Big Data

Data-Driven Regimes of Truth

~ L. M. Sacasas ~ 9 Comments

Below are excerpts from three items that came across my browser this past week. I thought it useful to juxtapose them here.

The first is Andrea Turpin’s review in The Hedgehog Review of Science, Democracy, and the American University: From the Civil War to the Cold War, a new book by Andrew Jewett about the role of science as a unifying principle in American politics and public policy.

“Jewett calls the champions of that forgotten understanding ‘scientific democrats.’ They first articulated their ideas in the late nineteenth century out of distress at the apparent impotence of culturally dominant Protestant Christianity to prevent growing divisions in American politics—most violently in the Civil War, then in the nation’s widening class fissure. Scientific democrats anticipated educating the public on the principles and attitudes of scientific practice, looking to succeed in fostering social consensus where a fissiparous Protestantism had failed. They hoped that widely cultivating the habit of seeking empirical truth outside oneself would produce both the information and the broader sympathies needed to structure a fairer society than one dominated by Gilded Age individualism.

Questions soon arose: What should be the role of scientific experts versus ordinary citizens in building the ideal society? Was it possible for either scientists or citizens to be truly disinterested when developing policies with implications for their own economic and social standing? Jewett skillfully teases out the subtleties of the resulting variety of approaches in order to ‘reveal many of the insights and blind spots that can result from a view of science as a cultural foundation for democratic politics.’”

The second piece, “When Fitbit is the Expert,” appeared in The Atlantic. In it, Kate Crawford discusses how data gathered by wearable devices can be used for and against its users in court.

“Self-tracking using a wearable device can be fascinating. It can drive you to exercise more, make you reflect on how much (or little) you sleep, and help you detect patterns in your mood over time. But something else is happening when you use a wearable device, something that is less immediately apparent: You are no longer the only source of data about yourself. The data you unconsciously produce by going about your day is being stored up over time by one or several entities. And now it could be used against you in court.”

[….]

“Ultimately, the Fitbit case may be just one step in a much bigger shift toward a data-driven regime of ‘truth.’ Prioritizing data—irregular, unreliable data—over human reporting, means putting power in the hands of an algorithm. These systems are imperfect—just as human judgments can be—and it will be increasingly important for people to be able to see behind the curtain rather than accept device data as irrefutable courtroom evidence. In the meantime, users should think of wearables as partial witnesses, ones that carry their own affordances and biases.”

The final excerpt comes from an interview with Mathias Döpfner in the Columbia Journalism Review. Döfner is the CEO of the largest publishing company in Europe and has been outspoken in his criticisms of American technology firms such as Google and Facebook.

“It’s interesting to see the difference between the US debate on data protection, data security, transparency and how this issue is handled in Europe. In the US, the perception is, ‘What’s the problem? If you have nothing to hide, you have nothing to fear. We can share everything with everybody, and being able to take advantage of data is great.’ In Europe it’s totally different. There is a huge concern about what institutions—commercial institutions and political institutions—can do with your data. The US representatives tend to say, ‘Those are the back-looking Europeans; they have an outdated view. The tech economy is based on data.’”

Döpfner goes out of his way to indicate that he is a regulatory minimalist and that he deeply admires American-style tech-entrepreneurship. But ….

“In Europe there is more sensitivity because of the history. The Europeans know that total transparency and total control of data leads to totalitarian societies. The Nazi system and the socialist system were based on total transparency. The Holocaust happened because the Nazis knew exactly who was a Jew, where a Jew was living, how and at what time they could get him; every Jew got a number as a tattoo on his arm before they were gassed in the concentration camps.”

Perhaps that’s a tad alarmist, I don’t know. The thing about alarmism is that only in hindsight can it be definitively identified.

Here’s the thread that united these pieces in my mind. Jewett’s book, assuming the reliability of Turpin’s review, is about an earlier attempt to find a new frame of reference for American political culture. Deliberative democracy works best when citizens share a moral framework from which their arguments and counter-arguments derive their meaning. Absent such a broadly shared moral framework, competing claims can never really be meaningfully argued for or against, they can only be asserted or denounced. What Jewett describes, it seems, is just the particular American case of a pattern that is characteristic of secular modernity writ large. The eclipse of traditional religious belief leads to a search for new sources of unity and moral authority.

For a variety of reasons, the project to ground American political culture in publicly accessible science did not succeed. (It appears, by the way, that Jewett’s book is an attempt to revive the effort.) It failed, in part, because it became apparent that science itself was not exactly value free, at least not as it was practice by actual human beings. Additionally, it seems to me, the success of the project assumed that all political problems, that is all problems that arise when human beings try to live together, were subject to scientific analysis and resolution. This strikes me as an unwarranted assumption.

In any case, it would seem that proponents of a certain strand Big Data ideology now want to offer Big Data as the framework that unifies society and resolves political and ethical issues related to public policy. This is part of what I read into Crawford’s suggestion that we are moving into “a data-driven regime of ‘truth.'” “Science says” replaced “God says”; and now “Science says” is being replaced by “Big Data says.”

