First published May 20, 2003 on the “Networks, Economics, and Culture” mailing list.

Grid Computing is, according to the Grid Information Centre a way to “…enable the sharing, selection, and aggregation of a wide variety of geographically distributed computational resources.” It is, in other words, an attempt to make Sun’s famous pronouncement “The Network Is The Computer” an even more workable proposition. (It is also an instantiation of several of the patterns of decentralization that used to travel together under the name peer-to-peer.)

Despite the potential generality of the Grid, most of the public pronouncements are focusing on the use of Grids for supercomputing. IBM defines it more narrowly: Grid Computing is “… applying resources from many computers in a network-at the same time-to a single problem” , and the MIT Technology Review equated Grid technology with supercomputing on tap when it named Grids one of “Ten Technologies That Will Change the World.”

This view is wrong. Supercomputing on tap won’t live up to to this change-the-world billing, because computation isn’t a terribly important part of what people do with computers. This is a lesson we learned with PCs, and it looks like we will be relearning it with Grids.

The Misnomer of the Personal Computer

Though most computational power lives on the world’s hundreds of millions of PCs, most PCs are not used for computation most of the time. There are two reasons for this, both of which are bad news for predictions of a supercomputing revolution. The first is simply that most people are not sitting at their computer for most hours of the day. The second is because even when users are at their computers, they are not tackling computationally hard problems, and especially not ones that require batch processing — submit question today, get answer tomorrow (or next week.) Indeed, whenever users encounter anything that feels even marginally like batch processing — a spreadsheet that takes seconds to sort, a Photoshop file that takes a minute to render — they begin hankering for a new PC, because they care about peak performance, not total number of cycles available over time. The only time the average PC performs any challenging calculations is rendering the visual for The Sims or WarCraft.

Therein lies the conundrum of the Grid-as-supercomputer: the oversupply of cycles the Grid relies on exists because of a lack of demand. PCs are used as many things — file cabinets and communications terminals and typewriters and photo albums and jukeboxes — before they are used as literal computers. If most users had batch applications they were willing to wait for even as long as overnight, the first place they would look for spare cycles would be on their own machines, not on some remote distributed supercomputer. Simply running their own PC round the clock would offer a 10x to 20x improvement, using hardware they already own.

If users needed Grid-like power, the Grid itself wouldn’t work, because the unused cycles the Grid is going to aggregate wouldn’t exist. Of all the patterns supported by decentralization, from file-sharing to real-time collaboration to supercomputing, supercomputing is the least general.

The Parallel with Push 

There is a parallel between Grids and Push technology, that glamorous flameout of the mid-90s. The idea behind Push, exemplified by the data-displaying screensaver Pointcast, was that because users suffered from limited bandwidth and periodic disconnection (e.g. laptops on airplanes), they would sign up to have data pushed to them, which they could then experience at their leisure. This, we were told, would create a revolution in the way people use the internet. (This notion reached its apotheosis in a Wired magazine cover story, “Push!”, whose subtitle read “Kiss your browser goodbye: The radical future of media beyond the Web”.)

As it turned out, user’s response to poor connectivity was to agitate for better connectivity, because like CPUs, users want bandwidth that provides good peak performance, even if that means most of it gets “wasted.” Shortly after the Wired cover, it was PointCast we kissed goodbye.

Push’s collapse was made all the more spectacular because of its name. The label Push seemed to suggest a sweeping new pattern of great importance. Had the technology been given a duller but more descriptive name, like “forward caching,” it would have generated much less interest in the beginning, but might also not have been so prematurely consigned to the list of failed technologies.

Forward caching is in fact a key part of some applications. In particular, companies building decentralized groupware like Groove , Kubi Software, and Shinkuro, all of whom use forward caching of shared files to overcome the difficulties caused by limited bandwidth and partially disconnected nodes, just the issues Push was supposed to address. By pushing the name Push, the Pointcast’s of the world made it harder to see that though forward caching was not universally important, it was still valuable in some areas.

Distributed Batch Processing

So it is with Grids. The evocative name suggests that computation is so critical that we must have a global infrastructure to provide all those cycles we’ll be needing next time our boss asks us to model an earthquake, or we have to help our parents crack a cryptographic key. The broadness of the term masks the specialised nature of the technology, which should probably be called “distributed batch processing.”

Like forward caching, distributed batch processing is useful in a handful of areas. The SETI@Home project runs on distributed batch processing, as does the distributed.net cryptographic key-breaking tool. The sequencing of the SARS virus happened using distributed batch processing. Distributed batch processing could be useful in fields like game theory, where scenarios could be exhaustively tested on the cheap, or animated film, where small studios or even individuals could afford acces to Pixar-like render farms.

Distributed batch processing is real progress for people who need supercomputing power, but having supercomputing on tap doesn’t make you a researcher anymore than having surfboard wax on tap would make you a surfer. Indeed, to the consternation of chip manufacturers (and the delight of researchers who want cheap cycles), people don’t even have much real use for the computational power on the machines they buy today.

History has not been kind to business predictions based on an undersupply of cycles, and the business case for selling access to supercomputing on tap is grim. Assuming that a $750 machine with a 2 gigahertz chip can be used for 3 years, commodity compute time now costs roughly a penny a gigahertz/hour. If Grid access costs more than a penny a ghz/hr, building a dedicated supercomputer starts to be an economical proposition, relative to buying cycles from a Grid. (And of course Moore’s Law sees to it that these economics get more adverse every year.)

Most of the for-profit work on supercomputing Grids will be in helping businesses harness their employees’ PCs so that the CFO can close the books quickly — cheap, one-shot contracts, in other words, that mostly displace money from the purchase of new servers. The cost savings for the average business will be nice of course, but saving money by deferring server purchases is hardly a revolution.

People Matter More Than Machines

We have historically overestimated the value of connecting machines to one another, and underestimated the value of connecting people, and by emphasizing supercomputing on tap, the proponents of Grids are making that classic mistake anew. During the last great age of batch processing, the ARPAnet’s designers imagined that the nascent network would be useful as a way of providing researchers access to batch processing at remote locations. This was wrong, for two reasons: first, it turned out researchers were far more interested in getting their own institutions to buy computers they could use locally than in using remote batch processing, and Moore’s Law made that possible as time passed. Next, once email was ported to the network, it became a far more important part of the ARPAnet backbone than batch processing was. Then as now, access to computing power mattered less to the average network user than access to one another.

Though Sun was incredibly prescient in declaring “The Network is the Computer” at a time when PCs didn’t even ship with built-in modems, the phrase is false in some important ways — a network is a different kind of thing than a computer. As long ago as 1968, J.R. Licklider predicted that computers would one day be more important as devices of communication than of computation, a prediction that came true when email overtook the spreadsheet as the core application driving PC purchases.

What was true of the individual PC is true of the network as well — changes in computational power are nice, but changes in communications power are profound. As we learned with Push, an intriguing name is no substitute for general usefulness. Networks are most important as ways of linking unevenly distributed resources — I know something you don’t know; you have something I don’t have — and Grid technology will achieve general importance to the degree that it supports those kinds of patterns. The network applications that let us communicate and share in heterogeneous environments, from email to Kazaa, are far more important uses of the network than making all the underlying computers behave as a single supercomputer.

First published March 28, 2003 on the “Networks, Economics, and Culture” mailing list. 

“The future always comes too fast and in the wrong order.” — Alvin Toffler

For most of the past year, on many US airlines, those phones inserted into the middle seat have borne a label reading “Service Disconnected.” Those labels tell a simple story — people don’t like to make $40 phone calls. They tell a more complicated one as well, about the economics of connectivity and about two competing visions for access to our various networks. One of these visions is the one everyone wants — ubiquitous and convenient — and the other vision is the one we get — spotty and cobbled together. 

Call the first network “perma-net,” a world where connectivity is like air, where anyone can send or receive data anytime anywhere. Call the second network “nearly-net”, an archipelago of connectivity in an ocean of disconnection. Everyone wants permanet — the providers want to provide it, the customers want to use it, and every few years, someone announces that they are going to build some version of it. The lesson of in-flight phones is that nearlynet is better aligned with the technological, economic, and social forces that help networks actually get built. The most illustrative failure of permanet is the airphone. The most spectacular was Iridium. The most expensive will be 3G. 

“I’m (Not) Calling From 35,000 Feet”

The airphone business model was obvious — the business traveler needs to stay in contact with the home office, with the next meeting, with the potential customer. When 5 hours of the day disappears on a flight, value is lost, and business customers, the airlines reasoned, would pay a premium to recapture that value.

