificial intelligence, refers to a vast array of different algorithms that are being put to highly varied uses, including in transportation, medicine, social media, marketing, and many other settings. Not only do machine-learning algorithms vary widely across their types and uses, but they are evolving constantly. Even the same algorithm can perform quite differently over time as it is fed new data. Due to the staggering heterogeneity of these algorithms, multiple regulatory agencies will be needed to regulate the use of machine learning, each within their own discrete area of specialization. Even these specialized expert agencies, though, …

Layered Fiduciaries In The Information Age, Zhaoyi Li

Articles

Technology companies such as Facebook have long been criticized for abusing customers’ personal information and monetizing user data in a manner contrary to customer expectations. Some commentators suggest fiduciary law could be used to restrict how these companies use their customers’ data. Under this framework, a new member of the fiduciary family called the “information fiduciary” was born. The concept of an information fiduciary is that a company providing network services to “collect, analyze, use, sell, and distribute personal information” owes customers and end-users a fiduciary duty to use the collected data to promote their interests, thereby assuming fiduciary liability …

Layered Fiduciaries In The Information Age, Zhaoyi Li

Articles

Technology companies such as Facebook have long been criticized for abusing customers’ personal information and monetizing user data in a manner contrary to customer expectations. Some commentators suggest fiduciary law could be used to restrict how these companies use their customers’ data. Under this framework, a new member of the fiduciary family called the “information fiduciary” was born. The concept of an information fiduciary is that a company providing network services to “collect, analyze, use, sell, and distribute personal information” owes customers and end-users a fiduciary duty to use the collected data to promote their interests, thereby assuming fiduciary liability …

Governing Smart Cities As Knowledge Commons - Introduction, Chapter 1 & Conclusion, Brett M. Frischmann, Michael J. Madison, Madelyn Sanfilippo

Book Chapters

Smart city technology has its value and its place; it isn’t automatically or universally harmful. Urban challenges and opportunities addressed via smart technology demand systematic study, examining general patterns and local variations as smart city practices unfold around the world. Smart cities are complex blends of community governance institutions, social dilemmas that cities face, and dynamic relationships among information and data, technology, and human lives. Some of those blends are more typical and common. Some are more nuanced in specific contexts. This volume uses the Governing Knowledge Commons (GKC) framework to sort out relevant and important distinctions. The framework grounds …

Open-Source Clinical Machine Learning Models: Critical Appraisal Of Feasibility, Advantages, And Challenges, Keerthi B. Harish, W. Nicholson Price Ii, Yindalon Aphinyanaphongs

Articles

Machine learning applications promise to augment clinical capabilities and at least 64 models have already been approved by the US Food and Drug Administration. These tools are developed, shared, and used in an environment in which regulations and market forces remain immature. An important consideration when evaluating this environment is the introduction of open-source solutions in which innovations are freely shared; such solutions have long been a facet of digital culture. We discuss the feasibility and implications of open-source machine learning in a health care infrastructure built upon proprietary information. The decreased cost of development as compared to drugs and …

User Guided Abductive Proof Generation For Answer Set Programming Queries, Avishkar Mahajan, Martin Strecker, Meng Weng (Huang Mingrong) Wong

Research Collection Yong Pung How School Of Law

We present a method for generating possible proofs of a query with respect to a given Answer Set Programming (ASP) rule set using an abductive process where the space of abducibles is automatically constructed just from the input rules alone. Given a (possibly empty) set of user provided facts, our method infers any additional facts that may be needed for the entailment of a query and then outputs these extra facts, without the user needing to explicitly specify the space of all abducibles. We also present a method to generate a set of directed edges corresponding to the justification graph …

Biometrics And An Ai Bill Of Rights, Margaret Hu

Faculty Publications

This Article contends that an informed discussion on an AI Bill of Rights requires grappling with biometric data collection and its integration into emerging AI systems. Biometric AI systems serve a wide range of governmental purposes, including policing, border security and immigration enforcement, and biometric cyberintelligence and biometric-enabled warfare. These systems are increasingly categorized as "high-risk" when deployed in ways that may impact fundamental constitutional rights and human rights. There is growing recognition that high-risk biometric AI systems, such as facial recognition identification, can pose unprecedented challenges to criminal procedure rights. This Article concludes that a failure to recognize these …

Spotlight Report #6: Proffering Machine-Readable Personal Privacy Research Agreements: Pilot Project Findings For Ieee P7012 Wg, Noreen Y. Whysel, Lisa Levasseur

Publications and Research

What if people had the ability to assert their own legally binding permissions for data collection, use, sharing, and retention by the technologies they use? The IEEE P7012 has been working on an interoperability specification for machine-readable personal privacy terms to support this ability since 2018. The premise behind the work of IEEE P7012 is that people need technology that works on their behalf—i.e. software agents that assert the individual’s permissions and preferences in a machine-readable format.

