Law Commons^™

Measuring Change In Copyright Exceptions For Text And Data Mining, Michael Palmedo, Momina Imran, Miguel Alvarenga, Luca Schirru, Duc Le

Joint PIJIP/TLS Research Paper Series

Copyright exceptions for researchers are under debate at the World Intellectual Property Organization and within domestic governments, yet empirical research in this area is rare. In this early working paper, we aim to add to this nascent body of research. We expand PIJIP’s previous review and classification of copyright exceptions in WIPO Members’ laws by tracing changes in the laws over time. We find that most countries have copyright exceptions allowing some unauthorized uses for research purposes. However, most countries’ exceptions restrict some mix of the users, uses, or types of works that are allowed. High-income countries tend to be …

Copyright's Impact On Data Mining In Academic Research, Christian Handke, Lucie Guibault, Joan-Josep Vallbé

Articles, Book Chapters, & Popular Press

With the proliferation of digital data, data mining (DM)—in the sense of the discovery of valuable structures in large sets of data—is expected to increase the productivity of many types of research. This paper discusses how copyright affects DM by academic researchers. In some territories, academic DM is lawful if researchers have lawful access to input works. In other territories such as the European Union, lawful DM additionally requires specific consent by rights holders. Based on bibliometric data and quasi-experimental research designs, we show that where academic DM requires specific rights holder consent: (1) DM publications make up a significantly …

Trimming The Fat: The Gdpr As A Model For Cleaning Up Our Data Usage, Kassandra Polanco

Touro Law Review

No abstract provided.

Planning For Excellence: Insights From An International Review Of Regulators’ Strategic Plans, Adam M. Finkel, Daniel E. Walters, Angus Corbett

Pace Environmental Law Review

What constitutes regulatory excellence? Answering this question is an indispensable first step for any public regulatory agency that is measuring, striving towards, and, ultimately, achieving excellence. One useful way to answer this question would be to draw on the broader literature on regulatory design, enforcement, and management. But, perhaps a more authentic way would be to look at how regulators themselves define excellence. However, we actually know remarkably little about how the regulatory officials who are immersed in the task of regulation conceive of their own success.

In this Article, we investigate regulators’ definitions of regulatory excellence by drawing on …

Mining For Children’S Data In Today’S Digital World, Damin Park

Journal of the National Association of Administrative Law Judiciary

No abstract provided.

A Rule Of Persons, Not Machines: The Limits Of Legal Automation, Frank A. Pasquale

Faculty Scholarship

No abstract provided.

Desperately Seeking Solutions: Using Implementation-Based Solutions For The Troubles Of Information Privacy In The Age Of Data Mining And The Internet Society, Tal Z. Zarsky

Maine Law Review

Our personal information is constantly being recorded, stored and analyzed. Commercial entities watch our every action, storing this data and analyzing it in conjunction with information acquired from third parties. These entities use this knowledge to their benefit (and at times, our detriment) by discriminating between various customers on the basis of this personal information. At the same time, in the media market, large conglomerates can now provide specifically tailored content to individual customers on the basis of such data, thus potentially controlling their perspectives and impairing their autonomy. The expanding use of data mining applications, which enable vendors to …

Judicial Oversight Of Interception Of Communications In The United Kingdom: An Historical And Comparative Analysis, David G. Barnum

Georgia Journal of International & Comparative Law

No abstract provided.

Data-Driven Discrimination At Work, Pauline T. Kim

AI-DR Collection

A data revolution is transforming the workplace. Employers are increasingly relying on algorithms to decide who gets interviewed, hired, or promoted. Although data algorithms can help to avoid biased human decision-making, they also risk introducing new sources of bias. Algorithms built on inaccurate, biased, or unrepresentative data can produce outcomes biased along lines of race, sex, or other protected characteristics. Data mining techniques may cause employment decisions to be based on correlations rather than causal relationships; they may obscure the basis on which employment decisions are made; and they may further exacerbate inequality because error detection is limited and feedback …

