Monthly Archives: December 2007

Cleaning the slate

Here are some recent writings I had hoped to blog about but failed to:

Hunter R. Rawlings III, “Information, Knowledge, Authority, and Democracy

Michael Francis Booth, “Social Networks: Stop Designing Out The Fun

Jaron Lanier, “Long Live Closed-Source Software!

Steve Gillmor, “Overnight Success

Werner Vogels, “Eventually Consistent

And then there was this, in today’s NY Times Book Review, from Lee Siegel:

We have exhausted Romantic individualism, and we have twisted the uniquely individual, modernist escape from the self into “self-expression.” Expression is everywhere nowadays, but true art has grown indistinct and indefinable. We seem now to be living in a world where everyone has an artistic temperament — emotive and touchy, cold and self-obsessed — yet few people have the artistic gift. We are all outsiders, and we are all living in our own truth.

Top ten posts for 2007

Here are Rough Type’s ten most read posts during 2007 (total page views for the year in parentheses):

1. Adblock Plus: the nuclear plug-in (67,261)

2. The social graft (56,353)

3. Slutbot aces Turing Test* (46,909)

4. Avatars consume as much electricity as Brazilians (38,029)

5. The amorality of Web 2.0 (27,158)

6. Microsoft seeks mind-reading patent (24,896)

7. Google preparing to police web (19,135)

8. Steve’s devices (15,578)

9. IT doesn’t matter, part 1 (12,784)

10. Google, Apple and the future of personal computing (11,643)

“Amorality” was originally published in 2005. “Avatars” was originally published in 2006. The rest were published this year.

Merry Christmas and Best Wishes for 2008.

Illuminating cities: Cisco’s grand ambition

When I read the news this morning about Cisco’s plan “to network whole cities” …

Cisco Systems, the world’s biggest maker of data networking equipment, plans to launch a business group, based in Bangalore, India, that will wire new buildings and even entirely new cities with state-of-the-art networking technology … A city wired top-to-bottom with IP technology would be able to use it to manage infrastructure, such as traffic signals or surveillance cameras, while residents would be able to use it to access media content or control energy use in homes or office buildings, Cisco said.

… I couldn’t help but recall this passage about Thomas Edison in The Big Switch:

By the time he returned east in the fall [of 1878], he was consumed with the idea of supplying electricity over a network from a central generating station. His interest no longer lay in powering the drills of work crews in the wilderness, however. He wanted to illuminate entire cities.

Much of the discussion of the emerging new computing grid has been dominated by upstarts like Google and Amazon Web Services. We shouldn’t forget that there are other, very large and powerful businesses – Cisco, IBM, HP and the world’s big telecommunications carriers, to name a few – that have a big stake in the way the infrastructure of the new computing utility is deployed and used. Cisco’s move to network entire cities, illuminating them with optical fiber, gives a hint of the competitive battle on the horizon. 2008 will probably be the year when the big boys start to flex their muscles.

He with the most data wins

In The Google Enigma, I argue that the key to understanding Google’s business is complements theory. Literally everything that happens on the internet is a complement to the company’s main search and ad-serving businesses. Any net activity not only provides a potential new opportunity to distribute ads; it also provides a new opportunity to collect data, and it’s the richness of Google’s data that underpins its success in both search and ad-serving (which, in a virtuous cycle, bring in even more data).

In an illuminating post today, Brad Burnham explains why the collection of data is of such fundamental importance to Google’s competitive strategy:

In economic terms data has an increasing marginal utility [while] most physical objects have a decreasing marginal utility. When it is raining my first umbrella keeps me dry, a second may be handy if the first blows out, but a third is unlikely to be used. This is true of shirts, steaks, houses, of almost anything you can think of except data. Data has the opposite characteristic. Each incremental point of data adds value to the ones you all ready have. It is easy to see this in the context of an advertising network. If the ad network knows that a user is female it can show more relevant ads. But, If the ad network knows that female’s age, it can do even better, and data about location, household income, and recent web sites visited all add value to the existing data points, making it possible to show more and more relevant ads. Google’s services all benefit from additional data albeit in different ways.

More than that, Google’s core profit-making activity – distributing tailored ads – benefits from all the data collected by all its other services. In many cases, one can hypothesize, Google can afford to operate services at a loss simply because the data it collects about users, their preferences, and their patterns of activity is so valuable to its core business.

“So what does all this mean about the market for web services?” asks Burnham. “It means that we all need to begin to think about the degree to which Google’s enormous data asset will allow it to dominate this important sector.” Because data has an increasing marginal utility, having access to more data can provide, over the long run, a profound competitive advantage across a wide swath of web businesses – particularly those supported by advertising. That kind of dominance can end up putting a damper on entrepreneurship and innovation. “The source of the threat here,” Burnham explains, “is a data differential. Google has so much more data at their fingertips that even if a startup does a much better job leveraging data to deliver recommendations, Google could potentially provide a better value proposition to the end user with an inferior algorithm powered by more data, sourced from a broader range of services.”

Whether it’s increasing returns to scale, the network effect, or the increasing marginal utility of data, the great decentralized net unleashes strong forces that promote the centralization and consolidation of information, profits, and control. The big get bigger, and then they get bigger still.

