Law Commons^™

Computationally Assessing Suspicion, Wesley M. Oliver, Morgan A. Gray, Jaromir Savelka, Kevin D. Ashley

University of Cincinnati Law Review

Law enforcement officers performing drug interdiction on interstate highways have to decide nearly every day whether there is reasonable suspicion to detain motorists until a trained dog can sniff for the presence of drugs. The officers’ assessments are often wrong, however, and lead to unnecessary detentions of innocent persons and the suppression of drugs found on guilty ones. We propose a computational method of evaluating suspicion in these encounters and offer experimental results from early efforts demonstrating its feasibility. With the assistance of large language and predictive machine learning models, it appears that judges, advocates, and even police officers could …

The Evidentiary Implications Of Interpreting Black-Box Algorithms, Varun Bhatnagar

Northwestern Journal of Technology and Intellectual Property

Biased black-box algorithms have drawn increasing levels of scrutiny from the public. This is especially true for those black-box algorithms with the potential to negatively affect protected or vulnerable populations.1 One type of these black-box algorithms, a neural network, is both opaque and capable of high accuracy. However, neural networks do not provide insights into the relative importance, underlying relationships, structures of the predictors or covariates with the modelled outcomes.2 There are methods to combat a neural network’s lack of transparency: globally or locally interpretable post-hoc explanatory models.3 However, the threat of such measures usually does not bar an actor …

Risk Assessment And Immigration Court, Richard Frankel

Washington and Lee Law Review

Risk assessment and algorithmic tools have become increasingly popular in recent years, particularly with respect to detention and incarceration decisions. The emergence of big data and the increased sophistication of algorithmic design hold the promise of more accurately predicting whether an individual is dangerous or a flight risk, overcoming human bias in decision-making, and reducing detention without compromising public safety. But these tools also carry the potential to exacerbate racial disparities in incarceration, create a false veneer of objective scientific accuracy, and spawn opaque decision-making by “black box” computer programs.

While scholars have focused much attention on how judges in …

Evolving Privacy Protections For Emerging Machine Learning Data Under Carpenter V. United States, Emily Nicolella

FIU Law Review

The Fourth Amendment’s third-party doctrine eliminates an individual’s reasonable expectation of privacy in information they willingly turn over to third parties. Government scrutiny of this information is not considered a search under the Fourth Amendment and is therefore not given constitutional protections. In the 2018 case Carpenter v. United States, the Supreme Court created an exception to the third-party doctrine. In Carpenter, a case involving the warrantless use of cell site location information (CSLI) in a criminal investigation, the Court held that individuals do have a reasonable expectation of privacy regarding CSLI. According to Chief Justice Roberts, despite the necessary …

Let The Machines Do The Dirty Work: Social Media, Machine Learning Technology And The Iteration Of Racialized Surveillance, Subhah Wadhawan

Canadian Journal of Law and Technology

Post 9/11, where the current social and cultural temperature has constructed Islam as interchangeable with terrorism, digital intermediaries have responded with increased censorship of speech related to, emerging from, or advocating Islamic ideology. At the heart of this paper is the argument that digital intermediaries have relied on the opaqueness of machine learning technology (‘‘MLT”) to realize racialized surveillance, whereby speech concerning Islamic content has been disproportionally censored. This paper maps out how inherent biases concerning the ideology of Islam have been interwoven into the coding and machine learning used by the major tech giants. As a result of the …

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 …

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 …

Professions And Expertise: How Machine Learning And Blockchain Are Redesigning The Landscape Of Professional Knowledge And Organization, John Flood, Lachlan Robb

University of Miami Law Review

Machine learning has entered the world of the professions with differential impacts. Automation will have huge impacts on the nature of work and society. Engineering, architecture, and medicine are early and enthusiastic adopters of automation. Other professions, especially law, are late and, in some cases, reluctant adopters. This Article examines the effects of artificial intelligence (“AI”) and Blockchain on professions and their knowledge bases. We start by examining the nature of expertise in general and the function of expertise in law. Using examples from law, such as Gulati and Scott’s analysis of how lawyers create (or don’t create) legal agreements, …