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You’re In Good Hands, With Geek Insurance

October 19, 2009

Had the honor last week of speaking on a panel at the VRooM “Getting Personal With Data” panel, hosted by the typically brilliant and insightful Keith Hopper and Doc Searls. My fellow panelist was local entrepreneur Ben Rubin. His company, Zeo, is in the business of personal informatics — sleep, in particular. They produce slick alarm clock units that sync with a headset that the user wears at night. The machine tracks a variety of really neat stuff for the obsessive lifehacker in all of us: when you sleep, how much REM you’re getting, whether or not your sleep is being disturbed, and so on.

One point of discussion emerged from Ben, a position that you’ve heard a great deal if you’re anywhere near conference-inclined for the tech-open data-free/open source software world. This was the looming threat of the Data Dilemma, a common paranoia of businesses involved in handling large quantities of information. The general idea is this:

Businesses are majorly screwed with regards to choosing to make their data about users widely available or strictly controlled. Whatever they do, they will lose.

More eloquently:

Businesses that collect and archive data face a crucial choice in design. One is to open their data up — allow users to pull it down at will, and provide easy systems to port to other services. This is great on many levels — users are empowered to create new uses for their data, . Though for businesses, this is a real immediate opportunity cost on one level: you lose the chance to charge users for access and premium services around their data. In addition, there’s a menagerie of potential (though likely) other threats: beyond letting vertical competitors into the game that might build new services on top of your data, it also allows users to exit your service if they want to join a horizontal competitor that offers the same features.

However, to keep it closed and play it “safe” is an equally unsustainable strategy. True, you save yourself from the palpable negatives above. But walking through this door risks the possibility that your users will just get cleverer than you at hacking around your restrictions and getting what they want (something that we’ve been happen time and time again). And, even assuming that you could perfectly defend against this, there’s a bigger threat on the horizon. In particular, your willingness to close the data creates incentives for new businesses to get into the game and steal your customers by offering the open data that your customers want. The more iron-fisted, the bigger the incentive. Supply meets demand, and your profit takes a trip south. In both cases, time grinds down your advantage like so many novelty glass plates in a bull shop.

In parallel: it strikes me that the data dilemma is a smaller, meaner little cousin to the looming copyright dilemma that businesses hem-and-haw over repeatedly as well. It goes like this —

Permissive licensing like Creative Commons is great: it promotes content, encourages remixing, and otherwise. But, like the Data Dilemma, choosing to be permissive means that you lose out on business opportunities to charge people for the content. Plus, you open it up for other people to appropriate your work — inviting competitors and imitators.

However, to vigorously threaten legal action, and to protect restrictive copyright regimes, come with many of the same threats as time passes. Your users, instead of being deterred, might merely become ever more clever at pirating your stuff. Your competitors, seeing an opportunity to serve your market and steal your business, have incentives to design business models that feature permissive use of content.

Now, in the world of Free Culture and the variety of people concerned with personal data, there’s a couple of classic responses to these worries. We emphasize the inevitability of technological change, saying that it’s all a matter of time before The Big Bad Internet will come and erode the advantages of closed data. Or we emphasize the good, arguing for the benefits of allowing user innovation and community engagement. Or we deploy an arsenal of anecdotes, citing customer loyalty and other factors as reasons why its worked for this-or-that business in the past.

I admit that I kind of sympathize with businesses here. Easy for you to say, they might rightly throw back at people like us. And it’s true: we’re not the ones going down with the ship if the business fails, and there’s no good way to tell if it will work for them the same way it works for the odd success story. From their perspective — someone’s telling you to jump off a cliff with largely only a vague reassurance that a genie will pop out of your ass and you’re going magically going to start flying. I mean, really, who would?

While I can see where they’re coming from — as people interested in the overall ecology of the web, we worry about the aggregate effects of this reluctance towards opening data. Many businesses, choosing to remain closed, create a huge collective action problem and a systemic risk. This concern is partially Lessig-ian: siloed data and content lowers the possibility for innovation and cultural expression. It’s also partially just a worry about the logic of straight economics: popular, first-mover closed services have a huge advantage against competitors. Why move all my data from Zeo to another service, for instance, if it means I’ll lose all the data that’s already been collected? Closed ecosystems of data might remain closed (or become increasingly closed).

So, for those concerned about the ecology of the web, how do we provide more than reassurance to worried businesses squaring off against this dilemma? How do we make it worthwhile and persuasive for businesses to open up their data?

Here’s my plan: you pay me, repeatedly.

Look at it this way, the Data Dilemma implies that businesses face risk and uncertainty. Since the option of keeping data closed is only temporarily tenable, they would take a path of opening up data if they knew more certainly that they would benefit from taking this option.

But the data dilemma is not a special situation: businesses (and, for that matter, individuals) face analogous risky situations all the time. Do I trade with vendors online and run the risk of them being fraudulent? Do I move into a house and run the risk of it burning down? Do I ship this extremely expensive heirloom through the mail and run the risk of it being lost? How do I reap the advantages of living, and deal with the risk that I might, you know, die at some point?

The point here is that we have a recently unpopular though still critical instrument that we commonly use for things like this. It’s called insurance. Why couldn’t we do the same for businesses and their technology policy decisions? It’s tough out there for a business that wants to play it geek-friendly. Why couldn’t we offer, in a phrase, geek insurance?

So here’s my plan, again: you pay me, repeatedly. In exchange, I issue a data openness insurance policy. We’ll evaluate your business at regular intervals, and, if your business dips below a certain threshold, or competitors come to occupy a certain percentage of your market share as a result of your actions in allowing users to get their data — we will pay you, in full, for the entirety of potential business lost from opening data.

