Big Data

The Future of Privacy: More Data and More Choices

As I wrapped up my time at the Future of Privacy Forum, I prepared the following essay in advance of participating on a plenary discussion on the “future of privacy” at the Privacy & Access 20/20 conference in Vancouver on November 13, 2015 — my final outing in think tankery. 

Alan Westin famously described privacy as the ability of individuals “to determine for themselves when, how, and to what extent information about them is communicated to others.” Today, the challenge of controlling let alone managing our information has strained this definition of privacy to the breaking point. As one former European consumer protection commissioner put it, personal information is not just “the new oil of the Internet” but is also “the new currency of the digital world.” Information, much of it personal and much of it sensitive, is now everywhere, and anyone’s individual ability to control it is limited.

Early debates over consumer privacy focused on the role of cookies and other identifiers on web browsers. Technologies that feature unique identifiers have since expanded to include wearable devices, home thermostats, smart lighting, and every type of device in the Internet of Things. As a result, digital data trails will feed from a broad range of sensors and will paint a more detailed portrait about users than previously imagined. If privacy was once about controlling who knew your home address and what you might be doing inside, our understanding of the word requires revision in a world where every device has a digital address and ceaselessly broadcasts information.

The complexity of our digital world makes a huge challenge out of explaining all of this data collection and sharing. Privacy policies must either be high level and generic or technical and detailed, each option proves of limited value to the average consumer. Many connected devices have little capacity to communicate anything to consumers or passersby. And without meaningful insight, it makes sense to argue that our activities are now subject to the determinations of a giant digital black box. We see privacy conversations increasingly shift to discussions about fairness, equity, power imbalances, and discrimination.

No one can put the data genie back in a bottle. No one would want to. At a recent convening of privacy advocates, folks discussed the social impact of being surrounded by an endless array of “always on” devices, yet no one was willing to silence their smartphones for even an hour. It has become difficult, if not impossible, to opt out of our digital world, so the challenge moving forward is how do we reconcile reality with Westin’s understanding of privacy.

Yes, consumers may grow more comfortable with our increasingly transparent society over time, but survey after survey suggest that the vast majority of consumers feel powerless when it comes to controlling their personal information. Moreover, they want to do more to protect their privacy. This dynamic must be viewed as an opportunity. Rather than dour information management, we need better ways to express our desire for privacy. It is true that “privacy management” and “user empowerment” have been at the heart of efforts to improve privacy for years. Many companies already offer consumers an array of helpful controls, but one would be hard-pressed to convince the average consumer of this. The proliferation of opt-outs and plug-ins has done little to actually provide consumers with any feeling of control.

The problem is few of these tools actually help individuals engage with their information in a practical, transparent, or easy way. The notion of privacy as clinging to control of our information against faceless entities leaves consumers feeling powerless and frustrated. Privacy needs some rebranding. Privacy must be “appified” and made more engaging. There is a business model to be made in finding a way to marry privacy and control in an experience that is simple and functional. Start-ups are working to answer that challenge, and the rise of ephemeral messaging apps are, if not perfect implementations, a sure sign that consumers want privacy, if they can get it easily. For Westin’s view of privacy to have a future, we need to do a better job of embracing creative, outside-the-box ways to get consumers thinking about and engaging with how their data is being used, secured, and ultimately kept private.

Plunging Into the Black Box Society

Frank Pasquale’s The Black Box Society has been steadily moving up my reading list since it came out, but after Monday’s morning-long workshop on the topic of impenetrable algorithms, the book looks to be this weekend’s reading project. Professor Pasquale has been making the rounds for a while now, but when his presentation was combined by devastating real world examples of how opaque credit scores are harming consumers and regulators that were ill-equipped to address these challenges, U.S. PIRG Education Fund and the Center for Digital Democracy were largely successful in putting the algorithmic fear of God into me.

A few takeaways: first, my professional interest in privacy only occasionally intersects with credit reporting and the proliferation of credit scores, so it was alarming to learn that 25% of consumers have serious errors in their credit reports, errors large enough to impact their credit ratings. (PIRG famously concluded in 2004 that 79% of credit reports have significant errors.)

