Jules Polonetsky

Bio: Jules Polonetsky is an academic researcher from Future of Privacy Forum. The author has contributed to research in topics: Data Protection Act 1998 & Big data. The author has an hindex of 13, co-authored 24 publications receiving 1313 citations. Previous affiliations of Jules Polonetsky include Yale University & Washington and Lee University.

Big Data for All: Privacy and User Control in the Age of Analytics

Abstract: We live in an age of “big data.” Data have become the raw material of production, a new source for immense economic and social value. Advances in data mining and analytics and the massive increase in computing power and data storage capacity have expanded by orders of magnitude the scope of information available for businesses and government. Data are now available for analysis in raw form, escaping the confines of structured databases and enhancing researchers’ abilities to identify correlations and conceive of new, unanticipated uses for existing information. In addition, the increasing number of people, devices, and sensors that are now connected by digital networks has revolutionized the ability to generate, communicate, share, and access data. Data creates enormous value for the world economy, driving innovation, productivity, efficiency and growth. At the same time, the “data deluge” presents privacy concerns which could stir a regulatory backlash dampening the data economy and stifling innovation. In order to craft a balance between beneficial uses of data and in individual privacy, policymakers must address some of the most fundamental concepts of privacy law, including the definition of “personally identifiable information”, the role of individual control, and the principles of data minimization and purpose limitation. This article emphasizes the importance of providing individuals with access to their data in usable format. This will let individuals share the wealth created by their information and incentivize developers to offer user-side features and applications harnessing the value of big data. Where individual access to data is impracticable, data are likely to be de-identified to an extent sufficient to diminish privacy concerns. In addition, organizations should be required to disclose their decisional criteria, since in a big data world it is often not the data but rather the inferences drawn from them that give cause for concern.

Big Data for All: Privacy and User Control in the Age of Analytics

Abstract: We live in an age of “big data.” Data have become the raw material of production, a new source for immense economic and social value. Advances in data mining and analytics and the massive increase in computing power and data storage capacity have expanded by orders of magnitude the scope of information available for businesses and government. Data are now available for analysis in raw form, escaping the confines of structured databases and enhancing researchers’ abilities to identify correlations and conceive of new, unanticipated uses for existing information. In addition, the increasing number of people, devices, and sensors that are now connected by digital networks has revolutionized the ability to generate, communicate, share, and access data. Data creates enormous value for the world economy, driving innovation, productivity, efficiency and growth. At the same time, the “data deluge” presents privacy concerns which could stir a regulatory backlash dampening the data economy and stifling innovation. In order to craft a balance between beneficial uses of data and in individual privacy, policymakers must address some of the most fundamental concepts of privacy law, including the definition of “personally identifiable information”, the role of individual control, and the principles of data minimization and purpose limitation. This article emphasizes the importance of providing individuals with access to their data in usable format. This will let individuals share the wealth created by their information and incentivize developers to offer user-side features and applications harnessing the value of big data. Where individual access to data is impracticable, data are likely to be de-identified to an extent sufficient to diminish privacy concerns. In addition, organizations should be required to disclose their decisional criteria, since in a big data world it is often not the data but rather the inferences drawn from them that give cause for concern.

SmartPrivacy for the Smart Grid: embedding privacy into the design of electricity conservation