The airlines knew, of course, that the required investment would make in-flight calls expensive at first, but they had two forces on their side. The first was a captive audience — when a plane was in the air, they had a monopoly on communication with the outside world. The second was that, as use increased, they would pay off the initial investment, and could start lowering the cost of making a call, further increasing use.

What they hadn’t factored in was the zone of connectivity between the runway and the gate, where potential airphone users were physically captive, but where their cell phones still worked. The time spent between the gate and the runway can account for a fifth of even long domestic flights, and since that is when flight delays tend to appear, it is a disproportionately valuable time in which to make calls.

This was their first miscalculation. The other was that they didn’t know that competitive pressures in the cell phone market would drive the price of cellular service down so fast that the airphone would become more expensive, in relative terms, after it launched. 

The negative feedback loop created by this pair of miscalculations marginalized the airphone business. Since price displaces usage, every increase in the availability on cell phones or reduction in the cost of a cellular call meant that some potential users of the airphone would opt out. As users opted out, the projected revenues shrank. This in turn postponed the date at which the original investment in the airphone system could be paid back. The delay in paying back the investment delayed the date at which the cost of a call could be reduced, making the airphone an even less attractive offer as the number of cell phones increased and prices shrank still further.

66 Tears

This is the general pattern of the defeat of permanet by nearlynet. In the context of any given system, permanet is the pattern that makes communication ubiquitous. For a plane ride, the airphone is permanet, always available but always expensive, while the cell phone is nearlynet, only intermittently connected but cheap and under the user’s control. 

The characteristics of the permanet scenario — big upfront investment by few enough companies that they get something like monopoly pricing power — is usually justified by the assumption that users will accept nothing less than total connectivity, and will pay a significant premium to get it. This may be true in scenarios where there is no alternative, but in scenarios where users can displace even some use from high- to low-priced communications tools, they will.

This marginal displacement matters because a permanet network doesn’t have to be unused to fail. It simply has to be underused enough to be unprofitable. Builders of large networks typically overestimate the degree to which high cost deflects use, and underestimate the number of alternatives users have in the ways they communicate. And in the really long haul, the inability to pay off the initial investment in a timely fashion stifles later investment in upgrading the network.

This was the pattern of Iridium, Motorola’s famously disastrous network of 66 satellites that would allow the owner of an Iridium phone to make a phone call from literally anywhere in the world. This was permanet on a global scale. Building and launching the satellites cost billions of dollars, the handsets cost hundreds, the service cost dollars a minute, all so the busy executive could make a call from the veldt.

Unfortunately, busy executives don’t work in the veldt. They work in Pasedena, or Manchester, or Caracas. This is the SUV pattern — most SUV ads feature empty mountain roads but most actual SUVs are stuck in traffic. Iridium was a bet on a single phone that could be used anywhere, but its high cost eroded any reason to use an Iridium phone in most of the perfectly prosaic places phone calls actually get made.

3G: Going, Going, Gone

The biggest and most expensive permanet effort right now is wireless data services, principally 3G, the so-called 3rd generation wireless service, and GPRS, the General Packet Radio Service (though the two services are frequently lumped together under the 3G label.) 3G data services provide always on connections and much higher data rates to mobile devices than the widely deployed GSM networks do, and the wireless carriers have spent tens of billions worldwide to own and operate such services. Because 3G requires licensed spectrum, the artificial scarcity created by treating the airwaves like physical property guarantees limited competition among 3G providers. 

The idea here is that users want to be able to access data any time anywhere. This is of course true in the abstract, but there are two caveats: the first is that they do not want it at any cost, and the second and more worrying one is that if they won’t use 3G in environments where they have other ways of connecting more cheaply.

The nearlynet to 3G’s permanet is Wifi (and, to a lesser extent, flat-rate priced services like email on the Blackberry.) 3G partisans will tell you that there is no competition between 3G and Wifi, because the services do different things, but of course that is exactly the problem. If they did the same thing, the costs and use patterns would also be similar. It’s precisely the ways in which Wifi differs from 3G that makes it so damaging. 

The 3G model is based on two permanetish assumptions — one, that users have an unlimited demand for data while traveling, and two, that once they get used to using data on their phone, they will use it everywhere. Both assumptions are wrong.

First, users don’t have an unlimited demand for data while traveling, just as they didn’t have an unlimited demand for talking on the phone while flying. While the mobile industry has been telling us for years that internet-accessible cellphones will soon outnumber PCs, they fail to note that for internet use, measured in either hours or megabytes, the PC dwarfs the phone as a tool. Furthermore, in the cases where users do demonstrate high demand for mobile data services by getting 3G cards for their laptops, the network operators have been forced to raise their prices, the opposite of the strategy that would drive use. Charging more for laptop use makes 3G worse relative to Wifi, whose prices are constantly falling (access points and Wifi cards are now both around $60.)

The second problem is that 3G services don’t just have the wrong prices, they have the wrong kind of prices — metered — while Wifi is flat-rate. Metered data gives the user an incentive to wait out the cab ride or commute and save their data intensive applications for home or office, where sending or receiving large files creates no additional cost. The more data intensive a users needs are, the greater the price advantage of Wifi, and the greater their incentive to buy Wifi equipment. At current prices, a user can buy a Wifi access point for the cost of receiving a few PDF files over a 3G network, and the access point, once paid for, will allow for unlimited use at much higher speeds. 

The Vicious Circle 

In airline terms, 3G is like the airphone, an expensive bet that users in transit, captive to their 3G provider, will be happy to pay a premium for data communications. Wifi is like the cell phone, only useful at either end of travel, but providing better connectivity at a fraction of the price. This matches the negative feedback loop of the airphone — the cheaper Wifi gets, both in real dollars and in comparison to 3G, the greater the displacement away from 3G, the longer it will take to pay back the hardware investment (and, in countries that auctioned 3G licenses, the stupefying purchase price), and the later the day the operators can lower their prices.

More worryingly for the operators, the hardware manufacturers are only now starting to toy with Wifi in mobile devices. While the picture phone is a huge success as a data capture device, the most common use is “Take picture. Show friends. Delete.” Only a fraction of the photos that are taken are sent over 3G now, and if the device manufacturers start making either digital cameras or picture phones with Wifi, the willingness to save a picture for free upload later will increase. 

Not all permanets end in total failure, of course. Unlike Iridium, 3G is seeing some use, and that use will grow. The displacement of use to cheaper means of connecting, however, means that 3G will not grow as fast as predicted, raising the risk of being too little used to be profitable.

Partial Results from Partial Implementation

In any given situation, the builders of permanet and nearlynet both intend to give the customers what they want, but since what customers want is good cheap service, it is usually impossible to get there right away. Permanet and nearlynet are alternate strategies for evolving over time.

The permanet strategy is to start with a service that is good but expensive, and to make it cheaper. The nearlynet strategy is to start with a service that is lousy but cheap, and to make it better. The permanet strategy assumes that quality is the key driver of a new service, and permanet has the advantage of being good at every iteration. Nearlynet assumes that cheapness is the essential characteristic, and that users will forgo quality for a sufficient break in price.

What the permanet people have going for them is that good vs. lousy is not a hard choice to make, and if things stayed that way, permanet would win every time. What they have going against them, however, is incentive. The operator of a cheap but lousy service has more incentive to improve quality than the operator of a good but expensive service does to cut prices. And incremental improvements to quality can produce disproportionate returns on investment when a cheap but lousy service becomes cheap but adequate. The good enough is the enemy of the good, giving an edge over time to systems that produce partial results when partially implemented. 

Permanet is as Permanet Does

The reason the nearlynet strategy is so effective is that coverage over cost is often an exponential curve — as the coverage you want rises, the cost rises far faster. It’s easier to connect homes and offices than roads and streets, easier to connect cities than suburbs, suburbs than rural areas, and so forth. Thus permanet as a technological condition is tough to get to, since it involves biting off a whole problem at once. Permanet as a personal condition, however, is a different story. From the user’s point of view, a kind of permanet exists when they can get to the internet whenever they like.

For many people in the laptop tribe, permanet is almost a reality now, with home and office wired, and any hotel or conference they attend Wifi- or ethernet-enabled, at speeds that far outstrip 3G. And since these are the people who reliably adopt new technology first, their ability to send a spreadsheet or receive a web page faster and at no incremental cost erodes the early use the 3G operators imagined building their data services on. 

