Contextual clothing for naked transparency

The other day I listened to a Spark (CBC Radio) interview with Larry Lessig about his New Republic essay Against Transparency, which begins:

We are not thinking critically enough about where and when transparency works, and where and when it may lead to confusion, or to worse. And I fear that the inevitable success of this movement–if pursued alone, without any sensitivity to the full complexity of the idea of perfect openness–will inspire not reform, but disgust. The “naked transparency movement,” as I will call it here, is not going to inspire change. It will simply push any faith in our political system over the cliff.

The essay was published in October 2009. In this interview from November, Prof. Lessig reflected on the reactions that it provoked. Although the delicious and bitly feedback now suggests that most people understood the essay to be a thoughtfully nuanced critique, there were evidently some early responders who read it as a retreat from openness and an assault on the Internet.

I’m glad I missed the essay when it first appeared. Reading it along with a cloud of feedback from readers and from the author amplifies one of the key points: We don’t really want naked transparency, we want transparency clothed in context.

The Net can be an engine for context assembly, a wonderful phrase I picked up years ago from Jack Ozzie and echoed in several essays. But it can also be a context destroyer.

In the interview, Lessig notes one example of context destruction. The article, which most people will read online, spans eleven pages, each of which wraps its nugget of “content” in layers of distraction. Some early negative comments, Lessig says, came from people who had clearly not read to the end.

Our increasingly compressed and fragmented attention can also be a context destroyer:

What about when the claims are neither true nor false? Or worse, when the claims actually require more than the 140 characters in a tweet?

This is the problem of attention-span. To understand something–an essay, an argument, a proof of innocence– requires a certain amount of attention. But on many issues, the average, or even rational, amount of attention given to understand many of these correlations, and their defamatory implications, is almost always less than the amount of time required. The result is a systemic misunderstanding–at least if the story is reported in a context, or in a manner, that does not neutralize such misunderstanding. The listing and correlating of data hardly qualifies as such a context. Understanding how and why some stories will be understood, or not understood, provides the key to grasping what is wrong with the tyranny of transparency.

Transparency is a necessary but not a sufficient condition. Recently my town’s crime data and council meetings have appeared online. But this remarkable transparency does not alone enable the sort of collaborative sense-making that we all rightly envision.

In the case of crime data, we require a context that includes historical trends, regional and national comparisons, guidance from government about how its local taxonomy relates to regional and national taxonomies, and reporting by newspapers and citizens.

In the case of city council meetings, we require a context that includes relevant state law and local code, and reporting by stakeholders, by newspapers, and by affected citizens.

To enable context assembly, we’ll need to organize the numeric and narrative data produced by the “naked transparency” movement in ways friendly to linking, aggregation, and discovery.

But these principles will need to be adopted more broadly than by governments alone. Everyone needs to understand the principles of linking, aggregation, and discovery, so that everyone can help create the context we crave.

Gov2.0 transparency: An enabler for collaborative sense-making

Recently my town has adopted two innovative web services that I’ve featured on my podcast: CrimeReports.com, which does what its name suggests, and Granicus.com, which delivers video of city council meetings along with synchronized documents.

You can see the Keene instance of CrimeReports here, and our Granicus instance here.

I’m delighted to finally become a user of these systems that I’ve advocated for, written about, and podcasted. I’m also eager to move forward. We’re still only scratching the surface of what Net-mediated democracy can and should become.

In the case of CrimeReports, the next step is clear: Publish the data. It’s nice to see pushpins on a map, but when you’re trying to answer questions — like “Are we having a crime wave?” — you need access to the information that drives the map. Greg Whisenant, the founder of CrimeReports.com, says he’d be happy to publish feeds. But so far the cities that hire him to do canned visualizations of crime data aren’t asking him to do so, because most people aren’t yet asking their city governments to provide source data. So a few intrepid hackers, like Ben Caulfield here in Keene, are reverse-engineering PDF files to get at the information. Check out Ben’s remixed police blotter — it’s awesome. Now imagine what Ben might accomplish if he hadn’t needed to move mountains to uncover the data.

In the case of Granicus, I’m reminded of this item from last year: Net-enhanced democracy: Amazing progress, solvable challenges. The gist of that item was that:

  • It’s amazing to be able to observe the processes of government.

  • It’s still a challenge to make sense of them.

  • Tools that we know how to build and use can help us meet that challenge.