Abstract: The 2003 blackout in the northern and eastern U.S. and Canada which caused a $6 billion loss in economic revenue is one of many indicators that the current electrical grid is outdated. Not only must the grid become more reliable, it must also become more efficient, reduce its impact on the environment, incorporate alternative energy sources, allow for more consumer choices, and ensure cyber security. In effect, it must become “smart.” Significant investments in the billions of dollars are being made to lay the infrastructure of the future Smart Grid. However, the authors argue that we must take great care not to sacrifice consumer privacy amidst an atmosphere of unbridled enthusiasm for electricity reform. Information proliferation, lax controls and insufficient oversight of this information could lead to unprecedented invasions of consumer privacy. Smart meters and smart appliances will constitute a data explosion of intimate details of daily life, and it is not yet clear who will have access to this information beyond a person’s utility provider. The authors of this paper urge the adoption of Dr. Ann Cavoukian’s conceptual model ‘SmartPrivacy’ to prevent potential invasions of privacy while ensuring full functionality of the Smart Grid. SmartPrivacy represents a broad arsenal of protections, encapsulating everything necessary to ensure that all of the personal information held by an organization is appropriately managed. These include: Privacy by Design; law, regulation and independent oversight; accountability and transparency; market forces, education and awareness; audit and control; data security; and fair information practices. Each of these elements is important, but the concept of Privacy by Design represents its sine qua non. When applying SmartPrivacy to the Smart Grid, not only will the grid be able to, for example, become increasingly resistant to attack and natural disasters—it will be able to do so while also becoming increasingly resistant to data leakage and breaches of personal information. The authors conclude that SmartPrivacy must be built into the Smart Grid during its current nascent stage, allowing for both consumer control of electricity consumption and consumer control of their personal information, which must go hand in hand. Doing so will ensure that consumer confidence and trust is gained, and that their participation in the Smart Grid contributes to the vision of creating a more efficient and environmentally friendly electrical grid, as well as one that is protective of privacy. This will result in a positive-sum outcome, where both environmental efficiency and privacy can coexist.

A Theory of Creepy: Technology, Privacy and Shifting Social Norms

Abstract: The rapid evolution of digital technologies has hurled to the forefront of public and legal discourse dense social and ethical dilemmas that we have hardly begun to map and understand. In the near past, general community norms helped guide a clear sense of ethical boundaries with respect to privacy. One does not peek into the window of a house even if it is left open. One does not hire a private detective to investigate a casual date or the social life of a prospective employee. Yet with technological innovation rapidly driving new models for business and inviting new types of personal socialization, we often have nothing more than a fleeting intuition as to what is right or wrong. Our intuition may suggest that it is responsible to investigate the driving record of the nanny who drives our child to school, since such tools are now readily available. But is it also acceptable to seek out the records of other parents in our child’s car pool or of a date who picks us up by car? Alas, intuitions and perceptions of “creepiness” are highly subjective and difficult to generalize as social norms are being strained by new technologies and capabilities. And businesses that seek to create revenue opportunities by leveraging newly available data sources face huge challenges trying to operationalize such subjective notions into coherent business and policy strategies. This article presents a set of social and legal considerations to help individuals, engineers, businesses and policymakers navigate a world of new technologies and evolving social norms. These considerations revolve around concepts that we have explored in prior work, including enhanced transparency; accessibility to information in usable format; and the elusive principle of context.

A Theory of Creepy: Technology, Privacy, and Shifting Social Norms

Abstract: The rapid evolution of digital technologies has hurled to the forefront of public and legal discourse dense social and ethical dilemmas that we have hardly begun to map and understand. In the near past, general community norms helped guide a clear sense of ethical boundaries with respect to privacy. One does not peek into the window of a house even if it is left open. One does not hire a private detective to investigate a casual date or the social life of a prospective employee. Yet with technological innovation rapidly driving new models for business and inviting new types of personal socialization, we often have nothing more than a fleeting intuition as to what is right or wrong. Our intuition may suggest that it is responsible to investigate the driving record of the nanny who drives our child to school, since such tools are now readily available. But is it also acceptable to seek out the records of other parents in our child’s car pool or of a date who picks us up by car? Alas, intuitions and perceptions of “creepiness” are highly subjective and difficult to generalize as social norms are being strained by new technologies and capabilities. And businesses that seek to create revenue opportunities by leveraging newly available data sources face huge challenges trying to operationalize such subjective notions into coherent business and policy strategies. This article presents a set of social and legal considerations to help individuals, engineers, businesses and policymakers navigate a world of new technologies and evolving social norms. These considerations revolve around concepts that we have explored in prior work, including enhanced transparency; accessibility to information in usable format; and the elusive principle of context.