In fact, for many business people who are the logical customers for 3G data services, there is only one environment where there is significant long-term disconnection from the network: on an airplane. As with the airphone itself, the sky may be a connection-poor environment for some time to come, not because it isn’t possible to connect it, but because the environment on the plane isn’t nearly nearlynet enough, which is to say it is not amenable to inexpensive and partial solutions. The lesson of nearlynet is that connectivity is rarely an all or nothing proposition, much as would-be monopolists might like it to be. Instead, small improvements in connectivity can generally be accomplished at much less cost than large improvements, and so we continue growing towards permanet one nearlynet at a time.

First published February 8, 2003 on the “Networks, Economics, and Culture” mailing list.

Version 1.1: Changed 02/10/03 to point to the updated “Blogging Ecosystem” project, and to Jason Kottke’s work using Technorati.com data. Added addendum pointing to David Sifry’s “Technorati Interesting Newcomers” list, which is in part a response to this article.

A persistent theme among people writing about the social aspects of weblogging is to note (and usually lament) the rise of an A-list, a small set of webloggers who account for a majority of the traffic in the weblog world. This complaint follows a common pattern we’ve seen with MUDs, BBSes, and online communities like Echo and the WELL. A new social system starts, and seems delightfully free of the elitism and cliquishness of the existing systems. Then, as the new system grows, problems of scale set in. Not everyone can participate in every conversation. Not everyone gets to be heard. Some core group seems more connected than the rest of us, and so on.

Prior to recent theoretical work on social networks, the usual explanations invoked individual behaviors: some members of the community had sold out, the spirit of the early days was being diluted by the newcomers, et cetera. We now know that these explanations are wrong, or at least beside the point. What matters is this: Diversity plus freedom of choice creates inequality, and the greater the diversity, the more extreme the inequality.

In systems where many people are free to choose between many options, a small subset of the whole will get a disproportionate amount of traffic (or attention, or income), even if no members of the system actively work towards such an outcome. This has nothing to do with moral weakness, selling out, or any other psychological explanation. The very act of choosing, spread widely enough and freely enough, creates a power law distribution.

A Predictable Imbalance #

Power law distributions, the shape that has spawned a number of catch-phrases like the 80/20 Rule and the Winner-Take-All Society, are finally being understood clearly enough to be useful. For much of the last century, investigators have been finding power law distributions in human systems. The economist Vilfredo Pareto observed that wealth follows a “predictable imbalance”, with 20% of the population holding 80% of the wealth. The linguist George Zipf observed that word frequency falls in a power law pattern, with a small number of high frequency words (I, of, the), a moderate number of common words (book, cat cup), and a huge number of low frequency words (peripatetic, hypognathous). Jacob Nielsen observed power law distributions in web site page views, and so on.

We are all so used to bell curve distributions that power law distributions can seem odd. The shape of Figure #1, several hundred blogs ranked by number of inbound links, is roughly a power law distribution. Of the 433 listed blogs, the top two sites accounted for fully 5% of the inbound links between them. (They were InstaPundit and Andrew Sullivan, unsurprisingly.) The top dozen (less than 3% of the total) accounted for 20% of the inbound links, and the top 50 blogs (not quite 12%) accounted for 50% of such links.

Figure #1: 433 weblogs arranged in rank order by number of inbound links.  The data is drawn from N.Z Bear’s 2002 work on the blogosphere ecosystem. The current version of this project can now be found at http://www.myelin.co.nz/ecosystem/.

The inbound link data is just an example: power law distributions are ubiquitous. Yahoo Groups mailing lists ranked by subscribers is a power law distribution. (Figure #2) LiveJournal users ranked by friends is a power law. (Figure #3) Jason Kottke has graphed the power law distribution of Technorati link data. The traffic to this article will be a power law, with a tiny percentage of the sites sending most of the traffic. If you run a website with more than a couple dozen pages, pick any time period where the traffic amounted to at least 1000 page views, and you will find that both the page views themselves and the traffic from the referring sites will follow power laws.

Figure #2: All mailing lists in the Yahoo Groups Television category, ranked by number of subscribers (Data from September 2002.) Figure #3: LiveJournal users ranked by number of friends listed. (Data from March 2002)

Rank Hath Its Privileges #

The basic shape is simple – in any system sorted by rank, the value for the Nth position will be 1/N. For whatever is being ranked — income, links, traffic — the value of second place will be half that of first place, and tenth place will be one-tenth of first place. (There are other, more complex formulae that make the slope more or less extreme, but they all relate to this curve.) We’ve seen this shape in many systems. What’ve we’ve been lacking, until recently, is a theory to go with these observed patterns.

Now, thanks to a series of breakthroughs in network theory by researchers like Albert-Laszlo Barabasi, Duncan Watts, and Bernardo Huberman among others, breakthroughs being described in books like Linked, Six Degrees, and The Laws of the Web, we know that power law distributions tend to arise in social systems where many people express their preferences among many options. We also know that as the number of options rise, the curve becomes more extreme. This is a counter-intuitive finding – most of us would expect a rising number of choices to flatten the curve, but in fact, increasing the size of the system increases the gap between the #1 spot and the median spot.

A second counter-intuitive aspect of power laws is that most elements in a power law system are below average, because the curve is so heavily weighted towards the top performers. In Figure #1, the average number of inbound links (cumulative links divided by the number of blogs) is 31. The first blog below 31 links is 142nd on the list, meaning two-thirds of the listed blogs have a below average number of inbound links. We are so used to the evenness of the bell curve, where the median position has the average value, that the idea of two-thirds of a population being below average sounds strange. (The actual median, 217th of 433, has only 15 inbound links.) 

Freedom of Choice Makes Stars Inevitable #

To see how freedom of choice could create such unequal distributions, consider a hypothetical population of a thousand people, each picking their 10 favorite blogs. One way to model such a system is simply to assume that each person has an equal chance of liking each blog. This distribution would be basically flat – most blogs will have the same number of people listing it as a favorite. A few blogs will be more popular than average and a few less, of course, but that will be statistical noise. The bulk of the blogs will be of average popularity, and the highs and lows will not be too far different from this average. In this model, neither the quality of the writing nor other people’s choices have any effect; there are no shared tastes, no preferred genres, no effects from marketing or recommendations from friends.

But people’s choices do affect one another. If we assume that any blog chosen by one user is more likely, by even a fractional amount, to be chosen by another user, the system changes dramatically. Alice, the first user, chooses her blogs unaffected by anyone else, but Bob has a slightly higher chance of liking Alice’s blogs than the others. When Bob is done, any blog that both he and Alice like has a higher chance of being picked by Carmen, and so on, with a small number of blogs becoming increasingly likely to be chosen in the future because they were chosen in the past.

Think of this positive feedback as a preference premium. The system assumes that later users come into an environment shaped by earlier users; the thousand-and-first user will not be selecting blogs at random, but will rather be affected, even if unconsciously, by the preference premiums built up in the system previously.

Note that this model is absolutely mute as to why one blog might be preferred over another. Perhaps some writing is simply better than average (a preference for quality), perhaps people want the recommendations of others (a preference for marketing), perhaps there is value in reading the same blogs as your friends (a preference for “solidarity goods”, things best enjoyed by a group). It could be all three, or some other effect entirely, and it could be different for different readers and different writers. What matters is that any tendency towards agreement in diverse and free systems, however small and for whatever reason, can create power law distributions.

Because it arises naturally, changing this distribution would mean forcing hundreds of thousands of bloggers to link to certain blogs and to de-link others, which would require both global oversight and the application of force. Reversing the star system would mean destroying the village in order to save it.

Inequality and Fairness #

Given the ubiquity of power law distributions, asking whether there is inequality in the weblog world (or indeed almost any social system) is the wrong question, since the answer will always be yes. The question to ask is “Is the inequality fair?” Four things suggest that the current inequality is mostly fair.

The first, of course, is the freedom in the weblog world in general. It costs nothing to launch a weblog, and there is no vetting process, so the threshold for having a weblog is only infinitesimally larger than the threshold for getting online in the first place.

The second is that blogging is a daily activity. As beloved as Josh Marshall (TalkingPointsMemo.com) or Mark Pilgrim (DiveIntoMark.org) are, they would disappear if they stopped writing, or even cut back significantly. Blogs are not a good place to rest on your laurels.

Third, the stars exist not because of some cliquish preference for one another, but because of the preference of hundreds of others pointing to them. Their popularity is a result of the kind of distributed approval it would be hard to fake.

