The Myth of the ‘Transparent Society’

I’ve always been uncomfortable with the idea of David Brin’s The Transparent Society, because it provides an over-simplified version of a very complex problem. While it appeals to our general obsession with finding simple solutions, it fails to actually address a very real problem. Rather than a revolutionary or provocative idea, it’s in fact an argument for maintaining the status quo.

I’ve never quite been able to parse it out properly, but was pleased to see that Bruce Schneier (Chuck Norris of the security industry) addressed Brin’s argument this week for Wired:

When I write and speak about privacy, I am regularly confronted with the mutual disclosure argument. Explained in books like David Brin’s The Transparent Society, the argument goes something like this: In a world of ubiquitous surveillance, you’ll know all about me, but I will also know all about you. The government will be watching us, but we’ll also be watching the government. This is different than before, but it’s not automatically worse. And because I know your secrets, you can’t use my secrets as a weapon against me.

This might not be everybody’s idea of utopia — and it certainly doesn’t address the inherent value of privacy — but this theory has a glossy appeal, and could easily be mistaken for a way out of the problem of technology’s continuing erosion of privacy. Except it doesn’t work, because it ignores the crucial dissimilarity of power.

Schneier’s most recent book is Beyond Fear (which I’ve not yet had a chance to read) and also has an excellent monthly mailing list (that I read all the time) that covers topics like privacy and security. He is a gifted writer who can explain both the subtleties of the privacy debate as well as the complexities of security in terms that are informative for technologists and interesting for anyone else.

Sunday, March 9, 2008 | privacy  

Visualizing Data Book CoverVisualizing Data is my 2007 book about computational information design. It covers the path from raw data to how we understand it, detailing how to begin with a set of numbers and produce images or software that lets you view and interact with information. When first published, it was the only book(s) for people who wanted to learn how to actually build a data visualization in code.

The text was published by O’Reilly in December 2007 and can be found at Amazon and elsewhere. Amazon also has an edition for the Kindle, for people who aren’t into the dead tree thing. (Proceeds from Amazon links found on this page are used to pay my web hosting bill.)

Examples for the book can be found here.

The book covers ideas found in my Ph.D. dissertation, which is the basis for Chapter 1. The next chapter is an extremely brief introduction to Processing, which is used for the examples. Next is (chapter 3) is a simple mapping project to place data points on a map of the United States. Of course, the idea is not that lots of people want to visualize data for each of 50 states. Instead, it’s a jumping off point for learning how to lay out data spatially.

The chapters that follow cover six more projects, such as salary vs. performance (Chapter 5), zipdecode (Chapter 6), followed by more advanced topics dealing with trees, treemaps, hierarchies, and recursion (Chapter 7), plus graphs and networks (Chapter 8).

This site is used for follow-up code and writing about related topics.