That’s appalling, particular as credit scores are increasingly essential, as economic justice advocate Alexis Goldstein put it, “to avail yourself of basic opportunity.” Pasquale described the situation as a data collection architecture that is “defective by design.” Comparing the situation to malfunctioning toasters, he noted that basic consumer protection laws (and tort liability) would functionally prohibit toasters with a 20% chance of blowing up on toast-delivery, but we’ve become far more cavalier when it comes to data-based products. More problematic is the byzantine procedures for contesting credit scores and resolving errors.

Or even realizing your report has errors. I have taken to using up one of my free, annual credit reports every three months with a different major credit reporting bureau, and while I think this procedure makes me feel like a responsible credit risk, I’m not sure what good I’m doing. It also strikes me as disheartening that the credit bureaus have turned around and made “free” credit reports into both a business segment and something of a joke — who can forget the FreeCreditReport.com “band”?

Second, the Fair Credit Reporting Act, the first “big data” law, came out of the event looking utterly broken. At one point, advocates were describing how individuals in New York City had lost out on job opportunities due to bad or missing credit reports — and had frequently never received adverse action notices as required by FCRA. Peggy Twohig from the Consumer Financial Protection Bureau then discussed how her agency expected most consumer reporting agencies to have compliance programs, with basic training and monitoring, and quickly found many lacked adequate oversight or capacity to track consumer complaints.

And this is the law regulators frequently point to as strongly protective of consumers? Maybe there’s some combination of spotty enforcement, lack of understanding, or data run amok that is to blame for the problems discussed, but the FCRA is a forty-five year-old law. I’m not sure ignorance and unfamiliarity are adequate explanations.

Jessica Rich, the Director of the FTC’s Bureau of Consumer Protection, conceded that there were “significant gaps” in existing law, and moreover, that in some respects consumers have limited ability to control information about them. This wasn’t news to me, but no one seemed to have any realistic notion for how to resolve this problem. There were a few ideas bandied back-and-forth, including an interesting exchange about competitive self-regulation, but Pasquale’s larger argument seemed to be that many of these proposals were band-aids on a much larger problem.

The opacity of big data, he argued, allows firms to “magically arbitrage…or rather mathematically arbitrage around all the laws.” He lamented “big data boosters” who believe data will be able to predict everything. If that’s the case, he argued, it is no longer possible to sincerely support sectoral data privacy regulation where financial data is somehow separate from health data, from educational data, from consumer data. “If big data works the way they claim it works, that calls for a rethink of regulation.” Or a black box over our heads?

Hate the Consumer Privacy Bill of Rights, but Love the Privacy Review Boards

Considering the criticism on all sides, it’s not a bold prediction to suggest the White House’s Consumer Privacy Bill of Rights is unlikely to go far in the current Congress. Yet while actual legislation may not be the cards, the ideas raised by the proposed bill will impact the privacy debate. One of the bill’s biggest ideas is the creation of a new governance institution, the Privacy Review Board.

The bill envisions that Privacy Review Boards will provide a safety valve for innovative uses of information that strain existing privacy protections but could provide big benefits. In particular, when notice and choice are impractical and data analysis would be “not reasonable in light of context,” Privacy Review Boards could still permit data uses when “the likely benefits of the analysis outweigh the likely privacy risks.” This approach provides a middle-ground between calls for permissionless innovation, on one hand, and blanket prohibitions on innovative uses of information on the other.

Instead, Privacy Review Boards embrace the idea that ongoing review processes, whether external or internal, are important and are a better way to address amorphous benefits and privacy risks. Whatever they ultimately look like, these boards can begin the challenging task of specifically confronting the ethical qualms being raised by the benefits of “big data” and the Internet of Things.

This isn’t a novel idea. After all, the creation of formal review panels was one of the primary responses to ethical concerns with biomedical research. Institutional review boards, or IRBs, have now existed as a fundamental part of the human research approval process for decades. IRBs are not without their flaws. They can become overburdened and bureaucratic, and the larger ethical questions can be replaced by a rigid process of checking-off boxes and filling out paperwork. Yet IRBs have become an important mechanism by which society has come to trust researchers.

At their foundation, IRBs reflect an effort to infuse research with several overarching ethical principles identified in the Belmont Report, which serves as a foundational document in ethical research. The report’s principles of respect for persons, beneficence, and justice embody the ideas that researchers (1) should respect individual autonomy, (2) maximize benefits to the research project while minimizing risks to research subjects, and (3) ensure that costs and benefits of research are distributed fairly and equitably.

