It doesn’t matter who you say you are! Where you are (space), when you’re there (time), and your movements over time (travel) are closer to the truth.
I’ve seen a lot of data in my life, and I’d like to think I have a decent grip on what can be accomplished with data and analytics. However, I recently stumbled upon some facts that have radically reshaped my understanding of the world we are living in. What I thought was years away is already here! Our toes are dangling over the edge of a very different future.
Now, before you get all worked up, remember: You have helped
create this, most folks love this, and most will continue to eat this up
despite the obvious consequences.
Now, before you get all worked up, remember: You have helped create this, most folks love this, and most will continue to eat this up despite the obvious consequences.
Mobile devices in America are generating something like 600 billion geo-spatially tagged transactions per day. Every call, text message, email and data transfer handled by your mobile device creates a transaction with your space-time coordinate (to roughly 60 meters accuracy if there are three cell towers in range), whether you have GPS or not. Got a Blackberry? Every few minutes, it sends a heartbeat, creating a transaction whether you are using the phone or not. If the device is GPS-enabled and you’re using a location-based service your location is accurate to somewhere between 10 and 30 meters. Using Wi-Fi? It is accurate below10 meters.
It should be no surprise that all this data lives in the coffers of the cell providers. Lots of people know that. What is new, at least to me, is that this data is being provided to third parties that are leveraging specially designed analytics to make sense of our space-time-travel data.
With the data out and specialized analytics emerging, this infant industry is already doing some pretty amazing work. Your space-time-travel data makes where you live and where you work self-evident, and it reveals your most frequent, periodic, infrequent and rare destinations.
The data reveals the number of co-workers that join you Thursdays after work for a beer, and roughly where you all go. It knows where these same co-workers call home, and just exactly what kind of neighborhood they come from (e.g., average income, average home price) … information certainly useful to attentive direct marketing folks.
Large space-time data sets combined with advanced analytics enable a degree of understanding, discovery, and prediction that may be hard for many people to fully appreciate. Better prediction means a more efficient enterprise and nifty consumer services.
Cellular companies are now receiving essential insight about their customers (e.g., to better understand and predict customer churn). Major retailers can now better understand changes in consumer behavior (e.g., how far their customers are traveling on average this month compared to previous months). Consumers are benefiting by getting real-time traffic information so they can avoid congested roads. (I have a colleague that thinks he is saving two to four hours a week in commute time due to this service!)
Tip o’ the iceberg.
I can barely get my mind around the ramifications. My concept about what comes next shifts almost daily now. A government not so keen on free speech could use such data to see a crowd converging towards a protest site and respond before the swarm takes form – detected and preempted, this protest never happens. Or worse, it could be used to understand and then undermine any political opponent.
A stalker might be questioned just days after he starts and before his victim is personally aware of it – detection previously beyond human capacity. Maybe it’s not a crime in this case, and it turns out to be just a private investigator with poor tradecraft hired by a suspicious husband.
Such a surveillance intensive future is inevitable, irreversible and as I have said before here … irresistible.
Why? Companies must be competitive to survive and consumers have quite the appetite for almost anything that optimizes their life, especially if it’s cheap or free. For example:
Tuesday afternoon your [free] Gmail account advises you that your buddy Ken is going to be 15 minutes late to the pool hall this coming Thursday, unless he leaves work 15 minutes early … which he has only done twice in seven years. Brilliant!
Your Starbucks drink of choice (a grande vanilla soy latte in my case) is handed to you the instant you pull up, and you did not call ahead nor did they ask. Priceless!
When powerful analytics commingle space-time-travel data with tertiary data, the world we live in will fundamentally change. Organizations and citizens alike will operate with substantially more efficiency. There will be less carbon emissions, increased longevity, and fewer deaths.
I think people should know about this imminent new age we are marching into.
[Theatrical pause. Breathe.]
Now I’m going to step back and address some questions you may have, using the good news/bad news format.
Good news: The space-time-travel collected by the cellular network carriers is de-identified when provided to these third parties for privacy reasons in that it does not include your name, address, phone number, etc.; rather, unique identifiers are assigned to transactions from the same device so that trends can be measured.
Bad news: If you were to provide your home, work and one other address (e.g., gym, school) in most cases, with just these data points, you are re-identified. With just a few days of space-time-travel activity, your top three or four more frequently visited destinations become self-evident, and without a whole hell of a lot of effort you could be re-identified through a tertiary data set like a credit header.
Good news: There is so much data being produced, a lot of transactions are tossed aside, are sampled and summarized to make the computational effort feasible. Historical data also falls off the back of the wagon (ages off the system) rather quickly.