Reshaping Ability Grouping Through Big Data, Yoni H. Carmel, Tammy H. Ben-Shahar

Vanderbilt Journal of Entertainment & Technology Law

This Article examines whether incorporating data mining technologies in education can promote equality. Following many other spheres in life, big data technologies that include creating, collecting, and analyzing vast amounts of data about individuals are increasingly being used in schools. This process has already elicited widespread interest among scholars, parents, and the public at large. However, this attention has largely focused on aspects of student privacy and data protection and has overlooked the profound effects data mining may have on educational equality. This Article analyzes the effects of data mining on education equality by focusing on one educational practice--ability grouping--that …

The Use Of Big Data Analytics By The Irs: Efficient Solutions Or The End Of Privacy As We Know It?, Kimberly A. Houser, Debra Sanders

Vanderbilt Journal of Entertainment & Technology Law

This Article examines the privacy issues resulting from the IRS's big data analytics program as well as the potential violations of federal law. Although historically, the IRS chose tax returns to audit based on internal mathematical mistakes or mismatches with third party reports (such as W-2s), the IRS is now engaging in data mining of public and commercial data pools (including social media) and creating highly detailed profiles of taxpayers upon which to run data analytics. This Article argues that current IRS practices, mostly unknown to the general public are violating fair information practices. This lack of transparency and accountability …

Protecting One's Own Privacy In A Big Data Economy, Anita L. Allen

All Faculty Scholarship

Big Data is the vast quantities of information amenable to large-scale collection, storage, and analysis. Using such data, companies and researchers can deploy complex algorithms and artificial intelligence technologies to reveal otherwise unascertained patterns, links, behaviors, trends, identities, and practical knowledge. The information that comprises Big Data arises from government and business practices, consumer transactions, and the digital applications sometimes referred to as the “Internet of Things.” Individuals invisibly contribute to Big Data whenever they live digital lifestyles or otherwise participate in the digital economy, such as when they shop with a credit card, get treated at a hospital, apply …

Reconsidering Constitutional Protection For Health Information Privacy, Wendy K. Mariner

Faculty Scholarship

What kinds of health information should be reported to government for civil purposes? Several competing trends encourage efforts to reassess the scope of constitutional protection for health information: the social and commercial value of health information; the amount of data held by third parties, from health care providers to internet servers; critiques of the third party doctrine exception to Fourth Amendment protection; and concerns about the loss of privacy. This article describes a variety of civil purposes for which health information is collected today. A close analysis of cases applying the third party doctrine, administrative search principles, and the special …

Predicting Cross-Gaming Propensity Using E-Chaid Analysis, Eunju Suh, Matt Alhaery

UNLV Gaming Research & Review Journal

Cross-selling different types of games could provide an opportunity for casino operators to generate additional time and money spent on gaming from existing patrons. One way to identify the patrons who are likely to cross-play is mining individual players’ gaming data using predictive analytics. Hence, this study aims to predict casino patrons’ propensity to play both slots and table games, also known as cross-gaming, by applying a data-mining algorithm to patrons’ gaming data. The Exhaustive Chi-squared Automatic Interaction Detector (E-CHAID) method was employed to predict cross-gaming propensity. The E-CHAID models based on the gaming-related behavioral data produced actionable model accuracy …

Secondary Data: A Primary Concern, Kelsey L. Zottnick

Vanderbilt Journal of Entertainment & Technology Law

This Note addresses privacy concerns implicated by rising secondary data mining. Secondary data mining is the use of personal information for a purpose other than the original. This complex technology drives billions of dollars in commercial industry yet remains largely unregulated. This Note examines the current state of the data mining industry and the behavioral fallacies that belie societal concerns about online privacy. Further, relevant federal, state, and constitutional laws appear outstripped by these technological advances. An analysis of potential privacy solutions examines the advantages and disadvantages of implementing each one through the privacy community, the federal government, and the …

Could Data Broker Information Threaten Physician Prescribing And Professional Behavior?, Marco D. Huesch, Michael K. Ong, Barak D. Richman

Faculty Scholarship

Privacy is threatened by the extent of data collected and sold by consumer data brokers. Physicians, as individual consumers, leave a ‘data trail’ in the offline (e.g. through traditional shopping) and online worlds (e.g. through online purchases and use of social media). Such data could easily and legally be used without a physician’s knowledge or consent to influence prescribing practices or other physician professional behavior. We sought to determine the extent to which such consumer data was available on a sample of more than 3,000 physicians, healthcare faculty and healthcare system staff at one university’s health units. Using just work …