Thanks to a grant from the IEEE Technical Activities Board Committee on Standards (TAB CoS), we were able to explore the attitudes of …

Gauging The Acceptance Of Contact Tracing Technology: An Empirical Study Of Singapore Residents’ Concerns With Sharing Their Information And Willingness To Trust, Ee-Ing Ong, Wee Ling Loo

Research Collection Yong Pung How School Of Law

In response to the COVID-19 pandemic, governments began implementing various forms of contact tracing technology. Singapore’s implementation of its contact tracing technology, TraceTogether, however, was met with significant concern by its population, with regard to privacy and data security. This concern did not fit with the general perception that Singaporeans have a high level of trust in its government. We explore this disconnect, using responses to our survey (conducted pre-COVID-19) in which we asked participants about their level of concern with the government and business collecting certain categories of personal data. The results show that respondents had less concern with …

Problematic Ai — When Should We Use It?, Fredric Lederer

Popular Media

No abstract provided.

The Executive’S Guide To Getting Ai Wrong, Jerrold Soh

Asian Management Insights

It’s all math. Really.

Assessing Automated Administration, Cary Coglianese, Alicia Lai

Faculty Scholarship at Penn Carey Law

To fulfill their responsibilities, governments rely on administrators and employees who, simply because they are human, are prone to individual and group decision-making errors. These errors have at times produced both major tragedies and minor inefficiencies. One potential strategy for overcoming cognitive limitations and group fallibilities is to invest in artificial intelligence (AI) tools that allow for the automation of governmental tasks, thereby reducing reliance on human decision-making. Yet as much as AI tools show promise for improving public administration, automation itself can fail or can generate controversy. Public administrators face the question of when exactly they should use automation. …

Ai Insurance: How Liability Insurance Can Drive The Responsible Adoption Of Artificial Intelligence In Health Care, Ariel Dora Stern, Avi Goldfarb, Timo Minssen, W. Nicholson Price Ii

Articles

Despite enthusiasm about the potential to apply artificial intelligence (AI) to medicine and health care delivery, adoption remains tepid, even for the most compelling technologies. In this article, the authors focus on one set of challenges to AI adoption: those related to liability. Well-designed AI liability insurance can mitigate predictable liability risks and uncertainties in a way that is aligned with the interests of health care’s main stakeholders, including patients, physicians, and health care organization leadership. A market for AI insurance will encourage the use of high-quality AI, because insurers will be most keen to underwrite those products that are …

Volume Introduction, I. Glenn Cohen, Timo Minssen, W. Nicholson Price Ii, Christopher Robertson, Carmel Shachar

Other Publications

Medical devices have historically been less regulated than their drug and biologic counterparts. A benefit of this less demanding regulatory regime is facilitating innovation by making new devices available to consumers in a timely fashion. Nevertheless, there is increasing concern that this approach raises serious public health and safety concerns. The Institute of Medicine in 2011 published a critique of the American pathway allowing moderate-risk devices to be brought to the market through the less-rigorous 501(k) pathway,1 flagging a need for increased postmarket review and surveillance. High-profile recalls of medical devices, such as vaginal mesh products, along with reports globally …

Moving Toward Personalized Law, Cary Coglianese

Faculty Scholarship at Penn Carey Law

Rules operate as a tool of governance by making generalizations, thereby cutting down on government officials’ need to make individual determinations. But because they are generalizations, rules can result in inefficient or perverse outcomes due to their over- and under-inclusiveness. With the aid of advances in machine-learning algorithms, however, it is becoming increasingly possible to imagine governments shifting away from a predominant reliance on general rules and instead moving toward increased reliance on precise individual determinations—or on “personalized law,” to use the term Omri Ben-Shahar and Ariel Porat use in the title of their 2021 book. Among the various technological, …

