The tech giants use our data not only to predict our behavior but to change it

The tech companies’ innovation rhetoric effectively blinded users and lawmakers for many years. Facebook and Google were regarded as innovative companies that made dreadful mistakes at the expense of our privacy. Since then the picture has sharpened.

The logic of surveillance begins with unilaterally claiming private human experience as free raw material for production and sales. It wants our walk in the park, online browsing and communications, hunt for a parking space, voice at the breakfast table…

These experiences are translated into behavioral data. Some of this data may be applied to product or service improvements, and the rest is valued for its predictive power. These flows of predictive data are fed into computational products that predict human behavior.

A leaked Facebook document in 2018 describes its machine-learning system that “ingests trillions of data points every day” and produces “more than 6million predictions per second”.

Finally, these prediction products are sold to business customers in markets that trade in human futures.

Markets in human futures compete on the quality of predictions. This competition to sell certainty produces the economic imperatives that drive business practices. Ultimately, it has become clear that the most predictive data comes from intervening in our lives to tune and herd our behavior towards the most profitable outcomes.

Data scientists describe this as a shift from monitoring to actuation. The idea is not only to know our behavior but also to shape it in ways that can turn predictions into guarantees. It is no longer enough to automate information flows about us; the goal now is to automate us.

The big picture reveals extreme concentrations of knowledge and power. Surveillance capitalists know everything about us, but we know little about them. Their knowledge is used for others’ interests, not our own. Surveillance capitalism thrives in the absence of law or the proper implementation of the law.

The question is what kind of regulation? Are existing approaches to privacy and antitrust law the answer? Both are critical but neither is adequate.

One example is privacy law’s call for “data ownership”. It’s a misleading notion because it legitimates the unilateral taking of human experience?—?your face, your phone, your refrigerator, your emotions?—?for translation into data in the first place. Even if we achieve “ownership” of the data we have provided to companies like Facebook or Google, we will not achieve “ownership” of the predictions gleaned from it, or the fate of those products in its prediction markets.

Data ownership is an individual solution when collective solutions are required. We will never own those 6million predictions produced each second. Surveillance capitalists know this.

Research over the past decade suggests that when “users” are informed of surveillance capitalism’s backstage operations, they want protection, and they want alternatives.

We need regulation designed to advantage companies that want to break with surveillance capitalism. Competitors that align themselves with the actual needs of people and the norms of a market democracy are likely to attract just about every person on Earth as their customer.

Surveillance capitalists are rich and powerful, but they are not invulnerable. They fear law. They fear lawmakers. They fear citizens who insist on a different path. Both groups are bound together in the work of rescuing the digital future for democracy.

In conclusion, there is a need that companies respect the data privacy protection and implement the Data Privacy Law, and that individuals understand their ‘power’ over their privacy. Sad to say, we have not reached both objectives – yet.

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