According to a survey from the Cloud Security Alliance, an industry nonprofit with forty-eight thousand members, ten per cent of two hundred and seven officials at non-U.S. companies cancelled contracts with U.S. service providers after Edward Snowden’s disclosures about N.S.A. surveillance,

Starting to quantify the economic fallout of NSA surveillance for US-based cloud computing companies.

Facebook, Google and Microsoft’s Surveillance Cure-All: Transparency : The New Yorker

Playing Hardball

It seems like everywhere I look right now, people are playing hardball.  I.e., taking tough / extreme positions and sticking to them ferociously.

The showdown in congress over the budget and Obamacare is one case. The republicans have shown that they are willing to take it to the wall, and the Dems are calling their bluff.

The incredible story of the Silk Road’s demise is another.  This article detailing the story of Silk Road’s founder and his capture is a must read.  One way of looking at Ross Albricht’s (aka Dread Pirate Roberts) motivation was to give people a “taste of freedom” — i.e., it wasn’t about making money, but was simply about avoiding the power of the state.

Then, of course, there’s Snowden and the giant ripple of stories around him.  The latest to emerge is the story of (now shuttered) supposedly-secure email provider Lavabit’s resistance to the FBI’s request to decrypt all of their customers’ data.  They responded by supplying their 2,560 character SSL keys, printed out in 11 pages of 4pt type.  When the FBI complained and the judge ordered them to supply an electronic copy, Lavabit chose to shut down instead.

I suppose this is nothing new, but it also feels like maybe there’s something in common going on here.  A certain amount of pent up frustration, maybe.  Maybe we’re all watching too many reality shows and episodes of house of cards, because on one level this is all really exciting and fun (while being terrifying when you really think about it).  

But it seems like we’re seeing more and more absolute power, end runs, and dug-in fights.  The kid would say that this is just the beginning of the revolution. Not that I know what that feels like actually, but it does kind of feel that way.

The bottom line, Williams said, is that the internet is “a giant machine designed to give people what they want.” It’s not a utopia. It’s not magical. It’s simply an engine of convenience. Those who can tune that engine well — who solve basic human problems with greater speed and simplicity than those who came before — will profit immensely. Those who lose sight of basic human needs — who want to give people the next great idea — will have problems.

Open311 Data Prediction Challenge

As the federal government shuts down, there is no shortage of predictions about how it will shake out, when it will end, and who will take the blame.

Speaking of predictions (how’s that for a segue?), David Eaves (who writes a great blog for those who like the intersection of cities, governments and policy) just announced that the Open311 Prediction Data Competition is now live.  David and and the good folks at SeeClickFix are sponsoring this, as a follow on to a recent hackathon on the same topic.

For those not familiar: 311 is a semi-generic name for issue-reporting and question-asking/answering systems in cities (in Boston it’s called Citizens Connect).  In many cities, 311 is the city’s customer service desk, and was originally designed to simply make navigating the city bureaucracy easier. It was actually Bloomberg’s first major policy initiative in 2002.  

But, like a lot of data rich services, 311 has evolved to support secondary uses.  First, it’s essentially a citizen-sensor network, which, among other things, was credited with solving NYC’s Maple Syrup Smell mystery.

And second, it has potential as a predictive system.  There are all kinds of leading indicators hidden inside 311 data.  For example (and this one is logical and obvious, which still doesn’t mean it’s easy to see without data), Chicago used 311 data to predict when and where rodent problems would spike, based on 311 complaints about trash as the leading indicator.  This is just a tiny example of how big data sets like 311 can be used to make predictions that can help cities deploy their scarce resources more effectively.

So, if you’re into cities, data hacking and predictive analytics, check out the competition on Kaggle.

Related: Nate Silver is hiring stats- and prediction-savvy writers to focus on politics, sports and economics for FiveThirtyEight.com.   What a cool bunch of jobs those will be for the right people.

Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia

Here’s a plug for Anthony Townsend's new book, Smart Cities (which I haven’t read yet but have discussed with him throughout the making).  I can’t wait to get my hands on it, and suspect that it’ll be an enlightening read for anyone watching the “smart cities” / “civic hacking” space.

The angle I’m most interested in is this one, mentioned the Kirkus review:

Townsend especially focuses on the clash between industry’s cookie-cutter approach to smart-city building and the quirky local approach of civic hackers pushing decentralized and democratic alternatives. The author, who has been personally involved in creating free public Wi-Fi, sympathizes with young people, who have been weaned on the mobile Web and social media and are experimenting with human-centered designs based on grass-roots smart-city technologies—e.g., mobile apps, community wireless networks and open-source microcontrollers. Townsend covers topics from mass urban surveillance to how the poor can benefit from smart technologies, and he offers his own principles for creating human-centered smart cities.

