Law Commons^™

Governing Smart Cities As Knowledge Commons - Introduction, Chapter 1 & Conclusion, Brett M. Frischmann, Michael J. Madison, Madelyn Sanfilippo

Book Chapters

Smart city technology has its value and its place; it isn’t automatically or universally harmful. Urban challenges and opportunities addressed via smart technology demand systematic study, examining general patterns and local variations as smart city practices unfold around the world. Smart cities are complex blends of community governance institutions, social dilemmas that cities face, and dynamic relationships among information and data, technology, and human lives. Some of those blends are more typical and common. Some are more nuanced in specific contexts. This volume uses the Governing Knowledge Commons (GKC) framework to sort out relevant and important distinctions. The framework grounds …

#Audited: Social Media And Tax Enforcement, Michelle Lyon Drumbl

Scholarly Articles

With limited resources and a diminished budget, it is not surprising that the Internal Revenue Service would seek new tools to maximize its enforcement efficiency. Automation and technology provide new opportunities for the IRS, and in turn, present new concerns for taxpayers. In December 2018, the IRS signaled its interest in a tool to access publicly available social media profiles of individuals in order to “expedite IRS case resolution for existing compliance cases.” This has important implications for taxpayer privacy.

Moreover, the use of social media in tax enforcement may pose a particular harm to an especially vulnerable population: low-income …

Factors Affecting Access To Administrative Health Data For Research In Canada: A Study Protocol, Cynthia Kendell, Adrian Levy, Geoff Porter, Elaine Gibson, Robin Urquhart

Articles, Book Chapters, & Popular Press

In Canada, most provinces have established administrative health data repositories to facilitate access to these data for research. Anecdotally, researchers have described delays and substantial inter-provincial variations in the timeliness of data access approvals and receipt of data. Currently, the reasons for these delays and variations in timeliness are not well understood. This paper provides a study protocol for (1) identifying the factors affecting access to administrative health data for research within select Canadian provinces, and (2) comparing factors across provinces to assess whether and how they contribute to inter-provincial variations in access to administrative health data for research.

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

Articles

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.

Privacy In Pandemic: Law, Technology, And Public Health In The Covid-19 Crisis, Tiffany Li

Faculty Scholarship

The COVID-19 pandemic has caused millions of deaths and disastrous consequences around the world, with lasting repercussions for every field of law, including privacy and technology. The unique characteristics of this pandemic have precipitated an increase in use of new technologies, including remote communications platforms, healthcare robots, and medical AI. Public and private actors are using new technologies, like heat sensing, and technologically-influenced programs, like contact tracing, alike in response, leading to a rise in government and corporate surveillance in sectors like healthcare, employment, education, and commerce. Advocates have raised the alarm for privacy and civil liberties violations, but the …

Healthtech: How Blockchain Can Simplify Healthcare Compliance, Kathryn M. Bennett

Washington and Lee Journal of Civil Rights and Social Justice

This Note broadly explores solutions to modern-day accessibility and security problems latent in electronic health records. Specifically, this Note discusses HIPAA and HITECH, the current law in place, and how blockchain technology can be used to fix the accessibility and security problems of current electronic health records. This Note proposes that blockchain technology can help a healthcare industry struggling to adhere to the current rule of law in an era of Big Data. Further, Blockchain technology can help individual consumers, particularly those with significant health issues, obtain the best possible medical care while simultaneously keeping their private and sensitive information …

The Exclusionary Rule In The Age Of Blue Data, Andrew Ferguson

Articles in Law Reviews & Other Academic Journals

In Herring v. United States, Chief Justice John Roberts reframed the Supreme Court’s understanding of the exclusionary rule: “As laid out in our cases, the exclusionary rule serves to deter deliberate, reckless, or grossly negligent conduct, or in some circumstances recurring or systemic negligence.” The open question remains: how can defendants demonstrate sufficient recurring or systemic negligence to warrant exclusion? The Supreme Court has never answered the question, although the absence of systemic or recurring problems has figured prominently in two recent exclusionary rule decisions. Without the ability to document recurring failures, or patterns of police misconduct, courts can dismiss …

The Promise And Perils Of Algorithmic Lenders’ Use Of Big Data, Matthew Adam Bruckner

