Tag Archive for 'identity'

Some thoughts on Color with a capital C

colorballmanFirst, I wanted to set this up with a couple of assertions, that location is a signal, as John Battelle defined it, and that this signal will be extremely useful when wrapped around social objects, in the way that Jyri Engestrom intended the term way back in 2005, and it’s every bit as true today.

This is a slightly more structured way of just saying that location becomes meaningful in context.

I think we can all agree that Color flopped its launch. It chose proximity-oriented photos as the social object upon which to base the serendipitous creation of affinity groups. The hope was that this activity would be so engaging that people would be motivated to invite more people to use the app, they’d use it very frequently in many locations and Color would thus have access to a hyperlocalized two-way channel into the lives of their users.

The idea is that they would then use this so-called anonymous data to create user profiles and a rich database from which to launch advertising, local promotions and news-oriented feeds. I say so-called because they neglected to understand just how identifiable photographs of faces are! (Yes, I’m looking at you Facebook.)

Another surprising oversight given the data-driven nature of the founders is that “for the average person, knowing their approximate home and work locations — to a block level — identifies them uniquely.”

Isn’t it amazing how fast anonymity breaks down?

As if this wasn’t enough, Color’s original user interface was unintuitive in the extreme and absolutely required that you use the the application with at least one other person. So, it flopped big time.

Now that Color has quietly withdrawn from the scene, it’s back to the drawing board to roll out a different application that will feed their hungry proximity algorithms champing at the hyperlocal bit, not to mention their investors looking for gorgeous pivot. How will they deal with privacy and can they find the secret sauce to make me want to share my location with nearby strangers?

My prediction is that they will not. Their approach is all wrong; it’s backwards. You cannot define yourself “much more of a research company and a data mining company than a photo sharing site,” as Bill Nguyen did and expect to have the wild imagination and fire in your belly to create an amazingly compelling social application that lots of people will love. He has some interesting ideas about the social stickiness of proximity, but it’s all wrapped around how much data he’s going to collect and sell to advertisers.

My next post will explore another proximity application…

Update: Well this seems to support my guess… “Confirmed: Co-founder Peter Pham Leaves Color” and “Troubled Startup Color Loses Cofounder Peter Pham“. Trojan horses are not lovable.

Anonymity in a connected world

I was reading this article Your Morning Commute is Unique: On the Anonymity of Home/Work Location Pairs, by Arvind Narayanan, and it got me thinking. (Thanks to @jamespage for pointing to this article.)

He starts out by citing this study by two PARC researchers and concluding that “for the average person, knowing their approximate home and work locations — to a block level — identifies them uniquely.” Isn’t it amazing how fast anonymity breaks down?

Cover art for new Penguin edition of Orwell's 1984 (Shepard Fairey)

Now just having those two data points alone would leave your anonymity intact, but the potential danger comes in if this information is able to be shared by or among mobile connectivity providers, credit card companies, government agencies, advertisers and social networking services.

It could be that my paranoia level was increased after having seen this article in New York Times describing the amount of data mining and interpretation currently being used by the credit card industry.

The exploration into cardholders’ minds hit a breakthrough in 2002, when J. P. Martin, a math-loving executive at Canadian Tire, decided to analyze almost every piece of information his company had collected from credit-card transactions the previous year… Martin’s measurements were so precise that he could tell you the “riskiest” drinking establishment in Canada — Sharx Pool Bar in Montreal, where 47 percent of the patrons who used their Canadian Tire card missed four payments over 12 months. He could also tell you the “safest” products — premium birdseed and a device called a “snow roof rake” that homeowners use to remove high-up snowdrifts so they don’t fall on pedestrians.

By the time he publicized his findings, a small industry of math fanatics — many of them former credit-card executives — had started consulting for the major banks that issued cards, and they began using Martin’s findings and other research to build psychological profiles.

So when people start to use their cell phones to pay for merchandise, location information will be added to the database, too. Conspiracy theorists, novelists and filmmakers, rejoice! There are some great storylines to be made from this stuff. But, seriously, should we be worried about these developments?

Late breaking: With respect to U.S. constitutional law, the New York State Supreme Court ruled that tracking a suspect via the global positioning system without a warrant violated his right to privacy. A stalker could be uniquely linked to the victim by GPS tracking, for instance. Hat tip to @stoweboyd for the lead. [Added 15 May 12:30 CET]

Familiar strangers

I came across this slide deck today and thought I’d post it here and make a few comments. David Reed is the Reed of Reed’s Law, a person with genuine visionary status.
He sketches how the technologically-mediated public social fabric might look in the future. In slide 2 he postulates that in order to be well-connected we will need to feel safe, establish trust with “familiar strangers” and to share and collaborate with people in the same location. I am particularly interested in the term “familar strangers,” a seeming oxymoron.
I was first reminded of a quote by Diane Arbus, “Nothing is ever the same as they said it was. It’s what I’ve never seen before that I recognize.” But then I learned that it’s a term is commonly used in studying social networks and is generally defined as “an individual who is recognized from regular activities, but with whom one does not interact.”
In the future, however, I think the definition can be extended. The recognition can take place via machine-readable data. It all comes down to context, what elements we pour into the concept of context and how we weigh these elements in relation to each other. But it will never be really useful or trustworthy until our digital lives are tagged with open metadata and semantic protocols.
Since the people we don’t know will always be more numerous than those we do, we can gain much more from social search and discovery tools that tap into the knowledge of familiar strangers, applying rules learned from examining our declared identity and our relationships with people we do know and applying them to people that we don’t know.
Yet.