Trust In Robotics: A Multi-Staged Decision-Making Approach To Robots In Community, Wenxi Zhang, Willow Wong, Mark Findlay

Centre for AI & Data Governance

Pivoting on the desired outcome of social good within the wider robotics ecosystem, trust is identified as the central adhesive of the HRI interface. However, building trust between humans and robots involves more than improving the machine’s technical reliability or trustworthiness in function. This paper presents a holistic, community-based approach to trust-building, where trust is understood as a multifaceted and multi-staged looped relation that depends heavily on context and human perceptions. Building on past literature that identifies dispositional and learned stages of trust, our proposed Decision to Trust model considers more extensively the human and situational factors influencing how trust …

Designing Respectful Tech: What Is Your Relationship With Technology?, Noreen Y. Whysel

Publications and Research

According to research at the Me2B Alliance, people feel they have a relationship with technology. It’s emotional. It’s embodied. And it’s very personal. We are studying digital relationships to answer questions like “Do people have a relationship with technology?” “What does that relationship feel like?” And “Do people understand the commitments that they are making when they explore, enter into and dissolve these relationships?” There are parallels between messy human relationships and the kinds of relationships that people develop with technology. As with human relationships, we move through states of discovery, commitment and breakup with digital applications as well. Technology …

Me2b Alliance Validation Testing Report: Consumer Perception Of Legal Policies In Digital Technology, Noreen Y. Whysel, Karina Alexanyan, Shaun Spaulting, Julia Little

Publications and Research

Our relationship with technology involves legal agreements that we either review or enter into when using a technology, namely privacy policies and terms of service or terms of use (“TOS/TOU”). We initiated this research to understand if providing a formal rating of the legal policies (privacy policies and TOS/TOUs) would be valuable to consumers (or Me-s). From our early qualitative discussions, we noticed that people were unclear on whether these policies were legally binding contracts or not. Thus, a secondary objective emerged to quantitatively explore whether people knew who these policies protected (if anyone), and if the policies were perceived …

Clinical Interactions In Electronic Medical Records Towards The Development Of A Token-Economy Model, Nicole Allison S. Co, Jason Limcaco, Hans Calvin L. Tan, Ma. Regina Justina E. Estuar, Christian E. Pulmano, Dennis Andrew Villamor, Quirino Sugon Jr, Maria Cristina G. Bautista, Paulyn Jean Acacio-Claro

Graduate School of Business Publications

The use of electronic medical records (EMRs) plays a crucial role in the successful implementation of the Universal Healthcare Law which promises quality and affordable healthcare to all Filipinos. Consequently, the current adoption of EMRs should be studied from the perspective of the healthcare provider. As most studies look into use of EMRs by doctors or patients, there are very few that extend studies to look at possible interaction of doctor and patient in the same EMR environment. Understanding this interaction paves the way for possible incentives that will increase the use and adoption of the EMR. This study uses …

Liability For Use Of Artificial Intelligence In Medicine, W. Nicholson Price, Sara Gerke, I. Glenn Cohen

Law & Economics Working Papers

While artificial intelligence has substantial potential to improve medical practice, errors will certainly occur, sometimes resulting in injury. Who will be liable? Questions of liability for AI-related injury raise not only immediate concerns for potentially liable parties, but also broader systemic questions about how AI will be developed and adopted. The landscape of liability is complex, involving health-care providers and institutions and the developers of AI systems. In this chapter, we consider these three principal loci of liability: individual health-care providers, focused on physicians; institutions, focused on hospitals; and developers.

Defining Smart Contract Defects On Ethereum, Jiachi Chen, Xin Xia, David Lo, John Grundy, Xiapu Luo, Ting Chen

Research Collection School Of Computing and Information Systems

Smart contracts are programs running on a blockchain. They are immutable to change, and hence can not be patched for bugs once deployed. Thus it is critical to ensure they are bug-free and well-designed before deployment. A Contract defect is an error, flaw or fault in a smart contract that causes it to produce an incorrect or unexpected result, or to behave in unintended ways. The detection of contract defects is a method to avoid potential bugs and improve the design of existing code. Since smart contracts contain numerous distinctive features, such as the gas system. decentralized, it is important …

Law Library Blog (January 2022): Legal Beagle's Blog Archive, Roger Williams University School Of Law

Law Library Newsletters/Blog

No abstract provided.

