Science and Technology Law Commons^™

Hacking Copyright: Holding Cops Accountable For Abusing Youtube’S Copyright Filter System, Tyler Bloom

Journal of Law and Policy

This Note both explores the mechanisms and incentive structures that make “copyright hacking” possible and explains the legal system’s failure to provide recourse for victims of successful “copyright hacks” by police officers. Because the DMCA has failed to keep pace with the internet’s exponential growth, OSPs, such as YouTube, have developed filtering systems that can be exploited to “copyright hack” users and ultimately suppress their speech. A victim of “copyright hacking” by a police officer currently has no recourse; the doctrine of qualified immunity functionally precludes them from suing for violating their First Amendment rights. This Note proposes two possible …

An End-To-End Pipeline From Law Text To Logical Formulas, Aarne Ranta, Inari Listenmaa, Jerrold Soh, Meng Weng Wong

Research Collection Yong Pung How School Of Law

We propose a pipeline for converting natural English law texts into logical formulas via a series of structural representations. Text texts are first parsed using a formal grammar derived from light-weight annotations. An intermediate representation called assembly logic is then used for logical interpretation and supports translations to different back-end logics and visualisations. The approach, while rule-based and explainable, is also robust: it can deliver useful results from day one, but allows subsequent refinements and variations.

Algorithmic Elections, Sarah M.L. Bender

Michigan Law Review

Artificial intelligence (AI) has entered election administration. Across the country, election officials are beginning to use AI systems to purge voter records, verify mail-in ballots, and draw district lines. Already, these technologies are having a profound effect on voting rights and democratic processes. However, they have received relatively little attention from AI experts, advocates, and policymakers. Scholars have sounded the alarm on a variety of “algorithmic harms” resulting from AI’s use in the criminal justice system, employment, healthcare, and other civil rights domains. Many of these same algorithmic harms manifest in elections and voting but have been underexplored and remain …

A Tokenized Future: Regulatory Lessons From Crowdfunding And Standard Form Contracts, Darian M. Ibrahim

Faculty Publications

This Article examines the world of risk investing in the cryptoeconomy. The broader crypto market is booming despite the latest downturn. People and institutions are buying in. The question is now how to regulate it.

This Article first tackles the question of whether coins, tokens, and other investable cryptoassets are securities. Second, for those cryptoassets that are not securities, this Article seeks to find a regulatory solution that balances promoting innovation with investor protection, just as the Securities and Exchange Commission (SEC) would do. To strike the right balance, this Article adopts a proposal by Ian Ayres and Alan Schwartz …

Thaler V. Vidal: Artificial Intelligence—Can The Invented Become The Inventor?, Michelle Lavrichenko

Cardozo Law Review

No abstract provided.

Why A New Deal Must Address The Readability Of U.S. Consumer Contracts, Michael L. Rustad

Cardozo Law Review

United States companies are increasingly drafting consumer contracts that are complex and unreadable, thus making it difficult for many Americans to comprehend terms of use that apply to goods and services. Many U.S. companies are creating terms of use that are, in effect, rights-foreclosure schemes. Many consumer agreements cap damages at a nominal amount, disclaim all warranties, limit remedies, and impose mandatory arbitration clauses and class action waivers. U.S. courts enforce these unfair mass-market contracts with few exceptions. My proposal for a New Deal for Consumer Contracts, as described in this Article, would impose a more exacting readability standard, enforcing …

Algorithmic Governance From The Bottom Up, Hannah Bloch-Wehba

BYU Law Review

Artificial intelligence and machine learning are both a blessing and a curse for governance. In theory, algorithmic governance makes government more efficient, more accurate, and more fair. But the emergence of automation in governance also rests on public-private collaborations that expand both public and private power, aggravate transparency and accountability gaps, and create significant obstacles for those seeking algorithmic justice. In response, a nascent body of law proposes technocratic policy changes to foster algorithmic accountability, ethics, and transparency.

This Article examines an alternative vision of algorithmic governance, one advanced primarily by social and labor movements instead of technocrats and firms. …

Ftx: How The Sec Should React, Darian M. Ibrahim

Popular Media

No abstract provided.

Science, Technology, Engineering, And Mathematics (Stem) Project-Based Learning (Pbl) Education: A New Mexico Case Study For Equity And Inclusion, Kimberly A. Scheerer

Teacher Education, Educational Leadership & Policy ETDs

This research addresses how student participation in Science, Technology, Engineering, and Mathematics (STEM) project-based learning (PBL) education activities encourages underrepresented minority student achievement in STEM career field trajectories. Seven New Mexico high school counselors and 12 STEM organization personnel were interviewed during this study. Their responses represent the nuanced professional voices where New Mexico public education intersects with STEM student interest and cultural influence.

