Data Ethics 2: Electric Boogaloo

The advent of social media has brought with it a new kind of data, one that Lev Manovich thinks could bridge the gap between surface and depth that has historically limited scientists and anthropologists in the study of the human condition. Due to the sheer size of what we can now collect and analyze, now on such a scale that normal computers can not handle the load, a scientific study in today’s world could incorporate hundreds of millions of people, each with their own experiences, preferences, and desires.

But what is the “authenticity” of these extensive sets of data? Manovich poses the argument that our data is not a transparent window into our lives as some would think. His most extreme example is that of someone living in an oppressive state where thoughts and actions must be tailored to governmental preferences. Yet while many do not find themselves in this position, the constant burden of social anxiety and the desire to conform may act in place of Big Brother.

On the other hand, Alice Marwick moves from the benefits and potential detriments of this type of data in the scientific world to the darker, more deceptive world of grand-scale data collection and it’s ethical shortcomings. At the article’s time of publishing, The Guardian had very recently published a massive leak of NSA data and protocols creating a rabbit hole that is still getting deeper and deeper today. But, in the same light, Marwick writes about the many instances in which companies, primarily Target, have begun to use this type of data collecting to tailor advertisements towards their customer’s preferences; many times succeeding in being more creepy than helpful. So where do we draw the line between what is ethically correct and not when companies undergo many of the same types of collection and prediction without any of the responsibility of a government agency?

From an even more frightening standpoint, Marwick moves onto the topic of data brokers, companies that not only collect data from hundreds of millions of people each year but put it on the market, in many cases nonchalantly. Acxiom, her main example and the largest data broker in the business, has an untarnished record. Their competitor Experion has not had such good luck. On one occasion they sold personal data to an identity theft ring while on another they sold to a Vietnamese hacker. What is the ethicality, if any, in these forms of business when it comes to personal information?

 

By Judson, Griffen

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One thought on “Data Ethics 2: Electric Boogaloo

  1. Responders: Nile, Wes, Violet

    In your post, one question posed was related to the “authenticity” of big data sets. In the readings for Wednesday, the authors delved deeper into this question by illustrating the fallacy of believing that big data — by nature of simply being “big” — shows us anything truly authentic about our world. In the Boyde/Crawford article they point out that just because someone’s mobile phone data implies they spend more time with their colleagues than their spouse does not imply the colleagues are more important than the spouse. (671).

    They also refer to Leinweber, a researcher who used data mining techniques to demonstrate a “strong but spurious correlation between changes in the S&P 500 stock index and butter production in Bangladesh.” (668). Steven Salzberg showed how Google Flu, despite being formed from big data, was totally inaccurate and unhelpful because the data itself was inaccurate to begin with. “Like it or not,” he quips, “a big pile of dreck can only produce more dreck.” These examples serve to show how conclusions drawn out of big data do not necessarily line up with lived experience. It begs the question if “BIG” data are beneficial sources of information — and if it can be a beneficial source of information, when and how?

    The last question you posed was related to ethical practices when it comes big data. Corporations are buying, selling, swapping, mining, and collecting data about us — but more importantly, they are profiting off us. The reading for Friday, Immaterial Labour and Data Harvesting, questions the nature of our relationship with data behemoths like Facebook. A foundational concept from Marx is alienation, or when workers lose control of their own labor as well as control over their labor products. In industrial society, this exists as factory workers producing goods that they have no control of and that they do not own, since the principal means of production belong to the capitalist class. Shifting into a paradigm that involves Facebook, we are alienated data workers. We produce the commodifiable goods (data) but our control over those goods is tenuous at best and we are excluded entirely from the profit of commodity value.

    Your example had to do with ethical practices involving big corporations selling and buying data with other corporations, hacker groups, and other ethically dubious exchanges. These seem to exist on a horizontal relational plane. Ethical practice can also be applied to vertical relational planes — such as asking if it is ethical that users produce nearly all of the commodity value extracted from sites like Facebook but that those same users are excluded from the profit? How would getting paid Facebook dividends work with millions of people posting? “Youtube Partners” get shares of Youtube’s profit. Could something similar be applied to how data is produced and commodified in other spheres?

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