Computer Law Commons^™

Legal Considerations On Predictive Policing Based On Italian ‘Algorithmic Administration’ Principles, Stefano Rossa

Yearbook of Antitrust and Regulatory Studies

In Beck’s current risk society, the State is faced with a dilemma. To fail before the risk but to keep the sphere of citizens’ rights intact; or not to fail but to restrict fundamental rights? This payoff turns out to be the main issue that juridical reflections on the use of predictive technology tools in the public sector must consider. Policing is an administrative function that is mainly composed of acts of a preventive nature. By using ICT, it is possible to employ AI systems with a very high rate of certainty to ‘predict’ future crime scene. But is it …

Control As A Constitutional Threshold: Moody V. Netchoice And The Case For Human Authorship, Giselle Goad

Northwestern University Law Review

The Supreme Court’s 2024 decision in Moody v. NetChoice, LLC left a critical question unanswered: when do algorithmic outputs on social media platforms, such as recommended posts and videos, constitute the platform’s protected speech under the First Amendment? This Note contends that courts and litigants should borrow from the First Amendment’s speech-promoting partner, copyright law, and its authorship framework when answering that question. Copyright doctrine has already begun to grapple with how much human control is required over expressive outputs generated with the aid of technology, including AI, in order for an author to receive copyright protection over those outputs. …

From ‘Gig Work’ To Algorithmically Mediated Work: Shifting The Focus To Technological Control In Work Regulation, Jasoon Chelat

Indian Journal of Law and Technology

Platform-based work is finding a place in legislative instruments in India in recent years, under the Code on Social Security, 2020, as well as state-level legislations. In this paper, I argue that these efforts to extend protections to gig or platform work are limited in their understanding of the way work is shaped by digital technologies both within and outside of platforms. Platform-based work regulation seems to have skipped a step: the regulatory discourse has moved on to a welfare-focused model present in informal work, without examining existing jurisprudence on worker rights relevant to digitally mediated work. These legislative instruments …

The Proactive Approach Of Artificial Intelligence In Monitoring And Analyzing Illegal Money Laundering Operations In The Virtual World, Ammar Yasser El-Bably

Journal of Police and Legal Sciences

The research dealt with the proactive method of artificial intelligence in monitoring and analyzing non-suspicious operations of money laundering in the virtual world, especially the Internet and dark web, where it dealt with the risks created for those networks and their exploitation for the benefit of terrorist and criminal organizations, money laundering, the purchase of weapons and drugs, human trafficking and financial fraud, where Internet users around the world reached 5 billion users, and the volume of money laundering crimes became 2.8 Trillion dollars, according to United Nations and International Monetary Fund statistics 2023 AI applications where algorithms, machine learning, …

Beyond Data Deletion: Addressing Anticompetitive Conduct In The Era Of Machine Learning, Vaibhav Srikaran

Washington Journal of Law, Technology & Arts

Like a hamster wheel, the “virtuous cycle” of data collection, collation, and computation spins to create algorithms to assist modern business operations. Companies accumulate data by the terabyte with hopes that their army of data scientists can make sense of all the noise using machine learning. Potential profits encourage companies to seek out data—sometimes unlawfully through collusion. The use of unlawfully collected data in algorithms harms competition. Such data provides a competitive edge that is not accessible to all marketplace participants. Antitrust laws can police unlawful data sharing, but existing remedies are not effective for restoring competition.