Authoritative, information-packed must-read for urban policymakers.

Congrats Anthony on getting this up and out!

T-Corps and the Community IPO

Janelle Orsi has an article in Shareable that should be of interest for anyone following the “sharing economy” (or “peer economy”, or whatever you want to call it).

It tackles one of the most difficult and interesting problems facing sharing economy platforms: the relationship (technically speaking, i.e., the business relationship) between the companies operating the platform (e.g., Lyft or Airbnb), the “sellers” on the platform, and the buyers or users.

The nuances of this relationship are the source of many legal and regulatory head scratchers, most notably two recent suits against Lyft and Uber by their drivers, which allege that Lyft and Uber are really more like direct employers and less like information platforms or technology service providers.  This distinction is a really really really important one, both in terms of labor law and professional regulation (in transportation and all other sectors).

The solution that Orsi suggests is that sharing economy platforms should be organized as “T-Corps”.  She cleverly uses this term, which is the official IRS classification for co-ops.

She argues that this classification is not only more aligned with the community’s interests (i.e., the major stakeholders are equal owners), but it also avoids all of the messy legal and regulatory issues that are making things hard for many platforms in the space.

Finally, she suggests a path for doing a “Community IPO”, i.e., selling a sharing economy platform to its users (both on the buy and sell side):

Could or would each of the 2.1 million registered users of Airbnb come up with about $120 per year to complete the buy-out of a $2.5 billion dollar company in 10 years? Maybe. The number of users is growing rapidly, which would reduce the buy-in cost for each user. 

This is a really interesting conversation to be having, and fits right along side the discussion of the role of the B-Corp in the space.

It seems fair to say that the founders of collaborative / peer-driven companies like Airbnb, Sidecar, Meetup, Etsy and Kickstarter are idealistic, change-the-world types as much as they are businesspeople. And that there will continue to be an appetite for alternative investment arrangements which fit these new models well.

A natural question is whether this approach is actually / practically compatible with traditional venture investment, especially with regards to when & how such a community IPO would take place (such that it was affordable by the community and also delivered an appropriate return for that risk capital). That’s the billion dollar question (if you will).

Being an Urban Planner Just Got Awesome

I’m here today at the Adaptive Metropolis conference at UC Berkeley, organized by ReBar.  Which, as I suspected it would be, is awesome.  The premise of the conference is how cities, and the way we plan, manage and engage with them, is changing — an in particular, how bottom-up, diy, adaptive, responsive, agile, and user-generated approaches to city making are exploding in their scale and impact.

What I realized today — which I suppose I have known for a little while now — is that now is an incredible time to be an urban planner. (And by urban planner, I suppose I really mean “urbanist”).

This is a gross generalization, but in the past, the options for urban planners were pretty limited.  Go work for a city (when I was in school I interned at San Jose redevelopment agency, and was wasn’t accepted for a job a the Santa Cruz planning department — a job I would have hated anyway had I gotten it), go work for a private sector planning firm, or maybe for a commercial real estate developer.

Those are all fine options — but my experience, at least, was that up close, all of those options felt a bit dry, and didn’t live up to the hopes and interests that brought me to the space.  And it certainly wasn’t clear to me what my other options were.

Contrast that to now, and there is no shortage of amazing and really interesting jobs for folks who understand how cities work.  For instance, ReBar is a new kind of planning firm, that’s activist and artist at its core.  

Most interesting of all (to me at least) are the businesses and jobs that blend urbanism, data and technology.  Governments are creating “chief innovation officer” and “chief data officer” positions left and right.  Urban analytics and data visualization is a rapidly growing and super interesting field.  Nonprofits like Code for America, OpenPlans and MySociety are doing awesome work at the intersection of cities and technology.  And innumerable startup businesses are touching on urban issues (just to name a few: airbnb, lyft, sidecar, relayrides, getaround, honest buildings, neighborland, nextdoor, citymapper, coUrbanize).

Put another way, cities have always been interesting.  Now they’re sexy.

The Adaptive Metropolis

I’m writing this from a plane en route to Berkeley for what should be an awesome conference: Adaptive Metropolis: User Generated Urbanism.  Among the organizers is my favorite DIY city-making collective: ReBar.

