Law Commons^™

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

All Faculty Scholarship

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. …

Building Legal Datasets, Jerrold Soh

Research Collection Yong Pung How School Of Law

Data-centric AI calls for better, not just bigger, datasets. As data protection laws with extra-territorial reach proliferate worldwide, ensuring datasets are legal is an increasingly crucial yet overlooked component of “better”. To help dataset builders become more willing and able to navigate this complex legal space, this paper reviews key legal obligations surrounding ML datasets, examines the practical impact of data laws on ML pipelines, and offers a framework for building legal datasets.

Biographical Data And Black Box Empiricism: Lessons Learned For Algorithmic Assessments In Personnel Selection, Ketaki Sodhi, Marc Cubrich

Psychology from the Margins

As the popularity of biodata in selection assessments grew in the 1980s and into the 1990s, the field of industrial and organizational psychology witnessed many attempts to develop biodata theories and guide the development of biodata items. The insights that emerged from this body of research are increasingly relevant in the current era of big data, artificial intelligence (AI), and machine learning. More than ever, AI and machine learning are being used to score candidates and make hiring recommendations. Many organizations are using data-driven approaches to develop machine learning and AI algorithms, which are frequently atheoretical, based on correlations or …

Deep Fakes: The Algorithms That Create And Detect Them And The National Security Risks They Pose, Nick Dunard

James Madison Undergraduate Research Journal (JMURJ)

The dissemination of deep fakes for nefarious purposes poses significant national security risks to the United States, requiring an urgent development of technologies to detect their use and strategies to mitigate their effects. Deep fakes are images and videos created by or with the assistance of AI algorithms in which a person’s likeness, actions, or words have been replaced by someone else’s to deceive an audience. Often created with the help of generative adversarial networks, deep fakes can be used to blackmail, harass, exploit, and intimidate individuals and businesses; in large-scale disinformation campaigns, they can incite political tensions around the …

Judging By The Numbers: Judicial Analytics, The Justice System And Its Stakeholders, Jena Mcgill, Amy Salyzyn

Dalhousie Law Journal

This article considers the future of judicial analytics, its possible effects for the public, the judiciary and the legal profession, and potential responses to the rise of judicial analytics in Canada. Judicial analytics involves the use of advanced technologies, like machine learning and natural language processing, to quickly analyze publicly-available data about judges and judicial decision-making. While, in Canada, judicial analytics tools are as yet at the early stages of development and use, such tools are likely to become more powerful, more accurate and more accessible in the near-to-medium future, resulting in unprecedented public insight into judges and the work …

Legal Reviews Of War Algorithms, Tobias Vestner, Altea Rossi

International Law Studies

States and scholars recognize legal reviews of weapons, means or methods of warfare as an essential tool to ensure the legality of military applications of artificial intelligence (AI). Yet, are existing practices fit for this task? This article identifies necessary adaptations to current practices. For AI-enabled systems that are used in relation to targeting, legal reviews need to assess the systems’ compliance with additional rules of international law, in particular targeting law under international humanitarian law (IHL). This article discusses the procedural ramifications thereof. The article further finds that AI systems’ predictability problem needs to be addressed by the technical …

Brain-Computer-Interfacing & Respondeat Superior: Algorithmic Decisions, Manipulation, And Accountability In Armed Conflict, Salahudin Ali

Catholic University Journal of Law and Technology

This article examines the impact that brain-computer-interfacing platforms will have on the international law of armed conflict’s respondeat superior legal regime. Major Ali argues that the connection between the human brain and this nascent technology’s underlying technology of artificial intelligence and machine learning will serve as a disruptor to the traditional mental prerequisites required to impart culpability and liability on commanders for actions of their troops. Anticipating that BCI will become increasingly ubiquitous, Major Ali’s article offers frameworks for solution to BCI’s disruptive potential to the internal law of armed conflict.

Sounds Of Science: Copyright Infringement In Ai Music Generator Outputs, Eric Sunray

Catholic University Journal of Law and Technology

The music business is no stranger to disruptive technology. The industry’s apparent comeback from the devastating downturn caused by illegal file sharing seems to have arrived just in time for what may be an even more disruptive technological phenomenon: artificial intelligence (“AI”). Much has been said about the implications of AI-generated music, ranging from issues of ownership, to rights of publicity. However, there has been surprisingly little discussion of infringement in the AI systems’ outputs. By examining the functionality of AI music generators through the lens of de minimis use case law, this paper will explain how the outputs of …

Clearing Opacity Through Machine Learning, W. Nicholson Price Ii, Arti K. Rai

Articles

Artificial intelligence and machine learning represent powerful tools in many fields, ranging from criminal justice to human biology to climate change. Part of the power of these tools arises from their ability to make predictions and glean useful information about complex real-world systems without the need to understand the workings of those systems.

Health Ai For Good Rather Than Evil? The Need For A New Regulatory Framework For Ai-Based Medical Devices, Sara Gerke

Faculty Scholarly Works

Artificial intelligence (AI), especially its subset machine learning, has tremendous potential to improve health care. However, health AI also raises new regulatory challenges. In this Article, I argue that there is a need for a new regulatory framework for AI-based medical devices in the U.S. that ensures that such devices are reasonably safe and effective when placed on the market and will remain so throughout their life cycle. I advocate for U.S. Food and Drug Administration (FDA) and congressional actions. I focus on how the FDA could - with additional statutory authority - regulate AI-based medical devices. I show that …

Book Review, Aamir S. Abdullah

Publications

No abstract provided.

Ai In Adjudication And Administration, Cary Coglianese, Lavi M. Ben Dor

All Faculty Scholarship

The use of artificial intelligence has expanded rapidly in recent years across many aspects of the economy. For federal, state, and local governments in the United States, interest in artificial intelligence has manifested in the use of a series of digital tools, including the occasional deployment of machine learning, to aid in the performance of a variety of governmental functions. In this paper, we canvas the current uses of such digital tools and machine-learning technologies by the judiciary and administrative agencies in the United States. Although we have yet to see fully automated decision-making find its way into either adjudication …

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 …

Facial Recognition And The Fourth Amendment, Andrew Ferguson

Articles in Law Reviews & Other Academic Journals

Facial recognition offers a totalizing new surveillance power. Police now have the capability to monitor, track, and identify faces through networked surveillance cameras and datasets of billions of images. Whether identifying a particular suspect from a still photo, or identifying every person who walks past a digital camera, the privacy and security impacts of facial recognition are profound and troubling.

This Article explores the constitutional design problem at the heart of facial recognition surveillance systems. One might hope that the Fourth Amendment – designed to restrain police power and enacted to limit governmental overreach – would have something to say …

Beyond Algorithms: Toward A Normative Theory Of Automated Regulation, Felix Mormann

Faculty Scholarship

The proliferation of artificial intelligence in our daily lives has spawned a burgeoning literature on the dawn of dehumanized, algorithmic governance. Remarkably, the scholarly discourse overwhelmingly fails to acknowledge that automated, non-human governance has long been a reality. For more than a century, policymakers have relied on regulations that automatically adjust to changing circumstances, without the need for human intervention. This article surveys the track record of self-adjusting governance mechanisms to propose a normative theory of automated regulation.

Effective policymaking frequently requires anticipation of future developments, from technology innovation to geopolitical change. Self-adjusting regulation offers an insurance policy against the …