Formalizing a process of considering these principles, warts and all, went a long way toward alleviating fears that medical researchers lacked rules. Privacy Review Boards could do the same today for consumer data in the digital space. Consumers feel like they lack control over their own information, and they want reassurances that their personal data is only being used in ways that ultimately benefit them. Moreover, calls to develop these sorts of mechanisms in the consumer space are also not new. In response to privacy headaches, companies like Facebook and Google have already instituted review panels that are designed to reflect different viewpoints and encourage careful consideration.

Establishing the exact requirements for Privacy Review Boards will demand flexibility. The White House’s proposal offers a litany of different factors to consider. Specifically, Privacy Review Boards will need to have a degree of independence and also possess subject-matter expertise. They will need to take the sizes, experiences, and resources of a given company into account. Perhaps most challenging, Privacy Review Boards will to balance transparency and confidentiality. Controversially, the proposed bill places the Federal Trade Commission in the role of arbiter of the board’s validity. While it would be interested to imagine how the FTC could approach such a task, the larger project of having more ethical conversations about innovative data use is worth pursuing, and perhaps the principles put forward in the Belmont Report can provide a good foundation once more.

The principles in the Belmont Report already reflect ideas that exist in debates surrounding privacy. For example, the notion of respect for persons echoes privacy law’s emphasis on fair notice and informed choice. Beneficence stresses the need to maximize benefits and minimize harms, much like existing documentation on the FTC’s test for unfair business practices, and justice raises questions about the equity of data use and considerations about unfair or illegal disparate impacts. If the Consumer Privacy Bill of Rights accomplishes nothing else, it will have reaffirmed the importance of a considered review process. Privacy Review Boards might not have all the answers – but they are in a position to monitor data uses for problems, promote trust, and ultimately, better protect privacy.

Big Data: Catalyst for a Privacy Conversation

Big Data: Catalyst for a Privacy Conversation

This week, the Indiana Law Review released my short article on privacy and big data that I prepared after the journal’s spring symposium. Law and policy appear on the verge of redefining how they understand privacy, and data collectors and privacy advocates are trying to present a path forward. The article discusses the rise of big data and the role of privacy in both the Fourth Amendment and consumer contexts. It explores how the dominant conceptions of privacy as secrecy and as control are increasingly untenable, leading to calls to focus on data use or respect the context of collection. I quickly argue that the future of privacy will have to be built upon a foundation of trust—between individuals and the technologies that will be watching and listening. I was especially thrilled to see the article highlighted by The New York Times’ Technology Section Scuttlebot.

Big Data Conversations Need a Big Data Definition

As part of my day job, I recently recapped the Federal Trade Commission’s workshop on “Big Data” and discrimination. My two key takeaways were that regulators and the advocacy community wanted more “transparency” into how industry is using big data, particularly in positive ways, and second, that there was a pressing need for industry to take affirmative steps to implement governance systems and stronger “institutional review board”-type mechanisms to overcome the transparency hurdle the opacity of big data present.

But if I’m being candid, I think we really need to start narrowing our definitions of big data. Big data has become a term that gets attached to a wide-array of different technologies and tools that really ought to be addressed separately. We just don’t have a standard definition. The Berkeley School of Information recently asked forty different thought leaders what they thought of big data, and basically got forty different definitions. While there’s a common understanding of big data as more volume, more variety, and at greater velocity, I’m not sure how any of these terms is a foundation to start talking about practices or rules, let alone ethics.

At the FTC’s workshop, big data was spoken in the context of machine learning and data mining, the activities of data brokers and scoring profiles, wearable technologies and the greater Internet of Things. No one ever set ground rules as to what “Big Data” meant as a tool for inclusion or exclusion. At one point, a member of the civil rights community was focused on big data largely as the volume of communications being produced by social media at the same time as another panelist was discussing consumer loyalty cards. Maybe there’s some overlap, but the risks and rewards can be very different.

Playing Cupid: All’s Fair in Love in the Age of Big Data?

