Google and New Media

The other day I googled a product and the next website I went to it was advertised to me. Coincidence? How about the time I sent a snapchat picture of a item to a friend and two minutes later got a sponsored ad about it on Facebook? Or the time one of my contacts from my emails showed up on Facebook as a person I may know. Or Siri suggestions on my iPhone reflect the people I most recently message in a third party app. Welcome to the hyper connected world where Google searches you.

Facebook is currently building technology to almost pinpoint accurately describe the contents of an image, which at this stage is designed for the purpose of helping blind people to see, at least in a metaphorical sense, what their loved ones are posting on Facebook. This all seems well and good but I have seen Facebook identify the out of focus, underexposed faces of people in the background of my photos as exactly who they are. Imagine a world where your friend takes a photo of you and snapchats it to another person and within seconds the shopkeeper of a nearby store knows you are outside and walks out of the store with the new blender you’ve been looking at on eBay at a cheaper price. This is the future.

Google processes 52,300 searches every second which equates to roughly 3,000,000 every minute. Possibly the most influential and scary influence in the modern media landscape is integration. Films like Ex Machina and Corridor Digital’s Sync draw upon the idea that an AI could be created that may actually be able to process that much information. Google’s index now contains over  60 trillion pages, this is called the crawled web, as Google has thousands of computers constantly crawling the web and indexing pages. The question then follows… what can Google do with that data. Well aside from sending your search query an average of 1,500 miles and back, Google returns pages you searched for from the over 100,000,000GB database, ranking your search using over 200 individual factors and all of it in less than an eighth of a second. Every search uses about 1000 individual machines.

Every single movement you make online is saved somewhere, whether on a local server, in temporary files, caches, external machines, government metadata, it’s all there. Imagine if one person was actually able to see all of it, every site you’ve ever been to, every video you probably shouldn’t have watched. No one is closer than the search giant but even the like of Google can only index a portion of the surface web. What I mean by that is Google can index over a million pages a minute but there are more than twice that created on Facebook every second including every single comment, picture, status update. All of these elements have what are called permalinks (I briefly mentioned these in my first blog post about blogging). They are being created at rapid speeds, so much so that we don’t even have the ability to quantify the size of data creation on the net and every estimate only takes into account a small sample space. And here’s the best part, the deep web or hidden web as some call it is literally thousands of times larger, and that’s just conservative estimations.

It is quite possible that there are multiple hundreds of terabytes of data per person on the face of the earth.

So the question I’m putting forward is, how soon, in this hyper-connected modern internet age (where all the social networks and search engines are literally building a digital profile of me) will the information be no longer private. When the internet sends you ads for books about cheating partners when you didn’t even know your partner was cheating. When computers can serve up media campaigns tailor made to target your individual emotional responses based on your opinions, desires and emotions, the kinds of literature you read.

As media practitioners we need to update our vocabulary, more than ever we have the tools at our disposal to make informed choices about what stories we tell and why and whom will watch them and who will respond to them. Never before have we had enough data to predict down to the exact dollar, how much money a certain ad campaign will generate for a company based on exactly what colour socks a person in Guatemala prefers to wear.

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