Merely deleting ill-gotten …

Gendering The New International Convention On Cybercrimes And New Norms On Artificial Intelligence And Emerging Technologies, Rangita De Silva De Alwis

Washington Journal of Law, Technology & Arts

The trifecta of the Digital Global Compact (2024), the UN General Assembly Resolution on AI for Sustainable Development (2024) and the new Cyber Crime Convention (2025) come at a time of what seems to be an inexorable march of new technology. It is also at a time of transborder disruption caused by data breaches and cyber threats, that binding international norms can respond to global challenge. However, it must be emphasized that digital violence, developer bias, and data bias are not new phenomena, they have existed since the origins of the internet. Data that is used to train machine-learning algorithms …

Continuing Discrimination In The Times Of Technology: Women, Work, Algorithms And Law In India, Sejal Chandak Ms

Indian Journal of Law and Technology

Human societies are discriminatory. So, it has been an unrelenting effort to eliminate what divides us. While there have been leapfrog developments in this regard, we need to consider newer challenges now that technology is taking over public and private spaces. The author, in this article, discusses gender-based algorithmic discrimination in workplaces and argues that there is an urgent need to enforce laws for regulating algorithmic discrimination. India is in a precarious position. It has been consistently faring poorly when it comes to the gender gap in work. It lacks a comprehensive and codified anti-discriminatory law; and lacks laws to …

Distinguishing Privacy Law: A Critique Of Privacy As Social Taxonomy, Maria P. Angel, Ryan Calo

Scholarly Works

What distinguishes violations of privacy from other harms? This has proven a surprisingly difficult question to answer. For over a century, privacy law scholars labored to define the illusive concept of privacy. Then they gave up. Efforts at distinguishing privacy came to be superseded at the turn of the millennium by a new approach: a taxonomy of privacy problems grounded in social recognition. Privacy law became the field that simply studies whatever courts or scholars talk about as related to privacy.

And it worked. Decades into privacy as social taxonomy, the field has expanded to encompass a broad range of …

Privacy's Algorithmic Turn, Maria P. Angel

Scholarly Works

As algorithms have taken over contemporary society, a portion of American privacy law scholars has gradually transformed information privacy into a post- algorithmic concept. Besides enabling individuals to protect their autonomy and attain certain collective benefits, these scholars now expect information privacy to act as the government's tool to protect society against data extraction and its consequent power asymmetries. This Article presents evidence of this transfor- mation-here referred to as "privacy's algorithmic turn"-, identifying its two main features: (1) a change in what is usually considered privacy harms, and (2) a transformation of the tools proposed to protect privacy. Additionally, …

Trademarks In An Algorithmic World, Christine Haight Farley

Washington Law Review

According to the sole normative foundation for trademark protection—“search costs” theory—trademarks transmit useful information to consumers, enabling an efficient marketplace. The marketplace, however, is in the midst of a fundamental change. Increasingly, retail is virtual, marketing is data-driven, and purchasing decisions are automated by AI. Predictive analytics are changing how consumers shop. Search costs theory no longer accurately describes the function of trademarks in this marketplace. Consumers now have numerous digital alternatives to trademarks that more efficiently provide them with increasingly accurate product information. Just as store shelves are disappearing from consumers’ retail experience, so are trademarks disappearing from their …

Hunting And Gathering On The Legal Information Savannah, Susan Nevelow Mart, Adam Litzler, David Gunderman

Publications

This article asks, what is it like for novice researchers to research real-world legal problems using four platforms: Bloomberg Law, Fastcase, Lexis Advance, and Westlaw? The study findings produced some surprises, as well as some clear implications for teaching legal research.

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.

“Computer Says No!”: The Impact Of Automation On The Discretionary Power Of Public Officers, Doa A. Elyounes

Vanderbilt Journal of Entertainment & Technology Law

The goal of this Article is to unpack the “human in the loop” requirement in the process of automation. It will analyze the impact of automation on street-level bureaucrats and lay out the steps policy makers need to take into account to ensure that meaningful human discretion is maintained. This issue is examined by comparing two algorithms related to the use of automation to detect and investigate fraud in welfare benefits. The first algorithm is used by Michigan’s Unemployment Insurance Agency for detecting and investigating unemployment fraud. This is a draconian algorithm with the ability to automatically decide to cut …

Book Review, Aamir S. Abdullah

Publications

No abstract provided.