Golden nuggets

On December 18, Google was granted a patent for generating “snippets” that summarize things, while on that very same day Amazon.com was granted a patent for collecting and displaying customer-supplied “blurbs” about things. Mike Masnick looks forward to the prospect of a “patent infringement lawsuit” in which the two net giants battle to define the boundaries between snippets and blurbs. What happens, for instance, when Google tries to snippetize a blurb? It could be the defining epistemological debate of our time.

Big Switch: now shipping

I’m pleased to report that Amazon.com has begun shipping The Big Switch. I’m not going to be so crassly mercantilistic as to suggest that you rush to purchase a copy or three, but I will say this: Imagine the joy on the faces of your loved ones when they find the book nestled under the tree on Tuesday morning.

Reality mining and your cell phone

If you’d like to know why companies like Google and Yahoo are so intent on gaining access to your mobile phone, take a look at the research on “reality mining” that’s being undertaken by an MIT team led by Sandy Pentland. In an interview with Technology Review, Pentland explains how modern cell phones provide a uniquely rich record not only of people’s locations but of their actions, social behavior, and even social roles:

Just look at a cell phone. It knows where you are, and this is obviously sort of useful. But the generalization is that maybe it can know lots of things about you. Take your Facebook friends as an example. The phone could know which ones you socialize with in person, which ones are your work friends, and which friends you’ve never seen in your life. That’s an interesting distinction, and reality mining can make it automatic. It’s about making the “dumb” information-technology infrastructure know something about your social life. All this sort-of Web 2.0 stuff is nice, but you have to type stuff in …

Today’s cell phones are on us all the time, and they come with hardware that can act as sensors for your environment. For instance, if Bluetooth is turned on, then the phone can see and be seen by other Bluetooth devices. You can start to make a record of the Bluetooth-enabled devices you encounter throughout the day. Then you can figure out, based on the frequency [with which] you encounter other people’s Bluetooth phones, what sort of relationship you have with them.

The iPhone also has an accelerometer that could tell if you are sitting and walking. You don’t have to explicitly type stuff in; it’s just measured. And all phones have built-in microphones that can be used to analyze your tone of voice, how long you talk, how often you interrupt people. These patterns can tell you what roles people play in groups: you can figure out who the leader is and who the followers are.

Pentland argues that this kind of machine awareness may have useful applications, such as tracking the spread of epidemics or even monitoring the “social health of communities.” But, as the interviewer points out, it “all gets very creepy very fast.” Replies Pentland:

That’s not a trivial thing. Do you really want your government to know about you to that level? It could stop SARS, but there’s a big trade-off there. You could make this a much more transparent world where that’s available to everybody. But we definitely need to talk about it and figure out a new deal for privacy – to use this data and not be abused.

Beyond the potential use of cell phone data by governments, though, it’s easy to see the vast commercial value of automatically harvesting a continuous stream of data on a person’s location, activities, relationships, and social roles and using it to personalize services and advertisements or, in the extreme, manipulate behavior for profit-making ends.

In a paper entitled “Inferring Social Network Structure Using Mobile Phone Data,” Pentland and two coauthors explain that one of the great benefits of the cell phone as a data mining tool is that it provides raw, unfiltered information, which ends up being more reliable than information “self-reported” by people. People’s reports on their own behavior are subject to a great deal of distortion due to memory lapses, cognitive biases, embarrassment, and other factors. Cell-phone reality mining, by contrast, provides “a new method for precise measurements of large-scale human behavior.” Our cell phone know us better than we know ourselves.

To illustrate the power of the technique, the authors conducted a reality mining experiment that involved “ninety-four subjects using mobile phones pre-installed with several pieces of software that record and send the researcher data on call logs, Bluetooth devices in proximity, cell tower IDs, application usage, and phone status. These subjects were observed via mobile phones over the course of nine months, representing over 330,000 person-hours of data (about 35 years worth of observations).” The data provided a remarkably intimate view of the subjects’ lives. The researchers were, for instance, able to “identify characteristic behavioral signatures of relationships that allowed us to accurately predict 95% of the reciprocated friendships in the study. Using these behavioral signatures we can predict, in turn, individual-level outcomes such as job satisfaction.”

Reality mining, the authors write, could revolutionize social research. It provides “a new approach to studying collaboration and communication within organizations – allowing the examination of the evolution of relationships over time. More dramatically, these methods allow for an inspection of the dynamics of macro networks that were heretofore unobservable. There is no technical reason why data cannot be collected from hundreds of millions of people throughout the course of their lives.” But it’s unlikely that the data will only be analyzed in the aggregate by academic researchers. The commercial value of reality mining is far too great to restrict the technique to the ivory tower. The resulting intrusions into personal privacy could well be dramatic, and as Pentland notes in the interview, we can’t assume that our interests will be protected: “The people making policies don’t know what is [technologically] possible, and they don’t necessarily make policies that are in our best interest … These capabilities are coming, but we have to come to a new deal. It doesn’t do any good to stick your head in the sand about it.”

NOTE: Technology Review provides a link to the paper, but it no longer seems to work. I found a copy in Google’s cache. And if you’d like to do a little reality mining yourself, you can download all the data from the researchers’ experiment here.