The Black Box Society: The Secret Algorithms That Control Money and Information

Abstract: Every day, corporations are connecting the dots about our personal behaviorsilently scrutinizing clues left behind by our work habits and Internet use. The data compiled and portraits created are incredibly detailed, to the point of being invasive. But who connects the dots about what firms are doing with this information? The Black Box Society argues that we all need to be able to do soand to set limits on how big data affects our lives. Hidden algorithms can make (or ruin) reputations, decide the destiny of entrepreneurs, or even devastate an entire economy. Shrouded in secrecy and complexity, decisions at major Silicon Valley and Wall Street firms were long assumed to be neutral and technical. But leaks, whistleblowers, and legal disputes have shed new light on automated judgment. Self-serving and reckless behavior is surprisingly common, and easy to hide in code protected by legal and real secrecy. Even after billions of dollars of fines have been levied, underfunded regulators may have only scratched the surface of this troubling behavior. Frank Pasquale exposes how powerful interests abuse secrecy for profit and explains ways to rein them in. Demanding transparency is only the first step. An intelligible society would assure that key decisions of its most important firms are fair, nondiscriminatory, and open to criticism. Silicon Valley and Wall Street need to accept as much accountability as they impose on others.

Current index to legal periodicals

Abstract: American Bankruptcy Institute Law Review 17 Am. Bankr. Inst. L. Rev., No. 1, Spring, 2009. Boston College Law Review 50 B.C. L. Rev., No. 3, May, 2009. Boston University Public Interest Law Journal 18 B.U. Pub. Int. L.J., No. 2, Spring, 2009. Cardozo Journal of Conflict Resolution 10 Cardozo J. Conflict Resol., No. 2, Spring, 2009. Cardozo Public Law, Policy, & Ethics Journal 7 Cardozo Pub. L. Pol’y & Ethics J., No. 3, Summer, 2009. Chicago Journal of International Law 10 Chi. J. Int’l L., No. 1, Summer, 2009. Colorado Journal of International Environmental Law and Policy 20 Colo. J. Int’l Envtl. L. & Pol’y, No. 2, Winter, 2009. Columbia Journal of Law & the Arts 32 Colum. J.L. & Arts, No. 3, Spring, 2009. Connecticut Public Interest Law Journal 8 Conn. Pub. Int. L.J., No. 2, Spring-Summer, 2009. Cornell Journal of Law and Public Policy 18 Cornell J.L. & Pub. Pol’y, No. 1, Fall, 2008. Cornell Law Review 94 Cornell L. Rev., No. 5, July, 2009. Creighton Law Review 42 Creighton L. Rev., No. 3, April, 2009. Criminal Law Forum 20 Crim. L. Forum, Nos. 2-3, Pp. 173-394, 2009. Delaware Journal of Corporate Law 34 Del. J. Corp. L., No. 2, Pp. 433-754, 2009. Environmental Law Reporter News & Analysis 39 Envtl. L. Rep. News & Analysis, No. 7, July, 2009. European Journal of International Law 20 Eur. J. Int’l L., No. 2, April, 2009. Family Law Quarterly 43 Fam. L.Q., No. 1, Spring, 2009. Georgetown Journal of International Law 40 Geo. J. Int’l L., No. 3, Spring, 2009. Georgetown Journal of Legal Ethics 22 Geo. J. Legal Ethics, No. 2, Spring, 2009. Golden Gate University Law Review 39 Golden Gate U. L. Rev., No. 2, Winter, 2009. Harvard Environmental Law Review 33 Harv. Envtl. L. Rev., No. 2, Pp. 297-608, 2009. International Review of Law and Economics 29 Int’l Rev. L. & Econ., No. 1, March, 2009. Journal of Environmental Law and Litigation 24 J. Envtl. L. & Litig., No. 1, Pp. 1-201, 2009. Journal of Legislation 34 J. Legis., No. 1, Pp. 1-98, 2008. Journal of Technology Law & Policy 14 J. Tech. L. & Pol’y, No. 1, June, 2009. Labor Lawyer 24 Lab. Law., No. 3, Winter/Spring, 2009. Michigan Journal of International Law 30 Mich. J. Int’l L., No. 3, Spring, 2009. New Criminal Law Review 12 New Crim. L. Rev., No. 2, Spring, 2009. Northern Kentucky Law Review 36 N. Ky. L. Rev., No. 4, Pp. 445-654, 2009. Ohio Northern University Law Review 35 Ohio N.U. L. Rev., No. 2, Pp. 445-886, 2009. Pace Law Review 29 Pace L. Rev., No. 3, Spring, 2009. Quinnipiac Health Law Journal 12 Quinnipiac Health L.J., No. 2, Pp. 209-332, 2008-2009. Real Property, Trust and Estate Law Journal 44 Real Prop. Tr. & Est. L.J., No. 1, Spring, 2009. Rutgers Race and the Law Review 10 Rutgers Race & L. Rev., No. 2, Pp. 441-629, 2009. San Diego Law Review 46 San Diego L. Rev., No. 2, Spring, 2009. Seton Hall Law Review 39 Seton Hall L. Rev., No. 3, Pp. 725-1102, 2009. Southern California Interdisciplinary Law Journal 18 S. Cal. Interdisc. L.J., No. 3, Spring, 2009. Stanford Environmental Law Journal 28 Stan. Envtl. L.J., No. 3, July, 2009. Tulsa Law Review 44 Tulsa L. Rev., No. 2, Winter, 2008. UMKC Law Review 77 UMKC L. Rev., No. 4, Summer, 2009. Washburn Law Journal 48 Washburn L.J., No. 3, Spring, 2009. Washington University Global Studies Law Review 8 Wash. U. Global Stud. L. Rev., No. 3, Pp.451-617, 2009. Washington University Journal of Law & Policy 29 Wash. U. J.L. & Pol’y, Pp. 1-401, 2009. Washington University Law Review 86 Wash. U. L. Rev., No. 6, Pp. 1273-1521, 2009. William Mitchell Law Review 35 Wm. Mitchell L. Rev., No. 4, Pp. 1235-1609, 2009. Yale Journal of International Law 34 Yale J. Int’l L., No. 2, Summer, 2009. Yale Journal on Regulation 26 Yale J. on Reg., No. 2, Summer, 2009.