Back in 2005, ReBar did something amazing.  They pulled up to a San Francisco parking space and put in a few quarters.  But instead of parking a car there, they rolled out sod, set up a park bench, and created a tiny, temporary public park.  They called it Park(ing).  Check it out:

The point, of course, is that charging cars $1 or $2 / hr to be there is a pretty lousy use of public space.  And that becomes really obvious when we experiment with using that space for other, more awesome things.

That stunt, and the video about it, ended up sparking something of a mini movement.  Later that year, there was an entire day in SF devoted to Park(ing).  After that, more cities joined in.  Back at OpenPlans, we helped organize NYC’s Park(ing) days in 2008 and 2009.  In 2011 (the last year for which they kept stats, since it got so big), Park(ing) Day was celebrated at 975 mini-parks, in 162 cities, in 35 countries, on 6 continents.  

Beyond all that, the city of San Francisco now has an official “Parklet” program, which facilitates the citizen-led transformation of under-utilized public spaces into mini-parks, including this nifty Parklet-o-matic infographic:

image

This is “user-generated urbanism” at its best.  And I would encourage everyone to take part in next year’s Park(ing) day, wherever you are (unfortunately, you’ll have to wait a whole year until Sept 2014).  But the really interesting thing to note is the way the city (eventually) embraced this, and made space for it in their policies.

Back to 2007: at the same time, NYC was experimenting with “hacking public spaces”.  That year, they began a massive program to do low cost experiments in public space transformation.  The first one simply painted over an empty parking lot in DUMBO.  Over the next few years, major street redesigns in Times Square, Madison Square, Union Square, the Meatpacking District, and elsewhere all over the city were started with paint and planters, not with jackhammers and concrete.

By doing these projects at super low cost, with cheap (but nice enough) materials, and by leaving the option open to change their minds if things didn’t work out, NYC DOT unleashed a torrent of public space innovation across the city.  I’m not sure any established city has ever seen the level of micro-scale street redesign that NYC saw from 2007-2012.  And the process of doing low-cost experiments, then collecting data and iterating was a breath of fresh air.

That’s what you might call “agile urbanism”.

So, we’ve got “user-generated urbanism” and “agile urbanism”.  That sounds a lot like how we describe the evolution of the internet and the software development process, respectively.  It might just be my internet centrism showing through, but it makes sense to me, and I see it continuing.

Now, in 2013, we’re seeing a new trend in our cities, which we might call “peer to peer urbanism”.  

Web- and mobile-enabled peer networks are bringing “web 2.0” models of collaboration and commerce (think: Ebay and everything that followed) to every part of the city.  You can now share or rent your apartment, your car, a seat in your car, your stuff, or even your dog.  You can also crowd-fund public works projects, shop at virtual farmers’ markets, and start to count on new forms of peer-to-peer humanitarian aid.

This latest wave has caused more than its share of problems as cities grapple with the implications of the rapid expansion of peer-to-peer everything.  It challenges fundamental notions of professionalism and trust, the same way Ebay did in 2001.  For example, if I use SideCar and give someone a ride, am I a taxi driver? (the state of California just decided I’m not, but it took a while to figure that out).  Does renting out my apartment on Airbnb turn it into a hotel? (New York state thinks it does).

As this continues, we have an opportunity to re-think how we regulate city activities for the public interest.  I think the big opportunity is to harness the data streaming out of all of these activities and use it to enable a more permissive, but more accountable, “2.0” regulatory regime.

So, anyway, maybe this is what we mean by the adaptive metropolis.  The city that changes, changes fast, and keeps on changing in response to that change.  Change is good.

Systems to Cover Up Symptoms

Cescalouise and I have started using Wunderlist to keep track of shared to-dos (bills to pay, stuff to buy, etc).  I’ve been a user of Wunderlist for a number of years now and have written about it before.

The shared lists in Wunderlist actually seem to be working for us.   Whenever she adds or updates an item, I get a notification, and vice versa.  This is helpful, for me at least, and can hopefully help her get less annoyed at me for forgetting things :)

I mentioned yesterday that I thought it was working pretty well, and her response was: “we’ll see.  systems cover up symptoms.”  Which is a fair point, I think.  It’s easy for me to waste time fiddling around with a perfect system and feel like I’m making a lot of progress, while not actually changing the underlying thing (in this case, not paying attention to things as much as I should).

In this particular case I am hopeful that the system will help solve the root problem, but I guess we’ll have to wait and see.