The Right To Contest Ai, Margot E. Kaminski, Jennifer M. Urban

Publications

Artificial intelligence (AI) is increasingly used to make important decisions, from university admissions selections to loan determinations to the distribution of COVID-19 vaccines. These uses of AI raise a host of concerns about discrimination, accuracy, fairness, and accountability.

In the United States, recent proposals for regulating AI focus largely on ex ante and systemic governance. This Article argues instead—or really, in addition—for an individual right to contest AI decisions, modeled on due process but adapted for the digital age. The European Union, in fact, recognizes such a right, and a growing number of institutions around the world now call for …

Algorithmic Opacity, Private Accountability, And Corporate Social Disclosure In The Age Of Artificial Intelligence, Sylvia Lu

Vanderbilt Journal of Entertainment & Technology Law

Today, firms develop machine-learning algorithms to control human decisions in nearly every industry, creating a structural tension between commercial opacity and democratic transparency. In many of their commercial applications, advanced algorithms are technically complicated and privately owned, which allows them to hide from legal regimes and prevents public scrutiny. However, they may demonstrate their negative effects—erosion of democratic norms, damages to financial gains, and extending harms to stakeholders—without warning. Nevertheless, because the inner workings and applications of algorithms are generally incomprehensible and protected as trade secrets, they can be completely shielded from public surveillance. One of the solutions to this …

Artificial Financial Intelligence, William Magnuson

Faculty Scholarship

Recent advances in the field of artificial intelligence have revived long-standing debates about what happens when robots become smarter than humans. Will they destroy us? Will they put us all out of work? Will they lead to a world of techno-savvy haves and techno-ignorant have-nots? These debates have found particular resonance in finance, where computers already play a dominant role. High-frequency traders, quant hedge funds, and robo-advisors all represent, to a greater or lesser degree, real-world instantiations of the impact that artificial intelligence is having on the field. This Article will argue that the primary danger of artificial intelligence in …

Secret Conviction Programs, Meghan J. Ryan

Washington and Lee Law Review

Judges and juries across the country are convicting criminal defendants based on secret evidence. Although defendants have sought access to the details of this evidence—the results of computer programs and their underlying algorithms and source codes—judges have generally denied their requests. Instead, judges have prioritized the business interests of the for-profit companies that developed these “conviction programs” and which could lose market share if the secret algorithms and source codes on which the programs are based were exposed. This decision has jeopardized criminal defendants’ constitutional rights.

Can An Improved Disclosure Mechanism Moderate Algorithm-Based Software Patentability In The Public Interest?, Vinicius Sala

Cybaris®

No abstract provided.

Ethical Testing In The Real World: Evaluating Physical Testing Of Adversarial Machine Learning, Kendra Albert, Maggie Delano, Jonathon Penney, Afsaneh Ragot, Ram Shankar Siva Kumar

Articles, Book Chapters, & Popular Press

This paper critically assesses the adequacy and representativeness of physical domain testing for various adversarial machine learning (ML) attacks against computer vision systems involving human subjects. Many papers that deploy such attacks characterize themselves as “real world.” Despite this framing, however, we found the physical or real-world testing conducted was minimal, provided few details about testing subjects and was often conducted as an afterthought or demonstration. Adversarial ML research without representative trials or testing is an ethical, scientific, and health/safety issue that can cause real harms. We introduce the problem and our methodology, and then critique the physical domain testing …

Platforms, The First Amendment And Online Speech: Regulating The Filters, Sofia Grafanaki

Pace Law Review

In recent years, online platforms have given rise to multiple discussions about what their role is, what their role should be, and whether they should be regulated. The complex nature of these private entities makes it very challenging to place them in a single descriptive category with existing rules. In today’s information environment, social media platforms have become a platform press by providing hosting as well as navigation and delivery of public expression, much of which is done through machine learning algorithms. This article argues that there is a subset of algorithms that social media platforms use to filter public …

Inside The Black Box Of Search Algorithms, Susan Nevelow Mart, Joe Breda, Ed Walters, Tito Sierra, Khalid Al-Kofahi

Publications

A behind-the-scenes look at the algorithms that rank results in Bloomberg Law, Fastcase, Lexis Advance, and Westlaw.