To put it another way, Big Data offers to fill the cultural role that was vacated by religious belief. It was a role that, in their turn, Reason, Art, and Science have all tried to fill. In short, certain advocates of Big Data need to read Nietzsche’s Twilight of the Idols. Big Data may just be another God-term, an idol that needs to be sounded with a hammer and found hollow.

Finally, Döfner’s comments are just a reminder of the darker uses to which data can and has been put, particularly when thoughtfulness and judgement have been marginalized.

Thinking About Big Data

~ L. M. Sacasas ~ 3 Comments

I want to pass on to you three pieces on what has come to be known as Big Data, a diverse set of practices enabled by the power of modern computing to accumulate and process massive amounts of data. The first piece, “View from Nowhere,” is by Nathan Jurgenson. Jurgenson argues that the aspirations attached to Big Data, particularly in the realm of human affairs, amounts to a revival of Positivism:

“The rationalist fantasy that enough data can be collected with the ‘right’ methodology to provide an objective and disinterested picture of reality is an old and familiar one: positivism. This is the understanding that the social world can be known and explained from a value-neutral, transcendent view from nowhere in particular.”

Jurgenson goes on to challenge these positivist assumptions through a critical reading of OkCupid CEO Christian Rudder’s new book Dataclysm: Who We Are (When We Think No One’s Looking).

The second piece is an op-ed in the NY Times by Frank Pasquale, “The Dark Market for Personal Data.” Pasquale considers the risks to privacy associated with gathering and selling of personal information by companies equipped to mine and package such data. Pasquale concludes,

“We need regulation to help consumers recognize the perils of the new information landscape without being overwhelmed with data. The right to be notified about the use of one’s data and the right to challenge and correct errors is fundamental. Without these protections, we’ll continue to be judged by a big-data Star Chamber of unaccountable decision makers using questionable sources.”

Finally, here is a journal article, “Obscurity and Privacy,” by Evan Selinger and Woodrow Hartzog. Selinger and Hartzog offer obscurity as an explanatory concept to help clarify our thinking about the sorts of issues that usually get lumped together as matters of privacy. Privacy, however, may not be a sufficiently robust concept to meet the challenges posed by Big Data.

“Obscurity identifies some of the fundamental ways information can be obtained or kept out of reach, correctly interpreted or misunderstood. Appeals to obscurity can generate explanatory power, clarifying how advances in the sciences of data collection and analysis, innovation in domains related to information and communication technology, and changes to social norms can alter the privacy landscape and give rise to three core problems: 1) new breaches of etiquette, 2) new privacy interests, and 3) new privacy harms.”

In each of these areas, obscurity names the relative confidence individuals can have that the data trail they leave behind as a matter of course will not be readily accessible:

“When information is hard to understand, the only people who will grasp it are those with sufficient motivation to push past the layer of opacity protecting it. Sense-making processes of interpretation are required to understand what is communicated and, if applicable, whom the communications concerns. If the hermeneutic challenge is too steep, the person attempting to decipher the content can come to faulty conclusions, or grow frustrated and give up the detective work. In the latter case, effort becomes a deterrent, just like in instances where information is not readily available.”

Big Data practices have made it increasingly difficult to achieve this relative obscurity thus posing a novel set social and personal challenges. For example, the risks Pasquale identifies in his op-ed may be understood as risks that follow from a loss of obscurity. Read the whole piece for a better understanding of these challenges. In fact, be sure to read all three pieces. Jurgenson, Selinger, and Pasquale are among our most thoughtful guides in these matters.

Allow me to wrap this post up with a couple of additional observations. Returning to Jurgenson’s thesis about Big Data–that Big Data is a neo-Positivist ideology–I’m reminded that positivist sociology, or social physics, was premised on the assumption that the social realm operated in predictable law-like fashion, much as the natural world operated according to the Newtonian world picture. In other words, human action was, at root, rational and thus predictable. The early twentieth century profoundly challenged this confidence in human rationality. Think, for instance, of the carnage of the Great War and Freudianism. Suddenly, humanity seemed less rational and, consequently, the prospect of uncovering law-like principles of human society must have seemed far more implausible. Interestingly, this irrationality preserved our humanity, insofar as our humanity was understood to consist of an irreducible spontaneity, freedom, and unpredictability. In other words, so long as the Other against which our humanity was defined was the Machine.

If Big Data is neo-Positivist, and I think Jurgenson is certainly on to something with that characterization, it aims to transcend the earlier failure of Comteian Positivism. It acknowledges the irrationality of human behavior, but it construes it, paradoxically, as Predictable Irrationality. In other words, it suggests that we can know what we cannot understand. And this recalls Evgeny Morozov’s critical remarks in “Every Little Byte Counts,”

“The predictive models Tucker celebrates are good at telling us what could happen, but they cannot tell us why. As Tucker himself acknowledges, we can learn that some people are more prone to having flat tires and, by analyzing heaps of data, we can even identify who they are — which might be enough to prevent an accident — but the exact reasons defy us.

