Law Commons^™

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 …

Vicarious Liability For Ai, Mihailis E. Diamantis

Indiana Law Journal

When an algorithm harms someone—say by discriminating against her, exposing her personal data, or buying her stock using inside information—who should pay? If that harm is criminal, who deserves punishment? In ordinary cases, when A harms B, the first step in the liability analysis turns on what sort of thing A is. If A is a natural phenomenon, like a typhoon or mudslide, B pays, and no one is punished. If A is a person, then A might be liable for damages and sanction. The trouble with algorithms is that neither paradigm fits. Algorithms are trainable artifacts with “off” switches, …

How Can I Tell If My Algorithm Was Reasonable?, Karni A. Chagal-Feferkorn

Michigan Technology Law Review

Self-learning algorithms are gradually dominating more and more aspects of our lives. They do so by performing tasks and reaching decisions that were once reserved exclusively for human beings. And not only that—in certain contexts, their decision-making performance is shown to be superior to that of humans. However, as superior as they may be, self-learning algorithms (also referred to as artificial intelligence (AI) systems, “smart robots,” or “autonomous machines”) can still cause damage.

When determining the liability of a human tortfeasor causing damage, the applicable legal framework is generally that of negligence. To be found negligent, the tortfeasor must have …

Fair Play: Notes On The Algorithmic Soccer Referee, Michael J. Madison

Vanderbilt Journal of Entertainment & Technology Law

The soccer referee stands in for a judge. Soccer’s Video Assistant Referee (VAR) system stands in for algorithms that augment human deciders. Fair play stands in for justice. They are combined and set in a polycentric system of governance, with implications for designing, administering, and assessing human-machine combinations.

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.

Title 2.0: Discrimination Law In A Data-Driven Society, Bryan Casey

Journal of Law and Mobility

More than a quarter century after civil rights activists pioneered America’s first ridesharing network, the connections between transportation, innovation, and discrimination are again on full display. Industry leaders such as Uber, Amazon, and Waze have garnered widespread acclaim for successfully combatting stubbornly persistent barriers to transportation. But alongside this well-deserved praise has come a new set of concerns. Indeed, a growing number of studies have uncovered troubling racial disparities in wait times, ride cancellation rates, and service availability in companies including Uber, Lyft, Task Rabbit, Grubhub, and Amazon Delivery.

Surveying the methodologies employed by these studies reveals a subtle, but …

Robot Criminals, Ying Hu

University of Michigan Journal of Law Reform

When a robot harms humans, are there any grounds for holding it criminally liable for its misconduct? Yes, provided that the robot is capable of making, acting on, and communicating the reasons behind its moral decisions. If such a robot fails to observe the minimum moral standards that society requires of it, labeling it as a criminal can effectively fulfill criminal law’s function of censuring wrongful conduct and alleviating the emotional harm that may be inflicted on human victims.

Imposing criminal liability on robots does not absolve robot manufacturers, trainers, or owners of their individual criminal liability. The former is …

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 …

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 …

A Comment On Privacy And Accountability In Black-Box Medicine, Carl E. Schneider

Michigan Telecommunications & Technology Law Review

Human institutions and activities cannot avoid failures. Anxiety about them often provokes governments to try to prevent those failures. When that anxiety is vivid and urgent, government may do so without carefully asking whether regulation’s costs justify their benefits. Privacy and Accountability in Black Box Medicine admirably labors to bring discipline and rationality to thinking about an important development — the rise of “black-box medicine” — before it causes injuries regulation should have prevented and before it is impaired by improvident regulation. That is, Privacy and Accountability weighs the costs against the benefits of various forms of regulation across the …

Tightening The Ooda Loop: Police Militarization, Race, And Algorithmic Surveillance, Jeffrey L. Vagle

Michigan Journal of Race and Law

This Article examines how military automated surveillance and intelligence systems and techniques, when used by civilian police departments to enhance predictive policing programs, have reinforced racial bias in policing. I will focus on two facets of this problem. First, I investigate the role played by advanced military technologies and methods within civilian police departments. These approaches have enabled a new focus on deterrence and crime prevention by creating a system of structural surveillance where decision support relies increasingly upon algorithms and automated data analysis tools and automates de facto penalization and containment based on race. Second, I will explore these …

Corporate Criminal Liability For Algorithmic Price Fixing In Canada, Theodore Milosevic

Canadian Journal of Law and Technology

The use of computerized algorithms is increasingly common in the modern business environment. An algorithm can be defined as ‘‘a set of mathematical instructions or rules that, especially if given to a computer, will help to calculate an answer to a problem.” As noted in this definition, algorithms are particularly powerful tools when combined with computing power. The proliferation of computerized algorithms in business settings has occasionally led to unintended and injurious outcomes. This is perhaps most notable in relation to the algorithmic trading of securities. The 2010 ‘‘Flash Crash” of the United States (U.S.) financial markets, during which key …

Privacy And Accountability In Black-Box Medicine, Roger Allan Ford, W. Nicholson Price Ii

Michigan Telecommunications & Technology Law Review

Black-box medicine—the use of big data and sophisticated machine-learning techniques for health-care applications—could be the future of personalized medicine. Black-box medicine promises to make it easier to diagnose rare diseases and conditions, identify the most promising treatments, and allocate scarce resources among different patients. But to succeed, it must overcome two separate, but related, problems: patient privacy and algorithmic accountability. Privacy is a problem because researchers need access to huge amounts of patient health information to generate useful medical predictions. And accountability is a problem because black-box algorithms must be verified by outsiders to ensure they are accurate and unbiased, …

Face-To-Face With Facial Recognition Evidence: Admissibility Under The Post-Crawford Confrontation Clause, Joseph Clarke Celentino

Michigan Law Review

In Crawford v. Washington, the Supreme Court announced a major change in Confrontation Clause doctrine, abandoning a decades-old framework that focused on the common law principles of hearsay analysis: necessity and reliability. The new doctrine, grounded in an originalist interpretation of the Sixth Amendment, requires courts to determine whether a particular statement is testimonial. But the Court has struggled to present a coherent definition of the term testimonial. In its subsequent decisions, the Court illustrated that its new Confrontation Clause doctrine could be used to bar forensic evidence, including laboratory test results, if the government failed to produce the …

Leveraging Predictive Policing Algorithms To Restore Fourth Amendment Protections In High-Crime Areas In A Post-Wardlow World, Kelly K. Koss

Chicago-Kent Law Review

Rapid technological changes have led to an explosion in Big Data collection and analysis through complex computerized algorithms. Law enforcement has not been immune to these technological developments. Many local police departments are now using highly advanced predictive policing technologies to predict when and where crime will occur in their communities, and to allocate crime-fighting resources based on these predictions.

Although predictive policing technology has an array of the potential uses, the scope of this Note is limited to addressing how the statistical outputs from these technologies can be used to restore eroded Fourth Amendment rights in alleged high-crime areas. …

Taking A Byte Out Of Abusive Agency Discretion: A Proposal For Disclosure In The Use Of Computer Models, John P. Barker

University of Michigan Journal of Law Reform

This Note examines the need for comprehensive requirements for the release of information pertaining to the use of computer-generated simulations used by federal administrative agencies or parties appearing before regulatory bodies. Part I of this Note defines computer models, identifies some of their current uses in administrative proceedings and describes the advantages of these models. Part II reviews the current requirements for documentation of computer models and the judicial review standards for agency findings. Part III examines the potential problems in the use of models and discusses the need for more adequate disclosure. Part IV describes several tests for verifying …