Interestingly enough, if it turns out that we are in fact right, that empowering your users with portable and interoperable data really is a win-win from the point of consumers and businesses — geek insurance should be, in fact, enormously profitable as a business (and as a sector). What we would be insuring against is risk, but importantly, only perceived risk — an insurer’s wet dream. Businesses would pay us for their policy, but we should rarely ever have to give a big payout back, since they should succeed by being open.

Like real insurance providers, this plan would also give some control over the process. Like the fire insurance policy that doesn’t apply if you’re experimenting with flamethowers in your basement, we could also have certain terms under which data openness was intelligently done. A final benefit, too: it’d also give us in turn some really hard data on something that we’ve only been until this point discussing in the talking shop. What kind of businesses succeed when they open their data? What kind fail? What are the differences between the two? I’d love to see the actuarial tables on success in data openness, the same way we’d calculate life expectancy of someone who regularly exercises.

So, any takers?

9 Comments leave one →
  1. October 19, 2009 3:31 pm

    Great post! I enjoyed speaking on the panel with you – some important issues are starting to become more clear. I posted a reply to our most vocal ‘I want my data!’ customer here:

    On your post – some great thinking about an important issue. I definitely feel at times that we are being asked to jump off a cliff and expect a genie to pop out on the way down.

    Your geek insurance idea has promise – I like the thinking. THis quote caught me as one-sided though:

    “Interestingly enough, if it turns out that we are in fact right … geek insurance should be, in fact, enormously profitable as a business”

    But – what if we are wrong? Very simple in the extreme case – insure a number of companies who pay a little, then they all fail and you can’t pay out all of the policies. You would need some huge underwriting for big, reputable firms to try this – and these guys would be notoriously risk-averse in approaching a new insurance business. A Catch-22. Interested to hear others thoughts on the subject.

  2. Ken permalink
    October 19, 2009 5:05 pm

    Hi Tim,

    Your thoughts on Geek Insurance are pretty awesome and were fun to think about.

    I do agree with Ben, above, though: how can an insurer (or several insurers, and even re-insurers) reasonably account for risk which we don’t have the hrd data and past history on? Speculative insurance like this is definitely something that established insurance companies will shy away from (especially in this time of less- and un-certain economies).

    Furthermore, how do you (or the insurance companies) convince the other companies to buy the insurance? There seems to be some serious anti-selection risk to account for in that those companies which are not so worried about losing heir respectie shirts via this geek-risk are not going to be so interested (at least at first) in protecting themselves from the dangers, so the insurance companies will be losing out on the “good risks”.

    Another thing that comes to mind is the collection side…how will a company who has bought into geek insurance prove that their losses are as a result of this problem, and not mis-managemet, poor decisions, economic badness, simply not being the best choice in their sector, or other reasons? The potential long, drawn-out fights inherent in these sorts of disagreements can easily last long enough and cost enough in legal fees and lost time spent by involved executives with their “usual” work with the buiness that the business might fail before they’re even close to getting their geek insurance benefit. How can insurance companies make all payments swiftly but also righteously?

    I look forward to your thoughts.

  3. October 20, 2009 5:11 pm

    A big unknown is being able to model the risk of businesses losing (or gaining?) money from opening up their data. If you can do it right, you’ll make a ton of money. If you need an econ quant type to advise in such matters, I’ll be around.

  4. October 21, 2009 12:57 pm

    Even though it’s hard to calculate the risk (perhaps because there isn’t any, yet), I think geek insurance is a kool idea.

    In the long run the vector of history (everything networked, everybody more empowered, more participants contributing, companies turning into talent aggregation systems, abundant data) points toward paying deliberately for value wherever it appears, including places where it’s mashed up with other value. This involves some kind of micro-accounting (rather than micropayments), and the means for paying … somehow. Because the will to recognize value, and not just risk, is there.

    Right now we have large companies like Google hogging the spotlight by looking for second and third order “because effects” off hacks like Android and Google Earth, but stay stuck in the past when we realize that those second and third order effects involve (so far) making money the old-fashioned way: through advertising, which is still woefully inefficient, and works mostly by shifting waste off paper and airwaves and onto server farms, screen pixels and the rods and cones in the backs of our eyes. The advertiser may pay only for click-throughs and not for “impressions” made in the same campaign; but making fruitless impressions (noise, actually) is still a waste, still guesswork, still costly and inefficient, still a problem to be solved, and not only on the supply side. The demand side needs to provide feedback, make its intentions known, become involved in the economy in ways other than by paying for goods and whining in public when service goes bad.

    Geek insurance is bulk payment for aggregated value. Better yet, it recognizes the presence value in the first place. Not just risk of bad acting.

    Value-for-value, which by the way drives fund-raising for non-profits, as well as the familiar commercial economy, will prevail. Abundant data, especially held personally out in the Long Tail, will make calculating all value easier.

  5. November 2, 2009 6:08 pm

    It seems like the problem beginning to provide geek insurance and the problem of corporations resisting openness both stem back to the same issue of lack ‘o hard data.

    I’d love to see some basic research on the benefits of openness. I wonder if openness measurement can be done out of context – it seems that users would respond to openness quite differently depending on their perceptions of the corporation, trust, etc.

    Alternatively, it might be possible to avoid the underwriter risk of geek insurance by asking the individuals who want the openness in the first place to do the underwriting. Not sure exactly how this might work… a perhaps a $2M kickstarter project funded by the users? Some sort of crowd-sourced insurance policy held in union by a company’s entire customer-base?


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  2. ProjectVRM Blog » Event horizons
  3. Berkman Center Events & Webcasts » Blog Archive » You’re In Good Hands, With Geek Insurance «
  4. links for 2009-11-01 at Scott Porad

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