Such aversion to understanding causality has a political cost. To apply such logic to more consequential problems — health, education, crime — could bias us into thinking that our problems stem from our own poor choices. This is not very surprising, given that the self-tracking gadget in our hands can only nudge us to change our behavior, not reform society at large. But surely many of the problems that plague our health and educational systems stem from the failures of institutions, not just individuals.”

It also suggests that some of the anxieties associated with Big Data may not be unlike those occasioned by the earlier positivism–they are anxieties about our humanity. If we buy into the story Big Data tells about itself, then it threatens, finally, to make our actions scrutable and predictable, suggesting that we are not as free, independent, spontaneous, or unique as we might imagine ourselves to be.

The Political Perils of “Big Data”

~ L. M. Sacasas ~ 7 Comments

In “Every Little Byte Counts,” a recent review of two books on “advances in our ability to store, analyze and profit from vast amounts of data generated by our gadgets” (otherwise known as Big Data), Evgeny Morozov makes two observations to which I want to draw your attention. 

The first of these he makes with the help of the Italian philosopher, Giorgio Agamben. Here are Morozov’s first two paragraphs: 

In “On What We Can Not Do,” a short and pungent essay published a few years ago, the Italian philosopher Giorgio Agamben outlined two ways in which power operates today. There’s the conventional type that seeks to limit our potential for self-­development by restricting material resources and banning certain behaviors. But there’s also a subtler, more insidious type, which limits not what we can do but what we can not do. What’s at stake here is not so much our ability to do things but our capacity not to make use of that very ability.

While each of us can still choose not to be on Facebook, have a credit history or build a presence online, can we really afford not to do any of those things today? It was acceptable not to have a cellphone when most people didn’t have them; today, when almost everybody does and when our phone habits can even be used to assess whether we qualify for a loan, such acts of refusal border on the impossible.

This is a profoundly important observation, and it is hardly ever made. In his brief but insightful book, Nature and Altering It, ethicist Allen Verhey articulated a similar concern. Verhey discusses a series of myths that underlie our understanding of nature (earlier he cataloged 16 uses of the idea of “nature”). While discussing one of these myths, the myth of the project of liberal society, Verhey writes,

“Finally, however, the folly of the myth of liberal society is displayed in the pretense that ‘maximizing freedom’ is always morally innocent. ‘Maximizing freedom,’ however, can ironically increase our bondage. What is introduced as a way to increase our options can become socially enforced. The point can easily be illustrated with technology. New technologies are frequently introduced as ways to increase our options, as ways to maximize our freedom, but they can become socially enforced. The automobile was introduced as an option, as an alternative to the horse, but it is now socially enforced …. The technology that surrounds our dying was introduced to give doctors and patients options in the face of disease and death, but such ‘options’ have become socially enforced; at least one sometimes still hears, “We have no choice!” And the technology that may come to surround birth, including pre-natal diagnosis, for example, may come to be socially enforced. ‘What? You knew you were at risk for bearing a child with XYZ, and you did nothing about it? And now you expect help with this child?’ Now it is possible, of course, to claim that cars and CPR and pre-natal diagnosis are the path of progress, but then the argument has shifted from the celebration of options and the maximizing of freedom to something else, to the meaning of progress.”

The second point from Morozov’s review that I want to draw your attention to involves the political consequences of tools that harness the predictive power of Big Data, a power divorced from understanding:

“The predictive models Tucker celebrates are good at telling us what could happen, but they cannot tell us why. As Tucker himself acknowledges, we can learn that some people are more prone to having flat tires and, by analyzing heaps of data, we can even identify who they are — which might be enough to prevent an accident — but the exact reasons defy us.

Such aversion to understanding causality has a political cost. To apply such logic to more consequential problems — health, education, crime — could bias us into thinking that our problems stem from our own poor choices. This is not very surprising, given that the self-tracking gadget in our hands can only nudge us to change our behavior, not reform society at large. But surely many of the problems that plague our health and educational systems stem from the failures of institutions, not just individuals.”

Moreover, as Hannah Arendt put it in The Human Condition, politics is premised on the ability of human beings to “talk with and make sense to each other and to themselves.” Divorcing action from understanding jeopardizes the premise upon which democratic self-governance is founded, the possibility of deliberative judgment. Is it an exaggeration to speak of the prospective tyranny of the algorithm?

I’ll give Morozov the penultimate word:

“It may be that the first kind of power identified by Agamben is actually less pernicious, for, in barring us from doing certain things, it at least preserves, even nurtures, our capacity to resist. But as we lose our ability not to do — here Agamben is absolutely right — our capacity to resist goes away with it. Perhaps it’s easier to resist the power that bars us from using our smartphones than the one that bars us from not using them. Big Data does not a free society make, at least not without basic political judgment.”

I draw your attention to these concerns not because I have an adequate response to them, but because I am increasingly convinced that they are among the most pressing concerns we must grapple with in the years ahead.