Finally, there is no real A-list, because there is no discontinuity. Though explanations of power laws (including the ones here) often focus on numbers like “12% of blogs account for 50% of the links”, these are arbitrary markers. The largest step function in a power law is between the #1 and #2 positions, by definition. There is no A-list that is qualitatively different from their nearest neighbors, so any line separating more and less trafficked blogs is arbitrary.

The Median Cannot Hold #

However, though the inequality is mostly fair now, the system is still young. Once a power law distribution exists, it can take on a certain amount of homeostasis, the tendency of a system to retain its form even against external pressures. Is the weblog world such a system? Are there people who are as talented or deserving as the current stars, but who are not getting anything like the traffic? Doubtless. Will this problem get worse in the future? Yes.

Though there are more new bloggers and more new readers every day, most of the new readers are adding to the traffic of the top few blogs, while most new blogs are getting below average traffic, a gap that will grow as the weblog world does. It’s not impossible to launch a good new blog and become widely read, but it’s harder than it was last year, and it will be harder still next year. At some point (probably one we’ve already passed), weblog technology will be seen as a platform for so many forms of publishing, filtering, aggregation, and syndication that blogging will stop referring to any particularly coherent activity. The term ‘blog’ will fall into the middle distance, as ‘home page’ and ‘portal’ have, words that used to mean some concrete thing, but which were stretched by use past the point of meaning. This will happen when head and tail of the power law distribution become so different that we can’t think of J. Random Blogger and Glenn Reynolds of Instapundit as doing the same thing.

At the head will be webloggers who join the mainstream media (a phrase which seems to mean “media we’ve gotten used to.”) The transformation here is simple – as a blogger’s audience grows large, more people read her work than she can possibly read, she can’t link to everyone who wants her attention, and she can’t answer all her incoming mail or follow up to the comments on her site. The result of these pressures is that she becomes a broadcast outlet, distributing material without participating in conversations about it.

Meanwhile, the long tail of weblogs with few readers will become conversational. In a world where most bloggers get below average traffic, audience size can’t be the only metric for success. LiveJournal had this figured out years ago, by assuming that people would be writing for their friends, rather than some impersonal audience. Publishing an essay and having 3 random people read it is a recipe for disappointment, but publishing an account of your Saturday night and having your 3 closest friends read it feels like a conversation, especially if they follow up with their own accounts. LiveJournal has an edge on most other blogging platforms because it can keep far better track of friend and group relationships, but the rise of general blog tools like Trackback may enable this conversational mode for most blogs.

In between blogs-as-mainstream-media and blogs-as-dinner-conversation will be Blogging Classic, blogs published by one or a few people, for a moderately-sized audience, with whom the authors have a relatively engaged relationship. Because of the continuing growth of the weblog world, more blogs in the future will follow this pattern than today. However, these blogs will be in the minority for both traffic (dwarfed by the mainstream media blogs) and overall number of blogs (outnumbered by the conversational blogs.)

Inequality occurs in large and unconstrained social systems for the same reasons stop-and-go traffic occurs on busy roads, not because it is anyone’s goal, but because it is a reliable property that emerges from the normal functioning of the system. The relatively egalitarian distribution of readers in the early years had nothing to do with the nature of weblogs or webloggers. There just weren’t enough blogs to have really unequal distributions. Now there are.

Addendum: #David Sifry, creator of the Technorati.com, has created the Technorati Interesting Newcomers List, in part spurred by this article. The list is designed to flag people with low overall link numbers, but who have done something to merit a sharp increase in links, as a way of making the system more dynamic.

First published January 21, 2003 on the ‘Networks, Economics, and Culture’ mailing list.

The first and last thirds of the music industry have been reconfigured by digital tools. The functions in the middle have not.

Thanks to software like ProTools and CakeWalk, the production of music is heavily digital. Thanks to Napster and its heirs like Gnutella and Kazaa, the reproduction and distribution of music is also digital. As usual, this digitization has taken an enormous amount of power formerly reserved for professionals and delivered it to amateurs. But the middle part — deciding what new music should be available — is still analog and still professionally controlled.

The most important departments at a record label are Artists & Repertoire, and Marketing. A&R’s job is to find new talent, and Marketing’s job is to publicize it. These are both genuinely hard tasks, and unlike production or distribution, there is no serious competition for those functions outside the labels themselves. Prior to its demise, Napster began publicizing itself as a way to find new music, but this was a fig leaf, since users had to know the name of a song or artist in advance. Napster did little to place new music in an existing context, and the current file-sharing networks don’t do much better. In strong contrast to writing and photos, almost all the music available on the internet is there because it was chosen by professionals.

Aggregate Judgments

The curious thing about this state of affairs is that in other domains, we now use amateur input for finding and publicizing. The last 5 years have seen the launch of Google, Blogdex, Kuro5in, Slashdot, and many other collaborative filtering sites that transform the simple judgments of a few participants into aggregate recommendations of remarkably high quality.

This is all part of the Big Flip in publishing generally, where the old notion of “filter, then publish” is giving way to “publish, then filter.” There is no need for Slashdot’s or Kuro5hin’s owners to sort the good posts from the bad in advance, no need for Blogdex or Daypop to pressure people not to post drivel, because lightweight filters applied after the fact work better at large scale than paying editors to enforce minimum quality in advance. A side-effect of the Big Flip is that the division between amateur and professional turns into a spectrum, giving us a world where unpaid writers are discussed side-by-side with New York Times columnists.

The music industry is largely untouched by the Big Flip. The industry harvests the aggregate taste of music lovers and sells it back to us as popularity, without offering anyone the chance to be heard without their approval. The industry’s judgment, not ours, still determines the entire domain in which any collaborative filtering will subsequently operate. A working “publish, then filter” system that used our collective judgment to sort new music before it gets played on the radio or sold at the record store would be a revolution.

Core Assumptions

Several attempts at such a thing have been launched, but most are languishing, because they are constructed as extensions of the current way of producing music, not alternatives to it. A working collaborative filter would have to make three assumptions. 

First, it would have to support the users’ interests. Most new music is bad, and the users know it. Sites that sell themselves as places for bands to find audiences are analogous to paid placement on search engines — more marketing vehicle than real filter. FarmFreshMusic, for example lists its goals as “1. To help artists get signed with a record label. 2. To help record labels find great artists efficiently. 3. To help music lovers find the best music on the Internet.” Note who comes third. 

Second, life is too short to listen to stuff you hate. A working system would have to err more on the side of false negatives (not offering you music you might like) rather than false positives (offering you music you might not like). With false negatives as the default, adventurous users could expand their preferences at will, while the mass of listeners would get the Google version — not a long list of every possible match, but rather a short list of high relevance, no matter what has been left out. 

Finally, the system would have to use lightweight rating methods. The surprise in collaborative filtering is how few people need to be consulted, and how simple their judgments need to be. Each Slashdot comment is moderated up or down only a handful of times, by only a tiny fraction of its readers. The Blogdex Top 50 links are sometimes pointed to by as few as half a dozen weblogs, and the measure of interest is entirely implicit in the choice to link. Despite the almost trivial nature of the input, these systems are remarkably effective, given the mass of mediocrity they are sorting through. 

A working filter for music would similarly involve a small number of people (SMS voting at clubs, periodic “jury selection” of editors a la Slashdot, HotOrNot-style user uploads), and would pass the highest ranked recommendations on to progressively larger pools of judgment, which would add increasing degrees of refinement about both quality and classification. 

Such a system won’t undo inequalities in popularity, of course, because inequality appears whenever a large group expresses their preferences among many options. Few weblogs have many readers while many have few readers, but there is no professional “weblog industry” manipulating popularity. However, putting the filter for music directly in the hands of listeners could reflect our own aggregate judgments back to us more quickly, iteratively, and with less distortion than the system we have today.

Business Models and Love

Why would musicians voluntarily put new music into such a system? 

Money is one answer, of course. Several sorts of businesses profit from music without needing the artificial scarcity of physical media or DRM-protected files. Clubs and concert halls sell music as experience rather than as ownable object, and might welcome a system that identified and marketed artists for free. Webcasting radio stations are currently forced to pay the music industry per listener without extracting fees from the listeners themselves. They might be willing to pay artists for music unencumbered by per-listener fees. Both of these solutions (and other ones, like listener-supported radio) would offer at least some artists some revenues, even if their music were freely available elsewhere. 

