Big Data Is Watching You

Photo: Hamish Reid.

What Does Big Data Really Mean?

Big Data is big news, big money; it’s the next big thing (where it’s not already here). And it’s a hell of a lot more than a passing fad. But what does it really mean for you and me? I don’t mean how Big Data is defined — (broadly) surveillance, analysis, and prediction, on a huge scale — I mean how’s it going to affect you on a daily basis?

The short-attention-span version: Big Data mostly means inescapable advertising, surveillance, and control (corporate, private, and governmental) on a huge scale. Everything else it enables — statistics-based medical research, advances in physics, accurate epidemiology, the ability to instantly find cute cat videos on the net — is just noise, a side effect.

The Big (Brother) Picture: Big Data means data gathering, analysis, and prediction on unprecedented scales. It means joining the dots — billions of them — in ways that were impossible until very recently. It means identifying and understanding patterns that aren’t evident without huge amounts of data and computing power; it means identifying and understanding trends before or as they happen, and predicting further trends before they’re visible at ground level. It’s a real boon for science, whether physics, molecular biology, or sociology. It’s also a real boon for governmental and corporate surveillance and control. All of that’s obvious, I’d hope.

In my techie life I’m surrounded by Big Data boosters. If they see any downsides to it at all, they think of them as unfortunate side effects; but in many cases the downsides are the whole point of Big Data. What are some of these downsides? Consider just a handful of scenarios:

  • Someone points their phone at you in public and a few seconds later knows not just your name and contact details, but also a great deal else about you as well — whether you want them to know anything about you or not. That’s Big Data. Think that’s creepy or far-fetched? I’m willing to bet that within a decade a cloud-based app using corporate or crowd-sourced data combined with face recognition will be able to do exactly that for a significant proportion of the population (and its use for advertising will surely follow — see below). In a world where “Information wants to be free” is a techie imperative, and the means to make it so are unstoppably emerging, privacy’s dead. Will anyone care? If you bare your soul to Big Data, everyone else will see it too.
  • Look around you at your cozy Internet-Of-Things (IOT) life. It’s just another platform for gathering and using Big Data on you. Companies don’t develop things like online thermostats or connected cars just to make you feel more cozy, or, well, connected — they do it because they can use the Big Data they gather from these things to profile you so they can sell you things (or they sell that data on to other companies that use that data to sell you things). Whatever connects to that connected fridge, for example, knows what you put in it, and what you take out of it; a goldmine for advertisers. And of course those IOT gadgets themselves become a platform for selling to you (that connected fridge giving you the hard sell for replacement beer or frozen dinners), but that’s not Big Data per se — it just goes hand in glove with it (like advertising and surveillance, those inseparable corporate siblings).
  • Imagine a future where you’re surrounded by inescapable, ubiquitous, ruthlessly-targeted, and heavily-personalized smart advertising. It’s in your self-driving car, it’s in your IOT home, it’s in that commuter train or bus, it’s on your VR headset and your wearables, it surrounds or confronts you when you’re strolling through a mall or walking down the street. Thank you Big Data! If you think Minority Report’s omnipresent hectoring advertising was just science fiction, you’ve got a lot to learn. It’s your likely future, and it’s called immersive advertising. It’s the sort of thing that’s the whole point of Big Data for many companies developing or using it. They see the future in terms of accurate consumer profiles, omniscient consumer surveillance, and highly-targeted pitches (all finally made possible by Big Data); what do you see? Ads, ads, ads.
  • You could develop this further — instead of immersive advertising being a distraction, it becomes your reality, an experience (“Using creative techniques, these brands have created concepts that immerse the viewer with their own branded worlds, transforming advertising from a message to an experience.” — straight from the horse’s mouth. Because we all want advertising to be an experience, no?). At some point it becomes the way you experience the real world. It already happens to a tiny extent, but with Big Data it’s a reality (that word, again). Society of the Spectacle? No, the Society of the Brand (they may be much the same thing). Or Branded Reality (does anyone remember what branding used to mean?).
  • You rent or buy a car. It comes with a non-removable tracking device attached — it’s a not-negotiable part of your rental agreement or insurance contract. You’re tracked every inch of the way when you use that car — and your insurance company knows every destination, every time you break the speed limit, break the law, or stop to go to the toilet. Car insurance or car rental problems now? You ain’t seen nothing yet…. That’s Big Data. And it’s already a (partial) reality in some places. But it’s not just the insurance or rental aspects that are in play here — all that Big Data about you just feeds into your individual behavioural profile for selling things to you, as well (and you’ll probably be sold to in that car as well, of course, based on your destination and in-car behaviour).
  • Imagine Precrime with the psychics replaced by analysts (human or not). Think that’s far-fetched? It’s already happening, at least in embryonic form (it’s called “profiling” in its most primitive form). It’s probably inescapable (for all the usual “public safety” reasons). The only reason it didn’t happen earlier was the sheer computing power and the size of the datasets needed. That’s Big Data’s specialty, no?
  • Imagine medical and life insurers knowing pretty much everything there is to know about you and your health, and being able to predict your likely health issues well in advance. That’s Big Data. Great, huh?! And in a civilized place where access to health care isn’t primarily determined by your social or economic status or past, present, and future health, it’s probably a good thing. But in a place like the US where private health insurance is the norm (and where insurers can drop you or refuse you or raise your rates based on existing or likely conditions) it’s potentially catastrophic. For the rich or well-insured, it’s probably a boon; for the rest of us, it’s just another way to deny insurance (and therefore, decent health care) altogether. And there’s no way on earth that this data about you will remain private, of course (think “Big Data Hackers”, but see also my first scenario, above).

I could go on (there’s much more where that came from, some of it more sinister and paranoid). But the point is, if you think scenarios like this are an unfortunate side effect of Big Data, you probably haven’t been paying attention. These scenarios (and similar ones) are often the whole point of Big Data for many companies and governments.

Who does Big Data best (besides, say, oh, the NSA and GCHQ)? It’s companies like Google or Amazon. And why? Well, Google’s not a search company — it’s an advertising and data company that uses search and Big Data to learn about you and to help others sell things to you. And it’s not a car company either — developing always-connected, self-driving cars for everyone is a wonderful way to get more data on everyone (or to entrap you in a mobile immersive advertising machine). (Which is not to say that the people developing those cars think that way — it’s almost certainly a lot of fun, and I’d love to be one of those developers. Which is part of the problem, no?)

Big Data’s inevitable, as are so many of its less pleasant intended uses. What to do about it? I don’t know.

(Initially written for a non-tech audience elsewhere, but I thought I’d put it up here as well…).

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