Bad news: The competitive nature of this emerging business model will likely require these organizations to make more sense of more data faster. Cloud computing and new classes of algorithms will make it possible to keep more transaction detail, keep it longer, and commingle it with other large and very interesting secondary data sets (e.g., phone books and property records).
Good news: So far there are only a handful of companies already entrusted with this data.
Bad news. It may not be good news that only a few companies do this. If only one company can monitor the consumer foot traffic of all Nordstrom stores in near real time, this would be an unfair advantage in terms of predetermining its financial condition before anyone else. As I learned from countless conversations with my friends at the ACLU, very powerful tools in the hands of a few is not often a good idea without one hell of a lot of oversight and accountability. And even then, this is no panacea.
Good news: Some of the organizations holding space-time-travel data are fully aware of the privacy consequences and are offering consumers the ability to opt-out – meaning, if they get a transaction about you it will be permanently removed from the system and all future correlation.
Bad news: If by chance a snapshot of sufficient detail had been sold off to another party before the opt-out request, then the toothpaste is out of the tube. Data tends to replicate, more about this here.
Good news: Not any old mom and pop operation can get into this business.
Bad news: That won’t be true for long. Suppose an aspiring entrepreneur makes a compelling proposition to a number of parties holding space-time-travel data. Anticipating free analytics and a cut of the future action, the parties work a deal. For computing power this entrepreneur simply hops onto Amazon’s EC2 cloud and partners with a data aggregator to get some tertiary data and what do they have? An ultra-sexy prediction engine.
Good news: People tend to appreciate location-based services, which is why they are opting in.
Bad news: Sensitive information about people is no longer under their own control. As well, a number of well held secrets (e.g., your hideout) evaporate overnight.
Good news: If you want to escape the consequences of having your space-time-travel being graphed by others, here are some options that come to mind:
(a) Stop using mobile devices;
(b) Use multiple devices e.g., use one device only at work, and only a land line at home – all mobile devices being off at all other times (never moving around with a device on) – being sure these mobile devices are registered to someone other than you – and if you need to use some kind of device while on the move or at other locations. see (c) below;
(c) Unregistered, cash-purchased, disposable devices – used once then discarded (or recycled!) – although in some cases you can use the device a few times, but you better let some fancy software (which I may have to invent) advise you what is safe usage and what is not.
(d) If you can figure out locations on earth where only one cell tower exists (and you are not moving between towers and never using GPS or Wi-Fi) you will probably live safely under the radar – unless you are a way bad mofo and others know it, in which case, you are ‘going down’ anyway because there are more tricks (expensive) which will be levied against you.
Bad news: Few are willing to be this inconvenienced. And if only a handful of innocent, clean living folks go to this same effort that the bad guys MUST employ … well crap, that in itself may be considered by some to be signal.
Net Net: My guess is most consumers don’t fully realize how their space-time-travel data is accumulating and congealing. I hope consumers come to appreciate how all of these nice conveniences of life are delivered. And I hope they will continue to enjoy these while they make better informed decisions, especially with respect to their privacy.
However, without a feedback loop consumers may never fully appreciate what can be gleaned from their space-time-travel trail. Therefore, one way to enlighten the consumer would involve holders of space-time-travel data to permit an owner of a mobile device the ability to also see what they can see:
(a) The top 10 places you spend the most time (e.g., 1. a home address, 2. a work address, 3. a secondary work facility address, 4. your kids school address, 5. your gym address, and so on);
(b) The top three most predictable places you will be at a specific time when on the move (e.g., Vegas on the 215 freeway passing the Rainbow exit on Thursdays 6:07 - 6:21pm -- 57% of the time);
(c) The first name and first letter of the last name of the top 20 people that you regularly meet-up with (turns out to be wife, kids, best friends, and co-workers – and hopefully in that order!)
(d) The best three predictions of where you will be for more than one hour (in one place) over the next month, not counting home or work.
On the subject of privacy and civil liberties consequences, privacy by design is essential. And for those of you with ideas in the area of policy or technology, I would be most appreciative if you would share these thoughts with me … sooner rather than later.
I will continue sharing perspectives about these ideas and the apparent consequences with my many friends in the privacy community, the defense/intelligence community, and media. (Surprisingly, their feedback so far has been quite similar.) I am also speaking with the organizations amassing and analyzing this space-time-travel data to learn more about what is possible. From the perspective of the analytic engines I create, this space-time-travel data looks like “super food.”