Check out, for example, last week’s Keene city council meeting. Scroll down to an item labeled 2. Ordinance O-2009-21. In this clip, the council agrees to amend the city code for residential real estate tax exemptions. I wish I could link you directly to that portion of the video, which begins at 34:11, in the same way that I can link you to the associated document. But more broadly, I wish that a citizen who tunes in could understand — and help establish — the context for this amendment.

Here’s the new language:

Sec. 86-29 Residential real estate tax exemptions and credits

With regard to property tax exemptions, the city hereby adopts the provisions of RSA 72:37 (Blind); RSA 72:37-b (Disabled); RSA 72:38-b (Deaf or Severely Hearing Impaired); RSA 72:39-a (Elderly); RSA 72:62 (Solar); RSA 72:66 (Wind); and RSA 72:70 (Wood).

With regard to property tax credits, the city hereby adopts the provisions of RSA 72:28, II, (Optional Veterans’ tax credit); RSA 72:29-a , II, (Surviving Spouse); and RSA 72:35, I-a, (Optional Tax Credit for Service-Connected total disability).

In this case, I just happen to know a bit of this amendment’s backstory. Earlier this year I found out — only thanks to a serendipitous encounter with a city councilor at a social event — that my wood gasifier qualified me for an exemption. This was the first such exemption, and to my knowledge is still the only one granted.

If I hadn’t gone through that experience, though, the video clip and its associated document would mean nothing to me. There would be no way to make a connection between state law on the one hand, and a documented case study on the other.

On the next turn of the crank, I hope that services like Granicus will enable us to make those connections. Seeing the process of government in action is a great step forward. Now we need to be able to use links and annotations to help one another make sense of that process.

Understanding Wikipedia notability

Some fellow residents of my town have recently noticed, and pointed out to me, that I’m listed in Wikipedia as a notable inhabitant of Keene, NH. They’re more impressed than they should be. All forms of notability are subject to bias, but Internet notability is subject to a different kind of bias than most people realize.

For example, friends and family used to be impressed by the fact that I was the top result in Google for my first name — and then second to Jon Stewart for a long while, until I had to reboot my InfoWorld archive. Why? Just because I’ve projected a large surface area of searchable documents whose titles include the trigram jon.

An example of a far more notable person than me is Glenn Fine, who was in my grade in junior high school and is now Inspector General for the Department of Justice. You won’t find him anywhere near the top of a search for his first name because Inspectors General don’t (yet) project a large surface area of documents onto the web.

To place my newfound Wikipedia notability into a similar context, I wanted to show people how these lists of notable inhabitants are made. I figured the person who made the change is somebody who knows of my work, because I’ve written about it so much online, and who is inclined to edit Wikipedia, which correlates with an interest in my work.

I wanted to illustrate exactly who, when, and how, so I went to Wikipedia with the confident expectation that it would be easy to answer those questions.

Surprisingly, it wasn’t. I guess I haven’t really tried searching revision histories in Wikipedia before, but in this case and a few others I’ve tried lately, it seems quite difficult to pinpoint the author of a change.

For example, on Twitter I asked:

Wikipedia: “The term ‘Web 2.0’ was coined by Darcy DiNucci in 1999.” Added when, by whom? WikiBlame seems an ineffective way to find out.

@bazzargh replied: Robert Gehl. http://bit.ly/46r1a

Thanks. By the way, how’d you do that?

switch to 500 view in history, then rough bisection from oldest. Couple of minutes; used this a lot to find long-lived vandalism.

if older, I progressively back off 2..4..8… pages through this. In this case though, there was a clueful log message!

That’s pretty much what I’ve found myself doing when trying to track down changes, so I was glad to know it wasn’t just me. But this highlights an important point about transparency: It’s all relative.

One of the reasons we think of government as opaque is that while records may be notionally public, it takes time, effort, and skill to visit city hall, dig through them, and find what you’re looking for.

I have always regarded Wikipedia as an extreme counter-example. And that’s true. It is radically transparent. You can ultimately find out exactly how any statement in any article came to be. You may not be able to correlate the author’s pseudonym to a real-world identity, but you can evaluate that author’s corpus and reputation within the context of Wikipedia.

And yet, the ability to do this spelunking requires more time, effort, and skill than most people possess. Although I’m reluctant to deflate my status as a notable inhabitant of Keene, I wish it were easier for people who read that to also find out what it does — and doesn’t — mean.