The more general answer, however, is replacement of greed with love, in Kevin Kelly’s felicitous construction. The internet has lowered the threshold of publishing to the point where you no longer need help or permission to distribute your work. What has happened with writing may be possible with music. Like writers, most musicians who work for fame and fortune get neither, but unlike writers, the internet has not offered wide distribution to people making music for the love of the thing. A system that offered musicians a chance at finding an audience outside the professional system would appeal to at least some of them. 

Music Is Different

There are obvious differences here, of course, as music is unlike writing in several important ways. Writing tools are free or cheap, while analog and digital instruments can be expensive, and writing can be done solo, while music-making is usually done by a group, making coordination much more complex. Furthermore, bad music is far more painful to listen to than bad writing is to read, so the difference between amateur and professional music may be far more extreme. 

But for all those limits, change may yet come. Unlike an article or essay, people will listen to a song they like over and over again, meaning that even a small amount of high-quality music that found its way from artist to public without passing through an A&R department could create a significant change. This would not upend the professional music industry so much as alter its ecosystem, in the same way newspapers now publish in an environment filled with amateur writing. 

Indeed, the world’s A&R departments would be among the most avid users of any collaborative filter that really worked. The change would not herald the death of A&R, but rather a reconfiguration of the dynamic. A world where the musicians already had an audience when they were approached by professional publishers would be considerably different from the system we have today, where musicians must get the attention of the world’s A&R departments to get an audience in the first place. 

Digital changes in music have given us amateur production and distribution, but left intact professional control of fame. It used to be hard to record music, but no longer. It used to be hard to reproduce and distribute music, but no longer. It is still hard to find and publicize good new music. We have created a number of tools that make filtering and publicizing both easy and effective in other domains. The application of those tools to new music could change the musical landscape.

First published January 7, 2003 on the ‘Networks, Economics, and Culture’ mailing list. 

To understand what’s going to happen to the telephone companies this year thanks to WiFi (otherwise known as 802.11b) and Voice over IP (VoIP) you only need to know one story: ZapMail.

The story goes like this. In 1984, flush from the success of their overnight delivery business, Federal Express announced a new service called ZapMail, which guaranteed document delivery in 2 hours. They built this service not by replacing their planes with rockets, but with fax machines.

This was CEO Fred Smith’s next big idea after the original delivery business. Putting a fax machine in every FedEx office would radically reconfigure the center of their network, thus slashing costs: toner would replace jet fuel, bike messenger’s hourly rates would replace pilot’s salaries, and so on. With a much less expensive network, FedEx could attract customers with a discount on regular delivery rates, but with the dramatically lower costs, profit margins would be huge compared to actually moving packages point to point. Lower prices, higher margins, and to top it all off, the customer would get their documents in 2 hours instead of 24. What’s not to love?

Abject failure was not to love, as it turned out. Two years and hundreds of millions of dollars later, FedEx pulled the plug on ZapMail, allowing it to vanish without a trace. And the story of ZapMail’s collapse holds a crucial lesson for the telephone companies today.

The Customer is the Competitor

ZapMail had three fatal weaknesses.

First of all, Federal Express didn’t get that faxing was a product, not a service. FedEx understood that faxing would be cheaper than physical delivery. What they missed, however, was that their customers understood this too. The important business decision wasn’t when to pay for individual faxes, as the ZapMail model assumed, but rather when to buy a fax machine. The service was enabled by the device, and the business opportunity was in selling the devices.

Second, because FedEx thought of faxing as a service, it failed to understand how the fax network would be built. FedEx was correct in assuming it would take hundreds of millions of dollars to create a useful network. (It has taken billions, in fact, over the last two decades.) However, instead of the single massive build out FedEx undertook, the network was constructed by individual customers buying one fax machine at a time. The capital expenditure was indeed huge, but it was paid for in tiny chunks, at the edges of the network.

Finally, because it misunderstood how the fax network would be built, FedEx misunderstood who its competition was. Seeing itself in the delivery business, it thought it had only UPS and DHL to worry about. What FedEx didn’t see was that its customers were its competition. ZapMail offered two hour delivery for slightly reduced prices, charged each time a message was sent. A business with a fax machine, on the other hand, could send and receive an unlimited number of messages almost instantaneously and at little cost, for a one-time hardware fee of a few hundred dollars.

There was simply no competition. ZapMail looked good next to FedEx’s physical delivery option, but compared to the advantages enjoyed by the owners of fax machines, it was laughable. If the phone network offered cheap service, it was better to buy a device to tap directly into that than to allow FedEx to overcharge for an interface to that network that created no additional value. The competitive force that killed ZapMail was the common sense of its putative users.

ZapPhone

The business Fred Smith imagined being in — build a network that’s cheap to run but charge customers as it if were expensive — is the business the telephone companies are in today. They are selling us a kind of ZapPhone service, where they’ve digitized their entire network up to the last mile, but are still charging the high and confusing rates established when the network was analog.

The original design of the circuit-switched telephone network required the customers to lease a real circuit of copper wire for the duration of their call. Those days are long over, as copper wires have been largely replaced by fiber optic cable. Every long distance phone call and virtually every local call is now digitized for at least some part of its journey.

As FedEx was about faxes, the telephone companies are in deep denial about the change from analog to digital. A particularly clueless report written for the telephone companies offers this choice bit of advice:

Telcos gain billions in service fees from […] services like Call Forwarding and Call Waiting […]. Hence, capex programs that shift a telco, say, from TDM to IP, as in a softswitch approach that might have less capital intensity, must absolutely preserve the revenue stream. [ http://www.proberesearch.com/alerts/refocusing.htm]

You don’t need to know telephone company jargon to see that this is the ZapMail strategy. 

Step #1: Scrap the existing network, which relies on pricey hardware switches and voice-specific protocols like Time Division Multiplexing (TDM). 
Step #2: Replace it with a network that runs on inexpensive software switches and Internet Protocol (IP). This new network will cost less to build and be much cheaper to run. 
Step #3: “Preserve the revenue stream” by continuing to charge the prices from the old, expensive network.

This will not work, because the customers don’t need to wait for the telephone companies to offer services based on IP. The customers already have access to an IP network — it’s called the internet. And like the fax machine, they are going to buy devices that enable the services they want on top of this network, without additional involvement by the telephone companies.

Two cheap consumer devices loom large on this front, devices that create enormous value for the owners while generating little revenue for the phone companies. The first is WiFi access points, which allow the effortless sharing of broadband connections, and the second is VoIP converters, which provide the ability to route phone calls over the internet from a regular phone.

WiFi — Wireless local networks

In classic ZapMail fashion, the telephone companies misunderstand the WiFi business. WiFi is a product, not a service, and they assume their competition is limited to other service companies. There are now half a dozen companies selling wireless access points; at the low end, Linksys sells a hundred dollar device for the home that connects to DSL or cable modems, provides wireless access, and has a built-in ethernet hub to boot. The industry has visions of the “2nd phone line” effect coming to data networking, where multi-computer households will have multiple accounts, but if customers can share a high-speed connection among several devices with a single product, the service business will never materialize.

The wireless ISPs are likely to fare no better. Most people do their computing at home or at work, and deploying WiFi to those two areas will cost at worst a couple hundred bucks, assuming no one to split the cost with. There may be a small business in wiring “third places” — coffee shops, hotels, and meeting rooms — but that will be a marginal business at best. WiFi is the new fax machine, a huge value for consumers that generates little new revenue for the phone companies. And, like the fax network, the WiFi extension to the internet will cost hundreds of millions of dollars, but it will not be built by a few companies with deep pockets. It will be built by millions of individual customers, a hundred dollars at a time.

VoIP — Phone calls at internet prices

Voice over IP is another area where a service is becoming a product. Cisco now manufactures an analog telephone adapter (ATA) with a phone jack in the front and an ethernet jack in the back. The box couldn’t be simpler, and does exactly what you’d expect a box with a phone jack in the front and an ethernet jack in the back to do. The big advantage is that unlike the earlier generation of VoIP products — “Now you can use your computer as a phone!” — the ATA lets you use your phone as a phone, allowing new competitors to offer voice service over any high-speed internet connection.

Vonage.com, for example, is giving away ATAs and offering phone service for $40 a month. Unlike the complex billing structures of the existing telephone companies, Vonage prices the phone like an ISP subscription. A Vonage customer can make an unlimited number of unlimited-length domestic long distance calls for their forty bucks, with call waiting, call forwarding, call transfer, web-accessible voicemail and caller ID thrown in free. Vonage can do this because, like the telephone companies, they are offering voice as an application on a digital network, but unlike the phone companies, they are not committed to charging the old prices by pretending that they are running an analog network.

