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Topic: #prediction-systems

Facebook and the Problem of Free Will


OK, just one more post about Facebook, and then I'm swearing off for at least two weeks.

One of the problems with knowledge claims about future events is that the causal chains that lead to those events often include decisions that people haven't made yet, decisions that in turn depend on the outcomes of contingent events that haven't yet occurred. Facebook is offering a new product that gets around this epistemological difficulty by waving crystalline neural networks at it.

“Facebook Uses Artificial Intelligence to Predict Your Future Actions for Advertisers, Says Confidential Document”
Sam Biddle, The Intercept, April 13, 2018

Instead of merely offering advertisers the ability to target people based on demographics and consumer preferences, Facebook instead offers the ability to target them based on how they will behave, what they will buy, and what they will think. These capabilities are the fruits of a self-improving, artificial intelligence-powered prediction engine, first unveiled by Facebook in 2016 and dubbed “FBLearner Flow.”

One slide in the document touts Facebook's ability to “predict future behavior,” allowing companies to target people on the basis of decisions they haven't even made yet. This would, potentially, give third parties the opportunity to alter a consumer's anticipated course. …

[Law professor Frank Pasquale] told The Intercept that Facebook's behavioral prediction work is “eerie” and worried how the company could turn algorithmic predictions into “self-fulfilling prophecies,” since “once they've made this prediction they have a financial interest in making it true.” That is, once Facebook tells an advertising partner you're going to do some thing or other next month, the onus is on Facebook to either make that event come to pass, or show that they were able to help effectively prevent it (how Facebook can verify to a marketer that it was indeed able to change the future is unclear).

Of course, such a prediction system can't operate transparently. If there is any way for targets to become aware of the predictions that are made about their future behavior, the predictions themselves enter the causal chain that result in the future decisions, thus undermining the basis for the predictions. To take the simplest and most extreme case, what happens if a Facebook user resolves to do the opposite of whatever FBLearner Flow predicts?

It occurs to me that the perfect use for this tool would be to predict which companies' advertising managers are gullible enough to be deceived by this hokum and which ones will decide to spend their advertising budgets in less carnivalesque ways. Then Facebook could perhaps develop a slicker pitch to alter the anticipated course of the second group of marks.

#Facebook #black-box-deciders #prediction-systems

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John David Stone (

created June 1, 2014 · last revised December 10, 2018