Making Smart Decisions About Surveillance: A Guide For Communities, Chris Conley, Matthew Cagle, Peter Bibring, Jessica Farris, Linda Lye, Mitra Ebadolahi, Nicole Ozer

Faculty Scholarship

California communities are increasingly grappling with whether to deploy new surveillance technologies ranging from drones to license plate readers to facial recognition. This is understandable, since public safety budgets are tight, technology vendors promise the ability to do more with less, and federal agencies or industry sponsors may even offer funding.

But surveillance can be both less effective and far more costly to local agencies and to the community at large than initially imagined, leaving communities saddled with long-term bills for surveillance that doesn't end up making the community safer. Surveillance can also be easily misused, leading to the erosion …

Hot Zone Identification: Analyzing Effects Of Data Sampling On Spam Clustering, Rasib Khan, Mainul Mizan, Ragib Hasan, Alan Sprague

Journal of Digital Forensics, Security and Law

Email is the most common and comparatively the most efficient means of exchanging information in today's world. However, given the widespread use of emails in all sectors, they have been the target of spammers since the beginning. Filtering spam emails has now led to critical actions such as forensic activities based on mining spam email. The data mine for spam emails at the University of Alabama at Birmingham is considered to be one of the most prominent resources for mining and identifying spam sources. It is a widely researched repository used by researchers from different global organizations. The usual process …

Brief Of Digital Humanities And Law Scholars As Amici Curiae In Support Of Defendant-Appellees And Affirmance, (The Authors Guild, Inc., Et Al., V. Google, Inc., Et Al.), Matthew L. Jockers, Matthew Sag, Jason Schultz

Copyright, Fair Use, Scholarly Communication, etc.

Amici are over 150 professors and scholars who teach, write, and research in computer science, the digital humanities, linguistics or law, and two associations that represent Digital Humanities scholars generally.2 Amici have an interest in this case because of its potential impact on their ability to discover and understand, through automated means, the data in and relationships among textual works. Legal Scholar Amici also have an interest in the sound development of intellectual property law. Resolution of the legal issue of copying for non-expressive uses has far-reaching implications for the scope of copyright protection, a subject germane to Amici’s professional …

Rethinking Privacy, William H. Simon

Faculty Scholarship

Anxiety about surveillance and data mining has led many to embrace implausibly expansive and rigid conceptions of privacy. The premises of some current privacy arguments do not fit well with the broader political commitments of those who make them. In particular, liberals seem to have lost touch with the reservations about privacy expressed in the social criticism of some decades ago. They seem unable to imagine that preoccupation with privacy might amount to a “pursuit of loneliness” or how “eyes on the street” might have reassuring connotations. Without denying the importance of the effort to define and secure privacy values, …

Governing, Exchanging, Securing: Big Data And The Production Of Digital Knowledge, Bernard E. Harcourt

Faculty Scholarship

The emergence of Big Data challenges the conventional boundaries between governing, exchange, and security. It ambiguates the lines between commerce and surveillance, between governing and exchanging, between democracy and the police state. The new digital knowledge reproduces consuming subjects who wittingly or unwittingly allow themselves to be watched, tracked, linked and predicted in a blurred amalgam of commercial and governmental projects. Linking back and forth from consumer data to government information to social media, these new webs of information become available to anyone who can purchase the information. How is it that governmental, commercial and security interests have converged, coincided, …

Personalizing Default Rules And Disclosure With Big Data, Ariel Porat, Lior Jacob Strahilevitz

Michigan Law Review

This Article provides the first comprehensive account of personalized default rules and personalized disclosure in the law. Under a personalized approach to default rules, individuals are assigned default terms in contracts or wills that are tailored to their own personalities, characteristics, and past behaviors. Similarly, disclosures by firms or the state can be tailored so that only information likely to be relevant to an individual is disclosed and information likely to be irrelevant to her is omitted. The Article explains how the rise of Big Data makes the effective personalization of default rules and disclosure far easier than it would …