Voice quality is just one feature among many

True to form, the telephone companies also misunderstand the threat from VoIP (though here it is in part because people have been predicting VoIPs rise since 1996.) The core of the misunderstanding is the MP3 mistake: believing that users care about audio quality above all else. Audiophiles confidently predicted that MP3s would be no big deal, because the sound quality was less than perfect. Listeners, however, turned out to be interested in a mix of things, including accessibility, convenience, and price. The average music lover was willing, even eager, to give up driving to the mall to buy high quality but expensive CDs, once Napster made it possible to download lower quality but free music.

Phone calls are like that. Voice over IP doesn’t sound as good as a regular phone call, and everyone knows it. But like music, people don’t want the best voice quality they can get no matter what the cost, they want a minimum threshold of quality, after which they will choose phone service based on an overall mix of features. And now that VoIP has reached that minimum quality, VoIP offers one feature the phone companies can’t touch: price.

The service fees charged by the average telephone company (call waiting, caller ID, dial-tone and number portability fees, etc) add enough to the cost of a phone that a two-line household that moved only its second line to VoIP could save $40 a month before making their first actual phone call. By simply paying for the costs of the related services, a VoIP customer can get all their domestic phone calls thrown in as a freebie. 

As with ZapMail, the principal threat to the telephone companies’ ability to shrink costs but not revenues is their customers’ common sense. Given the choice, an increasing number of customers will simply bypass the phone company and buy the hardware necessary to acquire the service on their own.

And hardware symbiosis will further magnify the threat of WiFi and VoIP. The hardest part of setting up VoIP is simply getting a network hub in place. Once a hub is installed, adding an analog telephone adapter is literally a three-plug set-up: power, network, phone. Meanwhile, one of the side-effects of installing WiFi is getting a hub with open ethernet ports. The synergy is obvious: Installing WiFi? You’ve done most of the work towards adding VoIP. Want VoIP? Since you need to add a hub, why not get a WiFi-enabled hub? (There are obvious opportunities here for bundling, and later for integration — a single box with WiFi, Ethernet ports, and phone jacks for VoIP.)

The economic logic of customer owned networks

According to Metcalfe’s Law, the value of an internet connection rises with the number of users on the network. However, the phone companies do not get to raise their prices in return for that increase in value. This is a matter of considerable frustration to them.

The economic logic of the market suggests that capital should be invested by whoever captures the value of the investment. The telephone companies are using that argument to suggest that they should either be given monopoly pricing power over the last mile, or that they should be allowed to vertically integrate content with conduit. Either strategy would allow them to raise prices by locking out the competition, thus restoring their coercive power over the customer and helping them extract new revenues from their internet subscribers.

However, a second possibility has appeared. If the economics of internet connectivity lets the user rather than the network operator capture the residual value of the network, the economics likewise suggest that the user should be the builder and owner of the network infrastructure.

The creation of the fax network was the first time this happened, but it won’t be the last. WiFi hubs and VoIP adapters allow the users to build out the edges of the network without needing to ask the phone companies for either help or permission. Thanks to the move from analog to digital networks, the telephone companies’ most significant competition is now their customers, because if the customer can buy a simple device that makes wireless connectivity or IP phone calls possible, then anything the phone companies offer by way of competition is nothing more than the latest version of ZapMail.

First published on O’Reilly’s OpenP2P on January 7, 2003.

A persistent criticism of open source software is that it is more about copying existing features than creating new ones. While this criticism is overblown, the literature of open source is clearer on debugging than on design. This note concerns an attempt to apply debugging techniques to feature requests and concludes by describing Ben Hammersley’s attempt to create such a system, implemented as an RSS feed.

A key observation in Eric Raymond’s The Cathedral and the Bazaar is: “Given enough eyeballs, all bugs are shallow.” Raymond suggests that Brook’s Law–“Adding more programmers to a late software project makes it later”–doesn’t apply here, because debugging is less collaborative than most other software development. He quotes Linus on the nature of debugging: “Somebody finds the problem, and somebody else understands it. And I’ll go on record as saying that finding it is the bigger challenge.”

Finding a bug doesn’t mean simply pointing out broken behavior, though. Finding a bug means both locating it and describing it clearly. The difference between “It doesn’t work” and “Whenever I resize the login window, the Submit button disappears” is the difference between useless mail and useful feedback. Both the description and the fix are vital, and the description precedes the fix.

Enter the LazyWeb

There is evidence that this two-step process applies to features as well, in a pattern Matt Jones has dubbed the LazyWeb. The original formulation was “If you wait long enough, someone will write/build/design what you were thinking about.” But it is coming to mean “I describe a feature I think should exist in hopes that someone else will code it.” Like debugging, the success of the LazyWeb is related at least in part to the quality of the descriptions. A feature, schema, or application described in enough detail can give the right developer (usually someone thinking about the same problem) a clear idea of how to code it quickly. 

Examples of the LazyWeb in action are Stephen Johnson’s URL catcher as built by Andre Torrez, and Ben Trott’s “More Like This From Others” feature after Ben Hammersley’s initial characterization.

LazyWeb seems to work for at least three reasons:

1. Developers have blind spotsBecause a developer knows a piece of software in a far more detailed way than their users, they can have blind spots. A good LazyWeb description provides a developer with a alternate perspective on the problem. And sometimes the triviality of the coding involved keeps developers from understanding how valuable a feature would be to its users, as with Yoz Grahame’s “get, search and replace, display” script for revising the text of web pages. Sometimes four lines of code can make all the difference.
2. Developers have social itchesThe canonical motivation for open source developers is that they want to “scratch an itch.” In this view, most open source software is written with the developer as the primary user, with any additional use seen as a valuable but secondary side-effect.Sometimes, though, the itch a developer has is social: they want to write software other people will adopt. In this case, the advantage of the LazyWeb is not just that a new application or feature is described clearly, but that it is guaranteed to have at least one grateful user. Furthermore, LazyWeb etiquette involves publicizing any solution that does arise, meaning that the developer gets free public attention, even if only to a select group. If writing software that gets used in the wild is a motivation, acting on a LazyWeb description is in many ways a karmically optimal move.
3. Many eyes make features shallowThis is really a meta-advantage. The above advantages would apply even to a conversation between a single describer and a single developer, if they were the right people. Expanding the conversation to include more describers and developers increases the possibility that at least one such pairing will occur.

Transaction Costs and Coordination Costs

The transaction costs of the LazyWeb are extremely low. Someone describes; someone else codes. The describer can write sketchily or in great detail. No developers are required to read the description; and those who do read it can ignore or modify the proposed design. The interface between the parties is lightweight, one-way, and optional.

However, the coordination costs of the LazyWeb as a whole are very high, and they will grow as more people try it. More people can describe features than write software, just as more people can characterize bugs than fix them. Unlike debugging, however, a LazyWeb description does not necessarily have a target application or a target group of developers. This creates significant interface problems, since maximal LazyWeb awareness would have every developer reading every description, an obvious impossibility. (Shades of Brook’s Law.)

This would be true even if the LazyWeb were confined to skilled programmers. The ability of system architects, say, to describe new visual layout tools, or graphics programmers to characterize their filesharing needs, ensures that there will always be more capable describers than suitable developers.

Thus the LazyWeb is currently limited to those environments that maximize the likelihood that a developer with a social itch and a good grasp of the problem space will happen to read a particular LazyWeb description. In practice, this means that successful LazyWeb requests work best when posted on a few blogs read by many developers. Far from being a “More describers than developers” scenario, in other words, the current LazyWeb has many fewer describers than developers, with the developers fragmented across several sites.

Sounds Like a Job for RSS

One common answer to this kind of problem is to launch a portal for all LazyWeb requests. (There have been earlier experiments in this domain, like http://www.halfbakery.com, http://www.shouldexist.org, andhttp://www.creativitypool.com, and Magnetbox has launched a Lazyweb-specific site.) These sites are meant to be brokers between describers and developers.

However, nearly a decade of experimentation with single-purpose portals shows that most of them fail. As an alternative to making a LazyWeb portal, creating an RSS feed of LazyWeb descriptions has several potential advantages, including letting anyone anywhere add to the feed, letting sites that serve developers present the feed in an existing context, and letting the developers themselves fold, spindle, and mutilate the feed in any way they choose.

