I think you touch on two of the significant tangible risks of data mining (discrimination and limitations on social mobility). I suppose abuse of data and errors in the data and process would be other risks. What I find more difficult to articulate are the abstract risks of data mining - this instinct that it's just inherently wrong to assemble and aggregate data about individuals. Although if that instinct has something to do with free will, that ties back into the point of your paper nicely.

-- ElizabethDoisy - 27 May 2009

-- WardBenson - 27 May 2009

A Return to Calvinist America

During a recent argument I had some difficulty defending the anti-data-mining cause. Ok says the 1L, putting aside fears about abuse by employees of data aggregators, the consequences of inaccurate records, and the potential loss of autonomy that may occur depending on how much you buy behavioral economics, if the data aggregators get it right, won't that be more efficient for the economy and the nation? What if the banks really can accurately determine everyone's true credit risk? What if the health insurance companies really can predict someone's lifetime health care costs? What if New York law firms can hire only those people who will work the hardest and not leave after immediately paying off their debts? Won't everything work more smoothly? While at the time I failed to give a convincing response, as is typical, a better (in my opinion) response came to me about ten seconds after the conversation ended. Sure, it is possible that through the use of data-mining and analysis banks may be able to much more efficiently dole out credit and companies will be much better able to know who they are hiring. However, no matter how much data-mining may be good for the economy (at least in the short-term), it poses a threat to one aspect of what America stands for. Crucial to American culture and mythology is the belief that America gives people a unique opportunity for reinvention. Whether their model be an immigrant who leaves behind the role he held in his previous country or the native who puts an unseemly past behind him and becomes an upstanding citizen, many believe in the American system and accept their place in it because they take it as an article of faith that anyone, no matter what they have done in the past, can start afresh and eventually succeed.

Reinvention is never quite as seemless as the myth implies, though, and Americans are rightly skeptical of those with tarnished pasts who claim to have turned over a new leaf. Apart from those segments of society with a long tradition of accepting people as born again after sufficient public shaming and atonement, a person's prospects for reinvention have always partially been a function of their ability to keep their past obscure enough to be plausibly benign. Data-mining makes recasting one's background impossible, however. You are no longer the resume you choose to hand to an interviewer or the persona you choose to present to a bank's loan officer. Your entire background and everything that can be inferred from it about your future prospects as an employee or debtor are available and beyond your control to frame in a positive light. When combined with the often unspoken skepticism that belies Americans' belief in individuals' capacity for change, this loss of control over the public perception of one's past may eliminate many wayward souls' chances for redemption.

Besides making it more difficult for individuals with self-imposed damaging pasts to move on, data-mining also harms those who must dig themselves out of backgrounds they did not choose to have. Generations of Americans have grown up believing that in our post-feudal society, debts reside and die with those who incurred them and are not passed on to their children. While technically still true, if it can be inferred that your parents' tendencies towards profligate spending was passed down to you, you perhaps may as well have inherited their debts if the result is higher fees and interest rates thanks to an omniscient credit rating agency. And ironically for a country in which there is so much bloviation about ``family values,'' those who will be most negatively affected are those who are deemed most likely to be loyal to and supportive of their kin because it will be inferred that they will come to their relatives' aid even at the risk of their own finances.

In the same way, data-mining may serve to reinforce the hardships endured by those who try to extricate themselves from backgrounds determined by race and class. Up until recently, a person ``of the other color[s]'' born in a neighborhood that had been red-lined could still, if sufficiently committed to changing their identity, have had a decent chance at home-ownership. By moving to a new, hopefully more tolerant area and ensuring that they dressed, spoke and acted the ``right'' way, they could convince a loan officer that they were not like ``the others.'' The same was largely true for attempts to enter other parts of the upper echelons of American society. There is no escaping the ghetto in the era of data-mining, however. If someone with power chooses to look hard enough, either blatant bigotry or well-meaning but invidious calculations may eliminate what was an, albeit demeaning for some, effective method of advancing in American society.

But since data-mining doesn't seem to be going away anytime soon, it may be wise to consider whether its killing of the American myth of the possibility of reinvention, and the related myth of the self-made man, has a silver lining. While Gladwell (and his editor) must have been overjoyed to learn that so many Americans were surprised to read that one's outcome in life is largely a product of one's upbringing and surroundings, the fact that it was such a revelation shows that the American myth of the self-made man--one who can succeed regardless of growing up under less than promising circumstances--may have been too powerful. While today Americans of all classes vigorously reject the notion that we are restrained by our backgrounds, if enough inference-making by the purchasers of our data makes this inevitably true, perhaps we will all have to rexamine our myths and think much more broadly about what must be done to make America a true meritocracy.

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