If our privacy is going out of the window anyway, let’s go the whole hog! Why let the Big Data/Internet of Things future be a plethora of individual apps/processes when it could be just a simple ‘global identity’ for each of us? [‘tongue-in-cheek mode’ enabled]
Let’s concoct a future scenario (extended from a passage in the book) to work with … You’re out for an urban stroll. You buy a bottle of orange juice along your way, and drink it as you’re walking. Half a mile down the road, you throw the empty bottle in a bin. Not that inspiring? OK, let’s IoT/big data it up a bit …
Your exercise is being monitored as you walk. When you buy the bottle, the cost is automatically debited from your bank account. Also the juice’s nutritional information is fed into your fitness tracker along with your steps. At the same time, the juice/bottle’s carbon penalty is added to your personal carbon footprint. If you dispose of the empty bottle in an approved recycling bin, some of that carbon penalty is credited back to you. The balance is your carbon tax to pay, although this is mitigated by an adjustment against your health tax: calculated from your fitness tracker’s juice and steps data. The net cost is also taken directly from your bank.
So, how might that all work?
This follows on from last month’s post, in which we discussed the possibility of a future Shazam for People service and extends it to the concept of a ‘universal tracking system’ or real-world Marauder’s Map …
So, just how feasible is it?
The Shazam for People discussion revisited as an article, ‘Identity Voyeurism‘, in September 2015’s British Computer Society (BCS) IT Now Magazine, made all the more relevant by recent breaches of personal privacy …
There’s more than one type of identity ‘crisis’. Conventional identity ‘theft’ is one thing but what of identity ‘voyeurism’? How much of ‘us’ is ‘in the shop window’ anyway? Are we in control? What are the risks? And where’s it heading?
The next time you’re on public transport, try playing the ‘Prof on a Train’ (PoaT) game. (It doesn’t really have to be a train or an academic but it’s a good example to work with.) Take a look at the person opposite you. Armed only with your senses, intelligence, intuition and an Internet connection, how much can you find out about them?
Well, if they’re quietly dozing in the corner, unremarkably dressed, with no distinguishing features whatsoever, you’ll probably lose. However, any activity at all or any visible clues might give you a chance. Are they doing, reading, saying or wearing anything? Who’s with them? Are they easier to identify? Where did they get on and do you know where they’re going? Anything odd? Here’s the basic strategy, on which PoaT is based:
They’re reading an academic paper on a certain subject (X) and you know where they got on (Y). A quick look at the photos on the ‘Department of X’ webpage for the ‘University of Y’ might be enough.
When Shazam first arrived on the scene, it was pretty amazing stuff; now, we rather take it for granted. But could the same idea soon work for people?
We know the scenario … You’re in a bar or a shop or listening to the radio or TV … or … just about anything really … and you hear a song that you either like or think you recognise or both … but you don’t know what it is. Frustrating, isn’t it? At least it was until music identification services such as Shazam first appeared. After that, no worries; simply allow your mobile to listen to the music for a few seconds, search the central database and, after a few more seconds, it reports back to you with full details of the name, artist and origin. It might even link you to a central library where you can find more of the same or possibly buy it.
Simple enough; but, might the same principle one day work for people? It’s really not that hard to imagine …
Accessible text version of photo
Then: “Ah, but this is only the free stuff. If you’re prepared to pay, I can tell you a lot more about him … “
It sounds like a science fiction ‘Big Brother for Everyone’ nightmare scenario. But could it happen? If so, how soon? Continue reading