After a three year dry spell, OkCupid’s fascinating OkTrends blog roared to life on Monday with a post by Christian Rudder, cofounder of the dating site. Rudder boldly declared that his matchmaking website “experiment[s] on human beings.” His comments are likely to reignite the controversy surrounding A/B testing on users in the wake of Facebook’s “emotional manipulation” study. This seems to be Rudder’s intention, writing that “if you use the Internet, you’re the subject of hundreds of experiments at any given time, on every site. That’s how websites work.”

Rudder’s announcement detailed a number of the fascinating ways that OkCupid “plays” with its user’s information. From removing text and photos from people’s profiles to duping mismatches into thinking they’re excellent matches for one another, OkCupid has tried a lot of different methods to help users find love. Curiously, my gut reaction to this news was that it was much less problematic that the similar sorts of tests being run by Facebook – and basically everyone involved in the Internet ecosystem.

After all, OkCupid is quite literally playing Cupid. Playing God. There’s an expectation that there’s some magic to romance, even if it’s been reduced to numbers. Plus, there’s the hope these experiments are designed to better connect users with eligible dates, while most website experiments are to improve user engagement with the service itself. Perhaps all is fair in love, even if it requires users to divulge some of the most sensitive personal information imaginable.

Whatever the ultimate value of OkCupid’s, or Facebook’s, or really any organization’s user experiments, critics are quick to suggest these studies reveal how much control users have ceded over their personal information. But I think the real issue is broader than any concern over “individual control.” Instead, these studies beg the question of how much technology – fueled by our own data – can shape and mediate interpersonal interactions.

OkCupid’s news immediately brought to mind a talk by Patrick Tucker just last week at the Center for Democracy & Technology’s first “Always On” forum. Tucker, editor at The Futurist magazine and author of The Naked Future, provided a firestarter talk that detailed some of the potential of big data to reshape how we live and interact with each other. At a similar TEDx talk last year, he posited that all of this technology and all of this data can be used to give individuals an unprecedented amount of power. He began by discussing prevailing concerns about targeted marketing: “We’re all going to be faced with much more aggressive and effective mobile advertising,” he conceded, ” . . . but what if you answered a push notification on your phone that you have a 60% probability of regretting a purchase you’re about to make – this is the antidote to advertising!”

But he quickly moved beyond this debate. He proposed a hypothetical where individuals could be notified (by push notification, of course) that they were about to alienate their spouse. Data can be used not just to set up dates, but to manage marriages! Improve friendships! For an introvert such as myself, there’s a lot of appeal to these sorts of applications, but I also wonder when all of this information becomes a crutch. As OkCupid explains, when its service tells people they’re a good match, they act as if they are “[e]ven when they should be wrong for each other.”

Occasionally our reliance on technology crosses not just some illusory creepy line, but fundamentally changes our behavior. Last year, at IAPP’s Navigate conference, I met Lauren McCarthy, an artist researcher in residence at NYU, who discussed how she used technology to augment her ability to communicate. For example, she demoed a “happy hat” that would monitor the muscles in your face and provide a jolt of physical pain if the wearer stopped smiling. She also explained using technology and crowd-sourcing to make her way through dates.  She would secretly video tape her interactions with men in order to provide a livestream for viewers to give her real time feedback on the situation.  “He likes you.” “Lean in.” “Act more aloof,” she’d be told. As part of the experiment, she’d follow whatever directions were being beamed to her.

I asked her later whether she’d ever faced the situation of feeling one thing, e.g., actually liking a guy, and being directed to “go home” by her string-pullers, and she conceded she had. “I wanted to stay true to the experiment,” she said. On the surface, that struck me as ridiculous, but as I think on her presentation now, I wonder if she was forecasting our social future.

Echoing OkCupid’s results, McCarthy also discussed a Magic 8 ball device that a dating pair could figuratively shake to direct their conversation. Smile. Compliment. Laugh, etc. According to McCarthy, people had reported that the device had actually “freed” their conversation, and helped liberate them from the pro forma routines of dating.