Ben Hammersley has designed a version of a LazyWeb feed. It has three moving parts. 

The first part is the collection of descriptions. Hammersley assumes that a growing number of people will be writing LazyWeb descriptions, and that most of these descriptions will be posted to blogs.

The second part is aggregation. He has created a trackback address, http://blog.mediacooperative.com/mt-tb.cgi/1080, for LazyWeb posts. Blog posts that point to this address are aggregated and presented at http://www.benhammersley.com/lazyweb/.

The third part is the RSS feed itself, athttp://www.benhammersley.com/lazyweb/index.rdf, which is simply the XML version of http://www.benhammersley.com/lazyweb/. However, because it is a feed, third parties can subscribe to it, filter it, present it as a sidebar on their own sites, and so on.

It’s easy to see new features that could be added to this system. A LazyWeb item in RDF has only four elements, set by the Trackback spec — title, link, description, and date. Thus almost all the onus on filtering the feed is on the subscriber, not the producer. An RDF format with optional but recommended tags (type: feature, schema, application, etc; domain: chat, blog, email, etc.) might allow for higher-quality syndication, but would be hard with the current version of Trackback. Alternatively, community consensus about how to use title tags to characterize feature requests could help.

And not everyone with a LazyWeb idea runs a Trackback-enabled weblog, so having some way for those people to register their ideas could be useful. Hooks for automated translation could make the feed more useful to developers working in languages other than English, and so on.

But for all the possible new features, this is a good start, having achieved a kind of bootstrap phase analogous to compiler development. The original work came out of a LazyWeb characterization made during a larger conversation Jones, Hammersley, and I have been having about social software, and some of the early LazyWeb requests are themselves feature descriptions for the system.

Will It Work?

Will it work? Who knows. Like any experiment, it could die from inactivity. It could also be swamped by a flood of low-quality submissions. It may be that the membrane that a weblog forms around its readers is better for matching describers and developers than an open feed would be. And Paul Hammond has suggested that “Any attempt to invoke the LazyWeb directly will cause the whole thing to stop working.” 

It’s worth trying, though, because the potential win is so large. If the benefits open source development offers for fixing bugs can be applied to creating features as well, it could confer a huge advantage on the development of Mob Software.

Stefano Mazzocchi of the Cocoon project has said “Anyway, it’s a design pattern: ‘good ideas and bad code build communities, the other three combinations do not.” This is extremely hard to understand, it’s probably the most counter-intuitive thing about open source dynamics.” If Mazzocchi is right, then a high-quality stream of feature requests could be a powerful tool for building communities of developers and users, as well as providing a significant advantage to open over closed source development.

The closed source shops could subscribe to such a feed as well, of course, but their advantage on the feature front isn’t speed, it’s secrecy. If a small group of closed source developers is working on a feature list that only they know, they will often ship it first. But for good ideas in the public domain, the open and closed development teams will have the same starting gun. And releasing early and often is where open development has always excelled.

It’s too early to tell if LazyWeb is just the flavor of the month or points to something profound about the way ideas can spread. And it’s much too early to know if an RSS feed is the right way to spread LazyWeb ideas to the developers best able to take advantage of them. But it’s not too early to know that it’s worth trying.

First published on the ‘Networks, Economics, and Culture mailing list.

For decades, the privacy debate has centered on questions about databases and database interoperability: How much information about you exists in the world’ databases? How easily is it retrieved? How easily is it compared or combined with other information?

Databases have two key weaknesses that affect this debate. The first is that they deal badly with ambiguity, and generally have to issue a unique number, sometimes called a primary key, to every entity they store information on. The US Social Security number is a primary key that points to you, the 6-letter Passenger Name Record is a primary key that points to a particular airline booking, and so on. This leads to the second weakness: since each database maintains its own set of primary keys, creating interoperability between different databases is difficult and expensive, and generally requires significant advance coordination.

Privacy advocates have relied on these weaknesses in creating legal encumbrances to issuing and sharing primary keys. They believe, rightly, that widely shared primary keys pose a danger to privacy. (The recent case of Princeton using its high school applicants’ Social Security numbers to log in to the Yale admittance database highlights these dangers.) The current worst-case scenario is a single universal database in which all records — federal, state, and local, public and private — would be unified with a single set of primary keys.

New technology brings new challenges however, and in the database world the new challenge is not a single unified database, but rather decentralized interoperability, interoperability brought about by a single universally used ID. The ID is DNA. The interoperability comes from the curious and unique advantages DNA has as a primary key. And the effect will put privacy advocates in a position analogous to that of the RIAA, forcing them to switch from fighting the creation of a single central database to fighting a decentralized and interoperable system of peer-to-peer information storage.

DNA Markers

While much of the privacy debate around DNA focuses on the ethics of predicting mental and physical fitness for job categories and insurance premiums, this is too narrow and too long-range a view. We don’t even know yet how many genes there are in the human genome, so our ability to make really sophisticated medical predictions based on a person’s genome is still some way off. However, long before that day arrives, DNA will provide a cheap way to link a database record with a particular person, in a way that is much harder to change or forge than anything we’ve ever seen.

Everyone has a biological primary key embedded in every cell of their body in the form of DNA, and everyone has characteristic zones of DNA that can be easily read and compared. These zones serve as markers, and they differ enough from individual to individual that with fewer than a dozen of them, a person can be positively identified out of the entire world’s population.

DNA-as-marker, in other words, is a nearly perfect primary key, as close as we can get to being unambiguous and unforgeable. If every person has a primary key that points to their physical being, then the debate about who gets to issue such a key are over, because the keys are issued every time someone is born, and re-issued every time a new cell is created. And if the keys already exist, then the technological argument is not about creating new keys, but about reading existing ones.

The race is on among several biotech firms to be able to sequence a person’s entire genome for $1000. The $1 DNA ID will be a side effect of this price drop, and it’s coming soon. When the price of reading DNA markers drops below a dollar, it will be almost impossible to control who has access to reading a person’s DNA.

There are few if any legal precedents that would prevent collection of this data, at least in the US. There are several large populations that do not enjoy constitutional protections of privacy, such as the armed services, prisoners, and children. Furthermore, most of the controls on private databases rely on the silo approach, where an organization can collect an almost unlimited amount of information about you, provided they abide by the relatively lax rules that govern sharing that information.

Even these weak protections have been enough, however, to prevent the creation of a unified database, because the contents of two databases cannot be easily merged without some shared primary key, and shared primary keys require advance coordination. And it is here, in the area of interoperability, that DNA markers will have the greatest effect on privacy.

You’re the Same You Everywhere

Right now, things like alternate name spellings or alternate addresses make positive matching difficult across databases. Its hard to tell if Eric with the Wyoming driver’s license and Shawn with the Florida arrest record are the same person, unless there is other information to tie them together. If two rows of two different databases are tied to the same DNA ID, however, they point to the same person, no matter what other material is contained in the databases, and no matter how it is organized or labeled.

No more trying to figure out if Mr. Shuler and Mr. Schuller are the same person, no more wondering if two John Smiths are different people, no more trying to guess the gender of J. Lee. Identity collapses to the body, in a way that is far more effective than fingerprints, and far more easily compared across multiple databases than more heuristic measures like retinal scans.

In this model, the single universal database never gets created, not because privacy advocates prevent it, but because it is no longer needed. If primary keys are issued by nature, rather than by each database acting alone, then there is no more need for central databases or advance coordination, because the contents of any two DNA-holding databases can be merged on demand in something close to real time.

Unlike the creation of a vast central database, even a virtual one, the change here can come about piecemeal, with only a few DNA-holding databases. A car dealer, say, could simply submit a DNA marker to a person’s bank asking for a simple yes-or-no match before issuing a title. In the same way the mid-90s ID requirements for US domestic travel benefited the airlines because it kept people from transferring unused tickets to friends of family, we can expect businesses to like the way DNA ties transactions to a single customer identity.

The privacy debate tends to be conducted as a religious one, with the absolutists making the most noise. However, for a large number of people, privacy is a relative rather than an absolute good. The use of DNA as an ID will spread in part because people want it to, in the form of credit cards that cannot be used in other hands or cars that cannot be driven by other drivers. Likewise, demands that DNA IDs be derived from populations who do not enjoy constitutional protections, whether felons or children, will be hard to deflect as the cost of reading an individual’s DNA falls dramatically, and as the public sees the effective use of DNA in things like rape and paternity cases.