Part I - Ai And Data As Medical Devices, W. Nicholson Price Ii

Other Publications

It may seem counterintuitive to open a book on medical devices with chapters on software and data, but these are the frontiers of new medical device regulation and law. Physical devices are still crucial to medicine, but they – and medical practice as a whole – are embedded in and permeated by networks of software and caches of data. Those software systems are often mindbogglingly complex and largely inscrutable, involving artificial intelligence and machine learning. Ensuring that such software works effectively and safely remains a substantial challenge for regulators and policymakers. Each of the three chapters in this part examines …

From Negative To Positive Algorithm Rights, Cary Coglianese, Kat Hefter

Faculty Scholarship at Penn Carey Law

Artificial intelligence, or “AI,” is raising alarm bells. Advocates and scholars propose policies to constrain or even prohibit certain AI uses by governmental entities. These efforts to establish a negative right to be free from AI stem from an understandable motivation to protect the public from arbitrary, biased, or unjust applications of algorithms. This movement to enshrine protective rights follows a familiar pattern of suspicion that has accompanied the introduction of other technologies into governmental processes. Sometimes this initial suspicion of a new technology later transforms into widespread acceptance and even a demand for its use. In this paper, we …

Antitrust By Algorithm, Cary Coglianese, Alicia Lai

Faculty Scholarship at Penn Carey Law

Technological innovation is changing private markets around the world. New advances in digital technology have created new opportunities for subtle and evasive forms of anticompetitive behavior by private firms. But some of these same technological advances could also help antitrust regulators improve their performance in detecting and responding to unlawful private conduct. We foresee that the growing digital complexity of the marketplace will necessitate that antitrust authorities increasingly rely on machine-learning algorithms to oversee market behavior. In making this transition, authorities will need to meet several key institutional challenges—building organizational capacity, avoiding legal pitfalls, and establishing public trust—to ensure successful …

Algorithm Vs. Algorithm, Cary Coglianese, Alicia Lai

Faculty Scholarship at Penn Carey Law

Critics raise alarm bells about governmental use of digital algorithms, charging that they are too complex, inscrutable, and prone to bias. A realistic assessment of digital algorithms, though, must acknowledge that government is already driven by algorithms of arguably greater complexity and potential for abuse: the algorithms implicit in human decision-making. The human brain operates algorithmically through complex neural networks. And when humans make collective decisions, they operate via algorithms too—those reflected in legislative, judicial, and administrative processes. Yet these human algorithms undeniably fail and are far from transparent. On an individual level, human decision-making suffers from memory limitations, fatigue, …

Exclusion Cycles: Reinforcing Disparities In Medicine, Ana Bracic, Shawneequa L. Callier, Nicholson Price

Articles

Minoritized populations face exclusion across contexts from politics to welfare to medicine. In medicine, exclusion manifests in substantial disparities in practice and in outcome. While these disparities arise from many sources, the interaction between institutions, dominant-group behaviors, and minoritized responses shape the overall pattern and are key to improving it. We apply the theory of exclusion cycles to medical practice, the collection of medical big data, and the development of artificial intelligence in medicine. These cycles are both self-reinforcing and other-reinforcing, leading to dismayingly persistent exclusion. The interactions between such cycles offer lessons and prescriptions for effective policy.

Book Review: Is Law Computable?: Critical Perspectives On Law And Artificial Intelligence, F. Tim Knight

Librarian Publications & Presentations

No abstract provided.

Regulating New Tech: Problems, Pathways, And People, Cary Coglianese

Faculty Scholarship at Penn Carey Law

New technologies bring with them many promises, but also a series of new problems. Even though these problems are new, they are not unlike the types of problems that regulators have long addressed in other contexts. The lessons from regulation in the past can thus guide regulatory efforts today. Regulators must focus on understanding the problems they seek to address and the causal pathways that lead to these problems. Then they must undertake efforts to shape the behavior of those in industry so that private sector managers focus on their technologies’ problems and take actions to interrupt the causal pathways. …