It’s Privacy Week here at CoinDesk, and we’ve been diving into a variety of technological and legal angles on the consequences of digital surveillance
It’s Privacy Week here at CoinDesk, and we’ve been diving into a variety of technological and legal angles on the consequences of digital surveillance. Anxiety about the rise of omnipresent snooping can often feel like an academic matter of principle, or a series of warnings about important but uncommon edge cases: the battered spouse being stalked with malware, the dissident tracked and murdered by a government, the consumer with legal but socially marginalized tastes. These scenarios of privacy compromise have serious implications, of course, for those who fall victim and for every single one of us.
But the most widespread use of digital surveillance can seem far more mundane than these headline examples, while being potentially vastly more insidious.
Algorithmic content targeting is the foundation of omnipresent information businesses like Google and Facebook, and it affects you every moment you’re online. It can make you less informed, less unique, less thoughtful and less interesting, so subtly you don’t even notice.
Harvard researcher Shoshana Zuboff describes the impact of algorithmic targeting as “the privatization of the division of learning.” We have increasingly handed over our decisions about everything to pattern-recognition software, she argues. It guides our interactions with social media, dating sites, search engines, programmatic advertising and content feeds – and it’s built almost entirely on models of past human behavior. At its structural root, it is hostile to novelty, innovation and independence. And its pioneers have benefitted hugely from it – according to Zuboff, Google now has a “world-historical concentration of knowledge and power.”
I have a slightly snappier name for this than Zuboff: the Algorithmic Loop. Like most loops, it is easy to get trapped in because it harvests our preferences, then uses that data to keep us hooked – and take control. Sure it shows us prospective dates or movie titles or news blurbs that it knows we’re likely to click. But those suggestions in turn shape our desire for the next thing we consume.
The algorithmic loop, in short, doesn’t just predict our tastes, attitudes and beliefs, it creates them. And because it shapes them based on only what it already knows and can understand, it is making us less creative and less individual in ways that we have barely begun to understand.
Over time, the individual and collective effects may prove devastating.
Lowest common denominator
How is the algorithmic loop narrowing the range of human thought and creativity?
The dynamic varies but consider the basics. Companies like Facebook, Amazon and Google ultimately make money by showing you things you might want to buy. One level up, social, search and streaming platforms keep your attention by showing you content you are most likely to find “engaging.” They accomplish these goals by observing your behavior, matching it to the behavior of similar people, then showing you the other things those people liked.
These systems are sometimes praised for their ability to help users with niche tastes find precisely what they’re looking for, and there is some truth to that. But the larger dynamic is easy to spot: The algorithmic loop operates on the fundamental assumption that your taste is interchangeable with other peoples’. The algorithm can neither predict nor create personality, innovation or chance encounters – which means that it is ultimately hostile to personal empowerment and individuality.
As a thought experiment, imagine a truly average user of YouTube or Amazon Prime Video. What do you suggest to someone who has rented five mainstream Hollywood films because that’s all they’ve heard of? Well, you offer them more of the same mainstream, middlebrow, easygoing content. Even when content truly is tailored to a demographic niche, the creative process has become an exercise in box-checking: Netflix, famously, uses its algorithmic loop to “optimize” a piece of content for success before it is made. If art at its best is a process of self-discovery and learning, the algorithmic loop is turning us away from that and toward simply repeating ourselves endlessly.
That algorithmic bias towards banality, along with other forces, has already dumbed down our culture in measurable ways. In the 20-odd years since algorithmic recommendation engines have been in the wild – first at online bookstores like Amazon, then at Netflix’s DVD service, then on streaming video and music platforms – global popular culture has undergone a radical contraction centered on the most popular and inoffensive blockbusters.
For example, Spotify, an algorithm-centered music platform, concentrates streams and earnings among a handful of top artists far more than the physical media-and-broadcasting system that preceded it. This is particularly striking because the terrestrial radio conglomerate ClearChannel was so often a bugaboo for music fans in the pre-internet…
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