Obviously, we are free to ignore the advice of Magic 8 balls, just as we can ignore push notifications on our phones. But if those push notifications work? If the algorithmic special sauce works? If data provides “better dates” and less alienated wives, why wouldn’t we use it? Why wouldn’t we harness it all the time? From one perspective, this is the ultimate form of individual control, where our devices can help us to tailor our behavior to better accommodate the rest of the world. Where then does the data end and the humanity begin? Privacy, as a value system, pushes up against this question, not because it’s about user control but because part of the value of privacy is in the right to fail, to be able to make mistakes, and to have secret spaces where push notifications cannot intrude. What that spaces looks like, however, when OkCupid is pulling our heartstrings.

Developing Consensus on the Ethics of Data Use

Information is power, as the saying goes, and big data promises the power to make better decisions across industry, government, and everyday life. Data analytics offers an assortment of new tools to harness data in exciting ways, but society has been slow to engage in a meaningful analysis of the social value of all this data. The result has been something of a policy paralysis when it comes to building consensus around certain uses of information.

Advocates noted this dilemma several years ago during the early stages of the effort to develop a Do Not Track (DNT) protocol at the World Wide Web Consortium. DNT was first proposed seven years ago as a technical mechanism to give users control over whether they were being tracked online, but the protocol remains a work in progress. The real issue lurking behind the DNT fracas was not any sort of technical challenge, however, but rather the fact that the ultimate value of online behavioral advertising remains an open question. Industry touts the economic and practical benefits of an ad-supported Internet, while privacy advocates maintain that targeted advertising is somehow unfair. Without any efforts to bridge that gap, consensus has been difficult to reach.

As we are now witnessing in conversations ranging from student data to consumer financial protection, the DNT debate was but a microcosm of larger questions surrounding the ethics of data use. Many of these challenges are not new, but the advent of big data has made the need for consensus ever more pressing.

For example, differential pricing schemes – or price discrimination – have increasingly become a hot-button issue. But charging one consumer a different price than another for the same good is not a new concept; in fact, it happens every day. The Wall Street Journal recently explored how airlines are the “world’s best price discriminators,” noting that what an airline passenger pays is tied to the type of people they’re flying with. As a result, it currently costs more for U.S. travelers to fly to Europe than vice versa because the U.S. has a stronger economy and quite literally can afford higher prices. Businesses are in business, after all, to make money, and at some level, differential pricing makes economic sense.

However, there remains a basic concern about the unfairness of these practices. This has been amplified by perceived changes in the nature of how price discrimination works. The recent White House “Big Data Report” recognized that while there are perfectly legitimate reasons to offers different prices for the same products, the capacity for big data “to segment the population and to stratify consumer experiences so seamlessly as to be almost undetectable demands greater review.” Customers have long been sorted into different categories and groupings. Think urban or rural, young or old. But big data has made it markedly easier to identify those characteristics that can be used to ensure every individual customer is charged based on their exact willingness to pay.

The Federal Trade Commission has taken notice of this shift, and begun to start a much-needed conversation about the ultimate value of these practices. At a recent discussion on consumer scoring, Rachel Thomas from the Direct Marketing Association suggested that companies have always tried to predict customer wants and desires. What’s truly new about data analytics, she argued, is that it offers the tools to actually get predictions right and to provide “an offer that is of interest to you, as opposed to the person next to you.” While some would argue this is a good example of market efficiency, others worry that data analytics can be used to exploit or manipulate certain classes of consumers. Without a good deal more public education and transparency on the part of decision-makers, we face a future where algorithms will drive not just predictions but decisions that will exacerbate socio-economic disparities.

The challenge moving forward is two-fold. Many of the more abstract harms allegedly produced by big data are fuzzy at best – filter bubbles, price discrimination, and amorphous threats to democracy are hardly traditional privacy harms. Moreover, few entities are engaging in the sort of rigorous analysis necessary to determine whether or not a given data use will make these things come to pass.

According to the White House, technological developments necessitate a shift in privacy thinking and practice toward responsible uses of data rather than its mere collection and analysis. While privacy advocates have expressed skepticism of use-based approaches to privacy, increased transparency and accountability mechanisms have been approached as a way to further augment privacy protections. Developing broad-based consensus around data use may be more important.

Consensus does not mean unanimity, but it does require a conversation that considers the interests of all stakeholders. One proposal that could help drive consensus are the development of internal review boards or other multi-stakeholder oversight mechanisms. Looking to the long-standing work of institutional review boards, or IRBs, in the field of human subject testing, Ryan Calo suggested that a similar structure could be used as a tool to infuse ethical considerations into consumer data analytics. IRBs, of course, engage in a holistic analysis of the risks and benefits that could result from any human testing project. They are also made up of different stakeholders, encompassing a wide-variety of diverse backgrounds and professional expertise. These boards also come to a decision before a project can be pursued.

