Verified Data Will Prevent “Fake It Til You Make It”

Besides having a great animated graphic, yesterday’s New York Times “Faking Cultural Literacy” OpEd got me thinking about the role of verified data. The column touches on the increasing proclivity (or even probability) that you develop and espouse an opinion without even experiencing the source data itself.

“It’s never been so easy to pretend to know so much without actually knowing anything. We pick topical, relevant bits from Facebook, Twitter or emailed news alerts, and then regurgitate them. Instead of watching “Mad Men” or the Super Bowl or the Oscars or a presidential debate, you can simply scroll through someone else’s live-tweeting of it, or read the recaps the next day….What we all feel now is the constant pressure to know enough, at all times, lest we be revealed as culturally illiterate.”

My personal experience with this phenomena is when I find myself slipping into a mode where the pleasure comes from finishing the book/movie/article/etc rather than actually absorbing and enjoying it. “Slow Media” is about bringing mindfulness to consumption of content just as Slow Food did for eating.

The column also reminded me how much more I favor systems where there’s some verified data besides a person’s opinion. A basic example is you must have downloaded an Apple iOS app before being able to review it. It’s sort of an “experience gate” as opposed to a paygate.

We’re also seeing verified data show up in resumes via first and third party tools. A software engineer who claims proficiency in Ruby might display a github score. Or a hiring manager may run a stack of resumes through some candidate eval software which pulls all sorts of data from github, stack overlflow, etc in order to try and verify that an individual has at least been publicly active in an area.

There are plenty more areas for this to go. For example, when I see all these armchair analysts tweeting about whether Twitter stock is overvalued or not, I’d love to know which actually own Twitter and have increased or decreased their holdings. You don’t need to disclose actual share figures, but even just a binary Yes or No would start to separate pundits from people putting their money where their mouth, err tweets, are.

I’m hoping via interesting APIs that we’ll see many more of these verification opportunities. One of Homebrew’s investments is a company called Plaid, which can be described as a modern API for banking data. There’s plenty of interesting ideas here which match again my theoretical use cases. For example, if a user gave Yelp permission to link their credit card accts to their Yelp account, Yelp would know whether a user charged a meal at a restaurant they reviewed and be able to use this in scoring trustworthiness. If you’re building a company around the availability and use of verified data (especially using APIs or blockchain), I’d love to hear more (

One thought on “Verified Data Will Prevent “Fake It Til You Make It”

  1. Great post. I like the way you theorize that there could be triangulation of information reality, by combining disparate datasets (Yelp + credit cards). I wrote a paper once about using business metadata (not tech metadata) to better define facts so that they are not used inappropriately. This led me to think about the notion that as datasets become publicly available, maybe there should be some notion of a ‘data auditor’ that would validate that the business metadata tied to the actual fact records that are presented through an API. It’s the same function as an accounting auditor who verifies that published financial facts are categorized according to the appropriate definitions and match the reality of the company’s performance. Curious about your thoughts here.

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