Computer Law Commons^™

Cybersecurity Risk Shifting, Deborah R. Farringer

Vanderbilt Journal of Entertainment & Technology Law

The Change Healthcare cyberattack of 2024 paralyzed the health care system for months, creating an exceedingly far reaching and devastating impact on providers, suppliers, and patients across the country. While the scope of the attack was unprecedented, the cyberattack itself was not new, unique, or isolated. Indeed, this attack came just months after the close of a year in which the United States’ Department of Health and Human Services’ Office for Civil Rights (OCR) recorded the highest number of reported breaches of protected health information and the highest number of breached records. With a medical record fetching nearly four times …

The Privacy Law Jigsaw: Piecing Together Legal Compliance When Pieces Don’T Fit, Roy Wyman, Wesley Mcculloch

Vanderbilt Journal of Entertainment & Technology Law

Over the past six years the United States has shifted from a relatively stable and laissez-faire privacy regime, anchored by a few, sector-specific federal statutes such as the Health Insurance Portability and Accountability Act, to an increasingly fragmented landscape dominated by numerous state-level consumer privacy laws. While these laws share commonalities, they also vary in important ways. This Article analyzes that patchwork legal regime and its impact on businesses through four points of friction: (i) statutory applicability and thresholds; (ii) notice-and-choice requirements; (iii) individual data-management rights; and (iv) controller–processor contracting obligations. This Article further explores how modern service-delivery models, especially …

Reconceiving Safety Regulation For Ai And Ml Medical Software, Barbara J. Evans, Eric S. Rosenthal, Azra Bihorac

Vanderbilt Journal of Entertainment & Technology Law

This article explores the challenges of regulating AI and ML clinical decision support tools intended to assist trained health care professionals in delivering clinical care. Two old, twentieth-century regulatory models have dominated discussions of medical AI policy since 2013. Thinking inside these old regulatory boxes has not produced effective regulatory solutions to address the novel risks AI poses in clinical care. The first regulatory box treats software as a medical device, which tasks medical device regulators with making software safe but neglects the crucial roles physicians, nurses, administrators, medical practice regulators, and other health oversight bodies must also play to …

Editorial

Indian Journal of Law and Technology

No abstract provided.

Fiscal Sponsorship In Truly Independent Film: Entity And Model Choice And Legal Risks, Samuel Johnson

Washington Journal of Law, Technology & Arts

This article examines fiscal sponsorship as a legal and financing structure for “truly independent” films—low-budget, non-commercial projects created by filmmakers without access to studio financing, tax incentives, or traditional investors. Neither standalone nonprofit incorporation nor purely for-profit entity structures adequately address the unique needs of such projects. After surveying the development of fiscal sponsorship as a means of funding projects that meet an exempt purpose, relevant IRS guidance, and current prevailing practices and organizational structures in independent film, the article contends that a Model C (“regranting”) fiscal sponsorship paired with a single-member limited liability company (SMLLC) offers the optimal balance …

Fluid Agency In Ai Systems: A Case For Functional Equivalence In Copyright, Patent, And Tort, Anirban Mukherjee, Hannah H. Chang

Washington Journal of Law, Technology & Arts

Modern artificial intelligence (AI) systems lack human-like consciousness or culpability, yet they exhibit fluid agency: behavior that is (i) stochastic (probabilistic and path-dependent), (ii) dynamic (co-evolving with user interaction), and (iii) adaptive (able to reorient across contexts). Fluid agency generates valuable outputs but collapses attribution, irreducibly entangling human and machine inputs. This fundamental unmappability fractures doctrines that assume traceable provenance—authorship, inventorship, and liability—yielding ownership gaps and moral “crumple zones.”

This Article argues that only functional equivalence stabilizes doctrine. Where provenance is indeterminate, legal frameworks must treat human and AI contributions as equivalent for allocating rights and responsibility—not as a claim …

Death Of Substantiality: Why The Legal System Should Rethink The Application And Weight Of This Fair-Use Factor In The Context Of Social Media, Lindsey Vickers

Washington Journal of Law, Technology & Arts

The fair use test for exemption for liability from copyright infringement was codified in the 1970s and has not been updated since—despite major technological changes in the interim. While three of the test’s four prongs are still useful when applied to short-form media that now dominates worldwide media consumption, the factor that considers the substantiality of the portion used relative to the total work is obsolete. The current dysfunctionality of this prong in social media settings is not the only reason it should be reassessed by courts and Congress. The prong and its analysis are a bit of a Frankenstein. …

Table Of Contents

Washington Journal of Law, Technology & Arts

No abstract provided.

Masthead

Washington Journal of Law, Technology & Arts

No abstract provided.

The Taiwanese Way To Ai Governance: Draft Basic Law On Artificial Intelligence And Future Regulatory Strategies

Washington International Law Journal

Abstract: Despite Taiwan’s significant contributions to the global artificial intelligence (AI) ecosystem, its role remains underexamined in international AI governance discourse. This Article addresses this gap by analyzing Taiwan’s emerging AI regulatory framework, with particular emphasis on the Draft Basic Law on Artificial Intelligence (the “Draft AI Law”). Situating Taiwan’s approach within the broader global regulatory landscape, the Article compares the Draft AI Law with key international models, including the European Union’s AI Act and the United States’ NIST AI Risk Management Framework, while also drawing on regulatory developments in Japan and South Korea. Rather than providing a clause-by-clause analysis, …

Mitigating Data Privacy Risks In Political Micro-Targeting Through Gdpr-Compliant Federated Learning: Lessons From The Cambridge Analytica Controversy, Jingfan (Serena) Xiao