Increasingly, technology is leaving policy behind. While that can both promote innovation and ultimately benefit society, it makes the need for consensus about the ethics at stake all the more important.

Big Data Privacy Bingo

Big Data Privacy Bingo

With the White House’s Big Data and Privacy Review anticipated any day now, I figured it was long past time to put together a quick #bigdataprivacy bingo card. If you go to enough privacy (or big data) events and workshops, you’ll quickly realize how many of the same buzzwords and anecdotes get cited over and over . . . and over again. In the battle between privacy and innovation, bingo may be the only thing that wins.

Truthout Publishes My Thoughts on Big Data’s Image Problem

Happy to report that Truthout today published my quick op-ed entitled “Big Data’s Big Image Problem.” Not only does this piece expand on comments the Future of Privacy Forum submitted as part of the White House’s Big Data Review, but it also riffs on my favorite part of the latest Marvel movie, Captain America: The Winter Soldier.  As a privacy wonk, I took great pleasure in discovering that ::minor spoilers:: Captain America’s chief villain was actually “The Algorithm.”  When Captain America doesn’t like you, you know you’ve got an image problem, and frankly, big data has an image problem.

White House/MIT Big Data Privacy Workshop Recap

Speaking for everyone snowed-in in DC, White House Counselor John Podesta remarked that “big snow trumped big data,” while on the phone to open the first of the Obama Administration’s three big data and privacy workshops.  This first workshop, which I was eager to attend (if only to continue my streak of annual appearances in Beantown), focused on advancing the “start of the art” in technology and practice.  For a mere lawyer such as myself, I anticipated a lot of highly technical jargon, and in that regard I was not disappointed. // Full recap on the Future of Privacy Forum Blog.

Technology Policy Institute Tackles Big Data

A recent paper by the Technology Policy Institute takes a pro-business look at the Big Data phenomenon, finding “no evidence” that Big Data is creating any sort of privacy harms.  As I hope to lay out, I didn’t agree with several of the report’s findings, but I found the paper especially interesting as it critiques my essay from September’s “Big Data and Privacy” conference.  According to TPI, my “inflammatory” suggestion that ubiquitous data collection may harm the poor was presented “without evidence.” Let me first say that I’m deeply honored to have my writing critiqued; for better or worse, I am happy to have my thoughts somehow contribute to a policy conversation.  That said, while some free market voices applauded the report as a thoughtful first step at doing a a Big Data cost-benefit analysis, I found the report to be one-sided to its detriment.

As ever in the world of technology and law, definitions matter, and neither myself nor TPI can adequately define what “Big Data” even is.  Instead, TPI suggests that Big Data phenomenon describes the fact that data is “now available in real time, at larger scale, with less structure, and on different types of variables than previously.”  If I wanted to be inflammatory, I would suggest this means that personal data is being collected and iterated upon pervasively and continuously.  The paper then does a good job of exploring some of the unexpected benefits of this situation.  It points to the commonly-lauded Google Flu Trends as the posterchild for Big Data’s benefits, but neglects to mention the infamous example where Target was able to uncover a teenage customer was pregnant before her family.

At that point, the paper looks at several common privacy concerns surrounding Big Data and attempts to debunk them. Read More…

Recapping EPIC’s Failing the Grade Educational Privacy Event

The arrival of new technologies in the field of education, from connected devices, student longitudinal data systems, and massive open online courses (MOOCs) present both opportunities and potential privacy risks for students and educators.  As part of my work at the Future of Privacy Forum, I have started surveying the issue of privacy in education, and early, anecdotal conversations suggest a pressing need for more education and awareness among all stakeholders.  With that in mind, I was pleased to see the Electronic Privacy Information Center (EPIC) host an informative discussion on education records and student privacy.