For students, STEM PBL can foster deep integration across educational disciplines and enhance STEM career trajectory interest and readiness. STEM education converged with PBL methodologies has the ability to leverage community support while broadening student networks. …

Big Data Affirmative Action, Peter N. Salib

Northwestern University Law Review

As a vast and ever-growing body of social-scientific research shows, discrimination remains pervasive in the United States. In education, work, consumer markets, healthcare, criminal justice, and more, Black people fare worse than whites, women worse than men, and so on. Moreover, the evidence now convincingly demonstrates that this inequality is driven by discrimination. Yet solutions are scarce. The best empirical studies find that popular interventions—like diversity seminars and antibias trainings—have little or no effect. And more muscular solutions—like hiring quotas or school busing—are now regularly struck down as illegal. Indeed, in the last thirty years, the Supreme Court has invalidated …

Marshalling Copyright Knowledge To Understand Four Decades Of Berne, Peter K. Yu

IP Theory

In the year 1978, the 1976 Copyright Act had just entered into effect. Marshall Leaffer, whom this article will affectionately refer to by his first name, had just completed his duties as an attorney advisor at the U.S. Copyright Office. On his way to academia, he, like the fictional character Captain William “Buck” Rogers, was to experience cosmic forces beyond all comprehension. In a freak mishap, his car veered off a rarely used mountain road and was frozen by temperatures beyond imagination. He did not return to academia until more than forty years later. What will he discover upon his …

W. Org. Res. Councils, Et Al. V. U.S. Bureau Of Land Mgmt., Sawyer J. Connelly, Sawyer J. Connelly

Public Land & Resources Law Review

The United States District Court for the District of Montana granted Plaintiffs summary judgment against BLM and the State of Wyoming. The court ruled that BLM violated NEPA and the APA because it failed to consider alternative leasing programs and the broad downstream impacts of coal, oil, and gas leasing in two Powder River Basin resource management plans. This decision followed WORC I & II, in which the court remanded the same plans to BLM to correct deficiencies. Following BLM’s revisions, Plaintiffs again sued in this case, arguing the revisions were still deficient under NEPA.

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 …

The Public Perception Of The #Geneeditedbabies Event Across Multiple Social Media Platforms: Observational Study, Ellen W. Clayton, Congning Ni, Et Al.

Vanderbilt Law School Faculty Publications

In November 2018, a Chinese researcher reported that his team had applied clustered regularly interspaced palindromic repeats or associated protein 9 to delete the gene C-C chemokine receptor type 5 from embryos and claimed that the 2 newborns would have lifetime immunity from HIV infection, an event referred to as #GeneEditedBabies on social media platforms. Although this event stirred a worldwide debate on ethical and legal issues regarding clinical trials with embryonic gene sequences, the focus has mainly been on academics and professionals. However, how the public, especially stratified by geographic region and culture, reacted to these issues is not …

The Centrality Of Data And Compute For Ai Innovation: A Blueprint For The National Research Cloud, Daniel E. Ho, Jennifer King, Russell C. Wald, Christopher Wan

Notre Dame Journal on Emerging Technologies

From the introduction: Artificial intelligence (AI) appears poised to transform the economy across sectors ranging from healthcare and finance to retail and education. What some have coined the “Fourth Industrial Revolution” is driven by three key trends: greater availability of data, increases in computing power, and improvements to algorithm design. First, increasingly large amounts of data have fueled the ability for computers to learn, such as by training an algorithmic language model on all of Wikipedia. Second, better computational capacity (often termed “compute”) and compute capability have enabled researchers to build models that were unimaginable merely ten years ago, spanning …

Note: Structured Psychometrics In Biglaw Talent Acquisition: Ai-Driven Quantitative Fit, Joseph J. Kim

Notre Dame Journal on Emerging Technologies

This Note combines a number of perspectives and disciplines to proffer a unique suggestion toward recognizing better talent and acquiring a new intraindustry competitive edge.

Deepfake Fight: Ai-Powered Disinformation And Perfidy Under The Geneva Conventions, David Nicholas Allen

Notre Dame Journal on Emerging Technologies

Deception and disinformation are as much a part of the battlefield as bullets and bombs. However, just like with bullets and bombs, if the law does not properly regulate a capability’s use the capability could degrade faith in the law. In this respect, this paper examines deepfake technology, a modern artificial intelligence-based capability that can generate superficially-perfect yet wholly invented media content. The paper looks ahead to its potential future applications in armed conflict, processes the ways in which current law contemplates such deception, and distills recommendations for improving governance where needed.

In Defense Of (Virtuous) Autonomous Weapons, Don Howard

Notre Dame Journal on Emerging Technologies

I will argue, we can construct effective means for norming the use of autonomous weapons short of a total ban by building upon the foundation of existing requirements stipulated in Article 36 of Protocol I to the Geneva Conventions that all new weapons technologies be reviewed for compliance with the International Law of Armed Conflict (ILOAC) and International Humanitarian Law (IHL). I begin with a critical review of several of the most commonly encountered arguments in favor of a ban. That is followed by a discussion of the moral opportunities afforded by enhanced autonomy. I conclude with a concrete policy …

Ethical Ai In American Policing, Elizabeth E. Joh

Notre Dame Journal on Emerging Technologies

We know there are problems in the use of artificial intelligence in policing, but we don’t quite know what to do about them. One can also find many reports and white papers today offering principles for the responsible use of AI systems by the government, civil society organizations, and the private sector. Yet, largely missing from the current debate in the United States is a shared framework for thinking about the ethical and responsible use of AI that is specific to policing. There are many AI policy guidance documents now, but their value to the police is limited. Simply repeating …

Note: Regulating Artificial Intelligence: A Call For A United States Artificial Intelligence Agency, Noah John Kahekili Rosenberg

Notre Dame Journal on Emerging Technologies

this Note draws upon two examples of emerging AI technologies that demonstrate the need for federal regulation: autonomous vehicles (i.e., self-driving cars) and algorithm-based hiring software. Part I illustrates the public safety concerns associated with AI technologies by outlining the inadequacy of existing laws and regulations on autonomous vehicles. Part II addresses the shortcomings of current regulations on algorithm-based hiring software and the issue of discrimination and inherent bias in AI. Part III recommends the creation of a new federal agency to guide AI regulation and enforcement.