Chicago-Kent Law Review

Tens of millions of Americans lack access to traditional forms of credit and must rely on payday and pawn loans instead. “Algorithmic lending 2.0” promises to enable fintech companies to lend to those excluded from traditional forms of credit. Version 2.0 algorithmic lenders claim to use Big Data and machine learning to increase credit access by making better predictions about prospective borrowers’ creditworthiness and decreasing the cost of credit. Supporters also claim that algorithmic lending 2.0 removes human bias from the financial services sector. Detractors have cast doubt on both claims, arguing that there is scant evidence that algorithmic lending …

Illuminating Black Data Policing, Andrew Ferguson

Articles in Law Reviews & Other Academic Journals

The future of policing will be driven by data. Crime, criminals, and patterns of criminal activity will be reduced to data to be studied, crunched, and predicted. The benefits of big data policing involve smarter policing, faster investigation, predictive deterrence, and the ability to visualize crime problems in new ways. Not surprisingly then, police administrators have been seeking out new partnerships with sophisticated private data companies and experimenting with new surveillance technologies. This potential future, however, has a very present limitation. It is a limitation largely ignored by adopting jurisdictions and could, if left unaddressed, delegitimize the adoption and use …

Is The Future Of Law A Driverless Car? Assessing How The Data Analytics Revolution Will Transform Legal Practice, Eric L. Talley

Faculty Scholarship

Machine learning and artificial intelligence technologies (“data analytics”) are quickly transforming research and practice in law, raising questions of whether the law can survive as a vibrant profession for natural persons to enter. In this article, I argue that data analytics approaches are overwhelmingly likely to continue to penetrate law, even in domains that have heretofore been dominated by human decision makers. As a vehicle for demonstrating this claim, I describe an extended example of using machine learning to identify and categorize fiduciary duty waiver provisions in publicly disclosed corporate documents. Notwithstanding the power of machine learning techniques, however, I …

A Machine Learning Classifier For Corporate Opportunity Waivers, Gabriel V. Rauterberg, Eric L. Talley

Faculty Scholarship

Rauterberg & Talley (2017) develop a data set of “corporate opportunity waivers” (COWs) – significant contractual modifications of fiduciary duties – sampled from SEC filings. Part of their analysis utilizes a machine learning (ML) classifier to extend their data set beyond the hand-coded sample. Because the ML approach is likely unfamiliar to some readers, and in the light of its great potential across other areas of law and finance research, this note explains the basic components using a simple example, and it demonstrates strategies for calibrating and evaluating the classifier.

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. …

Big Data And Predictive Reasonable Suspicion, Andrew Ferguson

Articles in Law Reviews & Other Academic Journals

The Fourth Amendment requires “reasonable suspicion” to seize a suspect. As a general matter, the suspicion derives from information a police officer observes or knows. It is individualized to a particular person at a particular place. Most reasonable suspicion cases involve police confronting unknown suspects engaged in observable suspicious activities. Essentially, the reasonable suspicion doctrine is based on “small data” – discrete facts involving limited information and little knowledge about the suspect.But what if this small data is replaced by “big data”? What if police can “know” about the suspect through new networked information sources? Or, what if predictive analytics …

The Scored Society: Due Process For Automated Predictions, Danielle K. Citron

Faculty Scholarship

Big Data is increasingly mined to rank and rate individuals. Predictive algorithms assess whether we are good credit risks, desirable employees, reliable tenants, valuable customers — or deadbeats, shirkers, menaces, and “wastes of time.” Crucial opportunities are on the line, including the ability to obtain loans, work, housing, and insurance. Though automated scoring is pervasive and consequential, it is also opaque and lacking oversight. In one area where regulation does prevail — credit — the law focuses on credit history, not the derivation of scores from data.

Procedural regularity is essential for those stigmatized by “artificially intelligent” scoring systems. The …

Digital Security In The Expository Society: Spectacle, Surveillance, And Exhibition In The Neoliberal Age Of Big Data, Bernard E. Harcourt

Faculty Scholarship

In 1827, Nicolaus Heinrich Julius, a professor at the University of Berlin, identified an important architectural mutation in nineteenth-century society that reflected a deep disruption in our technologies of knowledge and a profound transformation in relations of power across society: Antiquity, Julius observed, had discovered the architectural form of the spectacle; but modern times had operated a fundamental shift from spectacle to surveillance. Michel Foucault would elaborate this insight in his 1973 Collège de France lectures on The Punitive Society, where he would declare: “[T]his is precisely what happens in the modern era: the reversal of the spectacle into surveillance…. …