The focus of the discussion was on the growing “datafication” of student’s personal information.  Sen. Edward Markey (D-Mass), who has been active in the field of children’s privacy, opened the event with an introduction to the topic area.  In addition to discussing his Do Not Track Kids legislation, which would extend COPPA-type protections to 13, 14, and 15 year-olds, the Senator highlighted his new student privacy legislation.  The goals of the legislation were explained as follows:

  1. Student data should never be available for commercial purposes (focus on advertising);
  2. Parents should have access and rectification rights to data held by private companies, similar to what is afforded for records held by schools;
  3. Safeguards should be put in place to ensure that there are real protections for student records held by third parties; and
  4. Private companies must delete information that they no longer need. Student records should not be held permanently by companies, only by parents.

The panel itself featured Marc Rotenberg and Khaliah Barnes of EPIC; Kathleen Styles, Chief Privacy Officer at the Department of Education (DOE); Joel Reidenberg of Fordham Law School; Deborah Peel of Patient Privacy Rights; and Pablo Molina, Chief Information Officer at Southern Connecticut State University.

Read More…

Whose Hypothetical Horribles?

Released last fall, Rick Smolan and Jennifer Erwitt’s The Human Face of Big Data is a gorgeous, coffee table book that details page after page of projects that are using Big Data to reshape human society.  In a later interview, Smolan suggested that Big Data was “akin to the planet suddenly developing a nervous system” with “the potential to have a bigger impact on civilization than the Internet.” A bold claim if ever there was one, but the advent of Big Data begs the question: what sort of ramifications will this new data nervous system have on society?

Since I began reading about Big Data in earnest last year, I’ve noticed that much of the discussion seems to be focused at the extremes, hyping either the tremendous benefits and terrific fears of Big Data.

Proponents tend to look at data analytics with wide-eyed optimism.  In their recent book, Big Data: A Revolution That Will Transform How We Live, Work, and Think, Viktor Mayer-Schoenberger and Ken Cukier suggest that Big Data will “extract new insights or create new form of value, in ways that change markets, organizations, the relationship between citizens and governments, and more.”

On the other side of the coin, scholars like Paul Ohm argue that “Big Data’s touted benefits are often less significant than claimed and less necessary than assumed.” It is very easy to see Big Data as a giant engine designed explicitly to discriminate, to track, to profile, and ultimately, to exclude.  Technologist Alistair Croll has declared Big Data to be the “civil rights issue” of our generation.

Adam Thierer, who puts his faith in the market to sort these issues out, has derisively suggested these worries are little more than boogeyman scenarios and hypothetical horribles, but I take his point that much of the worry surrounding Big Data is of a kind of abstract doom and gloom.  The discussion could benefit by actually describing what consumers–what individuals are facing on the ground.

For example, in my paper, I noticed two interesting stories in the span of a few weeks.  First, that noted Judge Alex Kozinski had declared that he would be willing to spend $2,400 a year in order to protect his privacy from marketers and miscreants.  Second, that individuals were data-mining themselves on Kickstarter to the tune of $2,700.  One was an established legal figure; the other a poor graduate student.  One could pay.  The other could only sell.

More of the Big Data discussion should center around how consumers are honestly being impacted.  Instead, we’re still talking about Fair Information Practice Principles with the strong conviction that a few tweaks here and there and a renewed dedication to some long-standing principles will “solve” the privacy challenge we face.  In the regulatory regime, there is much discussion about offering “meaningful” user choice, but as the “Do Not Track” process has demonstrated, no one really knows what that means.

I would love to pay for my privacy, but that’s a cost I’m not prepared to cover.  I’d love to make meaningful choices about my privacy, but I’m not sure what any of my choices will actually accomplish.  Perhaps Thierer has a point, that I’m worried about hypothetical horribles, but I’m not sure our planet’s new data nervous system has my best interests in mind.

Buying and Selling Privacy Essay Published by Stanford Law Review Online

My essay on how “Big Data” is transforming our notions of individual privacy in unequal ways has been published by the Stanford Law Review Online.  Here’s how they summed up my piece:

We are increasingly dependent upon technologies, which in turn need our personal information in order to function. This reciprocal relationship has made it incredibly difficult for individuals to make informed decisions about what to keep private. Perhaps more important, the privacy considerations at stake will not be the same for everyone: they will vary depending upon one’s socioeconomic status. It is essential for society and particularly policymakers to recognize the different burdens placed on individuals to protect their data.

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