Marquette Intellectual Property & Innovation Law Review

Political micro-targeting employs granular data analytics to deliver hyper- personalized political messaging, raising fundamental tensions between electoral strategy, data privacy, and democratic accountability. The Facebook- Cambridge Analytica scandal exposed significant gaps in pre-GDPR data protection laws, highlighting the risks of unchecked algorithmic profiling in shaping voter behavior. However, as micro-targeting evolves under more sophisticated AI-driven systems, a pressing question emerges: should AI- generated political messaging qualify for First Amendment protection? This Article introduces the concept of speech certainty, arguing that speech must be intentional and cognitively understood by the speaker at the moment of articulation to warrant constitutional protection. Under …

Big Tech As Transnational Spyware Regulator, Natalie R. Davidson

Fordham Intellectual Property, Media and Entertainment Law Journal

Spyware has emerged as a potent tool for leaders to shrink dem- ocratic contestation. In response to calls for constraints on the trade in spyware, states have updated the principal multilateral agree- ment on export controls, civil society groups have employed strate- gic litigation, and the European Union has altered its regulation, in each case with the aim of limiting exports where there is a risk of human rights violations. Yet, scandals involving the Israeli company NSO, among others, have made clear that even the updated regula- tory landscape is inadequate. Many actors are currently debating the reasons for existing …

The Last Human Question: Generative Ai's Existential Threat To Consensus And Law, Joshua Fairfield

Scholarly Articles

The true risk of artificial intelligence (“AI”) is not that the toasters will rise up. It is that AI will be competent to perform human tasks and indifferent to human welfare. The risk is that we will be outcompeted by generative automated processes that create output similar to ours (although never the same, as this Article explains), but which need none of the outputs of the economy for food, shelter, or human flourishing. Further, a more precise and existential description of the threat is that generative AI will disrupt and crowd out humanity’s evolutionary superpower, our ability to generate agreement …

Operational Agency: A Permeable Legal Fiction For Tracing Culpability In Ai Systems, Anirban Mukherjee, Hannah H. Chang

SMU Science and Technology Law Review

Modern artificial intelligence (AI) systems act with a high degree of independence yet lack legal personhood—a paradox that fractures doctrines grounded in human-centric notions of mens rea and actus reus. This Article introduces Operational Agency (OA)—a permeable legal fiction structured as an ex post evidentiary framework—and Operational Agency Graph (OAG)—a tool for mapping causal interactions among human actors, organizations, and AI systems. OA evaluates an AI’s observable operational characteristics: its goal-directedness (as a proxy for intent), predictive processing (as a proxy for foresight), and safety architecture (as a proxy for standard of care). OAG operationalizes that analysis by embedding these …

Front Matter

SMU Science and Technology Law Review

No abstract provided.

Suing The Ghost In The Medical Machine, Jason R. Cheek

SMU Science and Technology Law Review

Devices that autonomously diagnose medical conditions, with no human interaction, have arrived. These self-operating systems incorporate artificial intelligence (AI), and include machines that diagnose preventable blindness, as well as some that write radiology reports. These devices feature AI-integrated software to make diagnosis decisions traditionally made by humans who have received extensive medical training. Soon, AI-driven devices will autonomously make treatment decisions.

What happens when these autonomous medical systems harm a patient? At the moment, most would expect product liability law to provide a path to recovery. But AI oftentimes uses multiple complex inputs and approaches, including statistical probabilities, to reach …

An Empirical Examination Of Law Student Attitudes Toward Legal Writing With Generative Ai, Abigail L. Perdue

SMU Science and Technology Law Review

Amid mounting predictions that generative artificial intelligence (AI) will substantially disrupt legal education, legal writing professors grapple with how and when to integrate generative AI into the classroom. While some believe that it should be woven into existing courses and integrated across the curriculum, even in the first year, others contend that it is better reserved for discussion in upper-level courses dedicated to AI-assistance. Yet it remains unclear which approach will best prepare graduates for the modern practice of law. Indeed, some scholars caution that permitting law students to use generative AI to complete their legal writing coursework, particularly in …

Dignity By Design: A Human-Centered Framework For Ethical Ai, Armin Tadayon

Washington and Lee Journal of Civil Rights and Social Justice

The launch of ChatGPT in November 2022 has triggered a global arms race–both among private technology companies and between nation states–for dominance in the field of Artificial Intelligence (AI). If this nascent technology, which is permeating every aspect of our lives as more companies across multiple sectors deploy it for a variety of functions, malfunctions or behaves in unanticipated ways, it can severely affect individuals in their day-to-day lives with broader consequences for society at large. As such, as AI permeates every aspect of our lives, and in some instances, begins to replace humans and human decision-making, it is imperative …

Reconceiving Safety Regulation For Ai And Ml Medical Software, Barbara J. Evans, Eric S. Rosenthal, Azra Bihorac

UF Law Faculty Publications

This article explores the challenges of regulating AI and ML clinical decision support tools intended to assist trained health care professionals in delivering clinical care. Two old, twentieth-century regulatory models have dominated discussions of medical AI policy since 2013. Thinking inside these old regulatory boxes has not produced effective regulatory solutions to address the novel risks AI poses in clinical care. The first regulatory box treats software as a medical device, which tasks medical device regulators with making software safe but neglects the crucial roles physicians, nurses, administrators, medical practice regulators, and other health oversight bodies must also play to …

Beyond Sharenting, Stacey B. Steinberg

UF Law Faculty Publications

Sharenting—the practice of parents sharing information about their children online—has become mainstream in American society. While most forms of sharenting may be considered benign or even beneficial, some parents harm or exploit their children when sharing online. For example, “mom-influencers” often violate their children’s privacy in their attempts to attract followers to their social media accounts. While traditional forms of parental sharing raise privacy concerns, we are only beginning to understand the dangers and impacts of widespread exposure of children on social media.

This Article is the first to propose a welfare model of child protection to address exploitative and …