The ethics of algorithms: Mapping the debate:

Abstract: In information societies, operations, decisions and choices previously left to humans are increasingly delegated to algorithms, which may advise, if not decide, about how data should be interpreted and what actions should be taken as a result. More and more often, algorithms mediate social processes, business transactions, governmental decisions, and how we perceive, understand, and interact among ourselves and with the environment. Gaps between the design and operation of algorithms and our understanding of their ethical implications can have severe consequences affecting individuals as well as groups and whole societies. This paper makes three contributions to clarify the ethical importance of algorithmic mediation. It provides a prescriptive map to organise the debate. It reviews the current discussion of ethical aspects of algorithms. And it assesses the available literature in order to identify areas requiring further work to develop the ethics of algorithms.

Applications of big data to smart cities

Abstract: Many governments are considering adopting the smart city concept in their cities and implementing big data applications that support smart city components to reach the required level of sustainability and improve the living standards. Smart cities utilize multiple technologies to improve the performance of health, transportation, energy, education, and water services leading to higher levels of comfort of their citizens. This involves reducing costs and resource consumption in addition to more effectively and actively engaging with their citizens. One of the recent technologies that has a huge potential to enhance smart city services is big data analytics. As digitization has become an integral part of everyday life, data collection has resulted in the accumulation of huge amounts of data that can be used in various beneficial application domains. Effective analysis and utilization of big data is a key factor for success in many business and service domains, including the smart city domain. This paper reviews the applications of big data to support smart cities. It discusses and compares different definitions of the smart city and big data and explores the opportunities, challenges and benefits of incorporating big data applications for smart cities. In addition it attempts to identify the requirements that support the implementation of big data applications for smart city services. The review reveals that several opportunities are available for utilizing big data in smart cities; however, there are still many issues and challenges to be addressed to achieve better utilization of this technology.

Big Data Analytics in Intelligent Transportation Systems: A Survey

Abstract: Big data is becoming a research focus in intelligent transportation systems (ITS), which can be seen in many projects around the world. Intelligent transportation systems will produce a large amount of data. The produced big data will have profound impacts on the design and application of intelligent transportation systems, which makes ITS safer, more efficient, and profitable. Studying big data analytics in ITS is a flourishing field. This paper first reviews the history and characteristics of big data and intelligent transportation systems. The framework of conducting big data analytics in ITS is discussed next, where the data source and collection methods, data analytics methods and platforms, and big data analytics application categories are summarized. Several case studies of big data analytics applications in intelligent transportation systems, including road traffic accidents analysis, road traffic flow prediction, public transportation service plan, personal travel route plan, rail transportation management and control, and assets maintenance are introduced. Finally, this paper discusses some open challenges of using big data analytics in ITS.