The First Amendment Case For Public Access To Secret Algorithms Used In Criminal Trials, Vera Eidelman

Georgia State University Law Review

As this Article sets forth, once a computerized algorithm is used by the government, constitutional rights may attach. And, at the very least, those rights require that algorithms used by the government as evidence in criminal trials be made available—both to litigants and the public. Scholars have discussed how the government’s refusal to disclose such algorithms runs afoul of defendants’ constitutional rights, but few have considered the public’s interest in these algorithms—or the widespread impact that public disclosure and auditing could have on ensuring their quality.

This Article aims to add to that discussion by setting forth a theory of …

Deploying The Secret Police: The Use Of Algorithms In The Criminal Justice System, Jessica Gabel Cino

Georgia State University Law Review

Algorithms saturate our lives today; from curated song lists to recommending “friends” and news feeds, they factor into some of the most human aspects of decision-making, tapping into preferences based on an ever-growing amount of data. Regardless of whether the algorithm pertains to routing you around traffic jams or finding your next dinner, there is little regulation and even less transparency regarding just how these algorithms work. Paralleling this societal adoption, the criminal justice system now employs algorithms in some of the most important aspects of investigation and decision-making.

The lack of oversight is abundantly apparent in the criminal justice …

The Gdpr’S Version Of Algorithmic Accountability, Margot Kaminski

Publications

No abstract provided.

Results May Vary, Susan Nevelow Mart

Publications

No abstract provided.

Understanding The Human Element In Search Algorithms And Discovering How It Affects Search Results, Susan Nevelow Mart

Publications

When legal researchers search in online databases for the information they need to solve a legal problem, they need to remember that the algorithms that are returning results to them were designed by humans. The world of legal research is a human-constructed world, and the biases and assumptions the teams of humans that construct the online world bring to the task are imported into the systems we use for research. This article takes a look at what happens when six different teams of humans set out to solve the same problem: how to return results relevant to a searcher’s query …

Regulating Black-Box Medicine, W. Nicholson Price Ii

Michigan Law Review

Data drive modern medicine. And our tools to analyze those data are growing ever more powerful. As health data are collected in greater and greater amounts, sophisticated algorithms based on those data can drive medical innovation, improve the process of care, and increase efficiency. Those algorithms, however, vary widely in quality. Some are accurate and powerful, while others may be riddled with errors or based on faulty science. When an opaque algorithm recommends an insulin dose to a diabetic patient, how do we know that dose is correct? Patients, providers, and insurers face substantial difficulties in identifying high-quality algorithms; they …

Artificial Intelligence In Health Care: Applications And Legal Implications, W. Nicholson Price Ii

Articles

Artificial intelligence (AI) is rapidly moving to change the healthcare system. Driven by the juxtaposition of big data and powerful machine learning techniques—terms I will explain momentarily—innovators have begun to develop tools to improve the process of clinical care, to advance medical research, and to improve efficiency. These tools rely on algorithms, programs created from healthcare data that can make predictions or recommendations. However, the algorithms themselves are often too complex for their reasoning to be understood or even stated explicitly. Such algorithms may be best described as “black-box.” This article briefly describes the concept of AI in medicine, including …

Data For The Algorithm As A Human Artifact: Implications For Legal [Re]Search, Susan Nevelow Mart

Research Data

These documents underlie and are cited in this empirical study: Susan Nevelow Mart, The Algorithm as a Human Artifact: Implications for Legal [Re]Search, 109 Law Libr. J. 387, 409 n.123 (2017), available at http://scholar.law.colorado.edu/articles/755/.

The ZIP file contains three files: one PDF document ("Tables for Charts 1-3"), and two SPSS files ("Data Archive" and "Syntax Archive" (SPSS version 24)). The "Syntax Archive" file may be viewed in a text editor (e.g., Notepad) as well as in SPSS.