William H. Sorrell, Attorney General Of Vermont, Et Al. V. Ims Health Inc., Et Al. - Amicus Brief In Support Of Petitioners, Kevin Outterson, David Orentlicher, Christopher Robertson, Frank Pasquale

Frank A. Pasquale

On April 26, 2011, the US Supreme Court will hear oral arguments in the Vermont data mining case, Sorrell v. IMS Health Inc. Respondents claim this is the most important commercial speech case in a decade. Petitioner (the State of Vermont) argues this is the most important medical privacy case since Whalen v. Roe. The is an amicus brief supporting Vermont, written by law professors and submitted on behalf of the New England Journal of Medicine

Grand Bargains For Big Data: The Emerging Law Of Health Information, Frank Pasquale

Frank A. Pasquale

No abstract provided.

Addressing The Harm Of Total Surveillance: A Reply To Professor Neil Richards, Danielle Citron, David Gray

David C. Gray

In his insightful article The Dangers of Surveillance, 126 HARV. L. REV. 1934 (2013), Neil Richards offers a framework for evaluating the implications of government surveillance programs that is centered on protecting "intellectual privacy." Although we share his interest in recognizing and protecting privacy as a condition of personal and intellectual development, we worry in this essay that, as an organizing principle for policy, "intellectual privacy" is too narrow and politically fraught. Drawing on other work, we therefore recommend that judges, legislators, and executives focus instead on limiting the potential of surveillance technologies to effect programs of broad and indiscriminate …

Addressing The Harm Of Total Surveillance: A Reply To Professor Neil Richards, Danielle Keats Citron, David C. Gray

Danielle Keats Citron

In his insightful article The Dangers of Surveillance, 126 HARV. L. REV. 1934 (2013), Neil Richards offers a framework for evaluating the implications of government surveillance programs that is centered on protecting "intellectual privacy." Although we share his interest in recognizing and protecting privacy as a condition of personal and intellectual development, we worry in this essay that, as an organizing principle for policy, "intellectual privacy" is too narrow and politically fraught. Drawing on other work, we therefore recommend that judges, legislators, and executives focus instead on limiting the potential of surveillance technologies to effect programs of broad and indiscriminate …

The Rule Of Law In Cyberspace, Mireille Hildebrandt

Mireille Hildebrandt

This is a translation of my inaugural lecture at Radboud University Nijmegen. The Dutch version has been published as a booklet, the English version in available on my bepress site.

Gouvernementalité Algorithmique Et Perspectives D'Émancipation : Le Disparate Comme Condition D'Individuation Par La Relation?, Antoinette Rouvroy, Thomas Berns

Antoinette Rouvroy

La gouvernementalité algorithmique se caractérise notamment par le double mouvement suivant : a) l’abandon de toute forme d’« échelle », d’« étalon », de hiérarchie, au profit d’une normativité immanente et évolutive en temps réel, dont émerge un « double statistique » du monde et qui semble faire table rase des anciennes hiérarchies dessinée par l’homme normal ou l’homme moyen ; b) l’évitement de toute confrontation avec les individus dont les occasions de subjectivation se trouvent raréfiées. Ce double mouvement nous paraît le fruit de la focalisation de la statistique contemporaine sur les relations. Nous tentons d’évaluer dans quelle mesure …

Addressing The Harm Of Total Surveillance: A Reply To Professor Neil Richards, Danielle Keats Citron, David C. Gray

Faculty Scholarship

In his insightful article The Dangers of Surveillance, 126 HARV. L. REV. 1934 (2013), Neil Richards offers a framework for evaluating the implications of government surveillance programs that is centered on protecting "intellectual privacy." Although we share his interest in recognizing and protecting privacy as a condition of personal and intellectual development, we worry in this essay that, as an organizing principle for policy, "intellectual privacy" is too narrow and politically fraught. Drawing on other work, we therefore recommend that judges, legislators, and executives focus instead on limiting the potential of surveillance technologies to effect programs of broad and indiscriminate …

Grand Bargains For Big Data: The Emerging Law Of Health Information, Frank Pasquale

Maryland Law Review

No abstract provided.