Peer-to-Peer Collation of Data

In the same way Kazaa has obviated the need for central storage or coordination for the world’s music, the use of DNA as an ID technology makes radically decentralized data integration possible. With the primary key problem solved, interoperability will arise as a side effect, neither mandated nor coordinated centrally. Fighting this will require different tactics, not least because it is a rear-guard action. The keys and the readers both exist, and the price and general availability of the technology all point to ubiquity and vanishingly low cost within a decade.

This is a different kind of fight over privacy. As the RIAA has discovered, fighting the growth of a decentralized and latent capability is much harder than fighting organizations that rely on central planning and significant resources, because there is no longer any one place to focus the efforts, and no longer any small list of organizations who can be targeted for preventive action. In a world where database interoperability moves from a difficult and costly goal to one that arises as a byproduct of the system, the important question for privacy advocates is how they will handle the change.

Published October 3, 2002 on the “Networks, Economics, and Culture” mailing list.

A lot of people in the weblog world are asking “How can we make money doing this?” The answer is that most of us can’t. Weblogs are not a new kind of publishing that requires a new system of financial reward. Instead, weblogs mark a radical break. They are such an efficient tool for distributing the written word that they make publishing a financially worthless activity. It’s intuitively appealing to believe that by making the connection between writer and reader more direct, weblogs will improve the environment for direct payments as well, but the opposite is true. By removing the barriers to publishing, weblogs ensure that the few people who earn anything from their weblogs will make their money indirectly.

The search for direct fees is driven by the belief that, since weblogs make publishing easy, they should lower the barriers to becoming a professional writer. This assumption has it backwards, because mass professionalization is an oxymoron; a professional class implies a minority of members. The principal effect of weblogs is instead mass amateurization.

Mass amateurization is the web’s normal pattern. Travelocity doesn’t make everyone a travel agent. It undermines the value of being travel agent at all, by fixing the inefficiencies travel agents are paid to overcome one booking at a time. Weblogs fix the inefficiencies traditional publishers are paid to overcome one book at a time, and in a world where publishing is that efficient, it is no longer an activity worth paying for.

Traditional publishing creates value in two ways. The first is intrinsic: it takes real work to publish anything in print, and more work to store, ship, and sell it. Because the up-front costs are large, and because each additional copy generates some additional cost, the number of potential publishers is limited to organizations prepared to support these costs. (These are barriers to entry.) And since it’s most efficient to distribute those costs over the widest possible audience, big publishers will outperform little ones. (These are economies of scale.) The cost of print insures that there will be a small number of publishers, and of those, the big ones will have a disproportionately large market share.

Weblogs destroy this intrinsic value, because they are a platform for the unlimited reproduction and distribution of the written word, for a low and fixed cost. No barriers to entry, no economies of scale, no limits on supply.

Print publishing also creates extrinsic value, as an indicator of quality. A book’s physical presence says “Someone thought this was worth risking money on.” Because large-scale print publishing costs so much, anyone who wants to be a published author has to convince a professionally skeptical system to take that risk. You can see how much we rely on this signal of value by reflecting on our attitudes towards vanity press publications.

Weblogs destroy this extrinsic value as well. Print publishing acts as a filter, weblogs do not. Whatever you want to offer the world — a draft of your novel, your thoughts on the war, your shopping list — you get to do it, and any filtering happens after the fact, through mechanisms like blogdex and Google. Publishing your writing in a weblog creates none of the imprimatur of having it published in print.

This destruction of value is what makes weblogs so important. We want a world where global publishing is effortless. We  want a world where you don’t have to ask for help or permission to write out loud. However, when we get that world we face the paradox of oxygen and gold. Oxygen is more vital to human life than gold, but because air is abundant, oxygen is free. Weblogs make writing as abundant as air, with the same effect on price. Prior to the web, people paid for most of the words they read. Now, for a large and growing number of us, most of the words we read cost us nothing.

Webloggers waiting for micropayments and other forms of direct user fees have failed to understand the enormity of these changes. Weblogs aren’t a form of micropublishing that now needs micropayments. By removing both costs and the barriers, weblogs have drained publishing of its financial value, making a coin of the realm unnecessary.

One obvious response is to restore print economics by creating artificial scarcity: readers can’t read if they don’t pay. However, the history of generating user fees through artificial scarcity is grim. Without barriers to entry, you will almost certainly have high-quality competition that costs nothing.

This leaves only indirect methods for revenue. Advertising and sponsorships are still around, of course. There is a glut of supply, but this suggests that over time advertising dollars will migrate to the Web as a low-cost alternative to traditional media. In a similar vein, there is direct marketing. The Amazon affiliate program is already providing income for several weblogs like Gizmodo and andrewsullivan.com.

Asking for donations is another method of generating income, via the Amazon and Paypal tip jars. This is the Web version of user-supported radio, where a few users become personal sponsors, donating enough money to encourage a weblogger to keep publishing for everyone. One possible improvement on the donations front would be weblog co-ops that gathered donations on behalf of a group of webloggers, and we can expect to see weblog tote bags and donor-only URLs during pledge drives, as the weblog world embraces the strategies of publicly supported media.

And then there’s print. Right now, the people who have profited most from weblogs are the people who’ve written books about weblogging. As long as ink on paper enjoys advantages over the screen, and as long as the economics make it possible to get readers to pay, the webloggers will be a de facto farm team for the publishers of books and magazines.

But the vast majority of weblogs are amateur and will stay amateur, because a medium where someone can publish globally for no cost is ideal for those who do it for the love of the thing. Rather than spawning a million micro-publishing empires, weblogs are becoming a vast and diffuse cocktail party, where most address not “the masses” but a small circle of readers, usually friends and colleagues. This is mass amateurization, and it points to a world where participating in the conversation is its own reward.

This essay is an extension of a speech I gave at the BBC about the prospects for online community building by broadcast media. First published September 9, 2002 on the ‘Networks, Economics, and Culture’ mailing list.

There is a long history of businesses trying to harness the power of online communities for commercial ends. Most of these attempts have failed, for the obvious reasons. There are few products or services people care about in a way that would make them want to join a community, and when people are moved to speak out about a commercial offering, it is usually to complain.

Media organizations, however, would seem to be immune to these difficulties, because online media and online communities have the same output: words and images. Even here, though, there are significant obstacles to hosting community, obstacles peculiar to the nature of media. Much of the discipline a broadcast organization must internalize to do its job well are not merely irrelevant to community building, but actively harmful.

If you were a broadcast media outlet thinking about community building, here are five things you would think about:

1. Audiences are built. Communities grow.
2. Communities face a tradeoff between size and focus.
3. Participation matters more than quality.
4. You may own the software, but the community owns itself.
5. The community will want to build. Help it, or at least let it.

#1. Audiences are built. Communities grow.

Audiences are connected through broadcast. Everyone in the MSNBC audience sees MSNBC content broadcast outwards from the center. You can’t build a community this way, because the things that make a community worthwhile are provided by the members for one another, and cannot be replaced by things the hosting organization can offer. Communities are connected through what Greg Elin calls intercast — the communications that pass among and between interconnected members of a community.

Broadcast connections can be created by a central organization, but intercast connections are created by the members for one another. Communities grow, rather than being built. New members of an audience are simply added to the existing pool, but new members of a community must be integrated. Matt Jones uses the word “loam” to describe the kind of environment conducive to community formation. One of the most important things you can do to attract community is to give it a fertile environment in which to grow, and one of the most damaging things you can do is to try to force it to grow at a rapid pace or in a preset direction.

#2. Communities face a tradeoff between size and focus.

Communities are held together through intercast communications, but, to restate Metcalfe’s Law, the complexity of intercast grows faster than group size. This means that in an intercast world, uniformly dense interconnectedness becomes first hard and then impossible to support as a group grows large. The typical response for a growing community is to sub-divide, in either “soft” ways (overlapping social clusters) or “hard” ways (a church that splits into two congregations.)

Small groups can be highly focused on some particular issue or identity, but such groups can’t simply be inflated like a balloon, because a large group is a different kind of thing than a small one. Online groups that grow from small to large tend to lose their focus, as topic drift or factionalization appears.

Most broadcast organizations assume that reaching a large group is an unqualified good, so they push for size at any cost, and eventually bump into the attendant tradeoffs: you can have large community, but not a highly focused one; you can have a focused community, but not a large one; or you can reach a large number of people focused on a particular issue, but it won’t be a community.

With these options, broadcast organizations will (often unconsciously) opt for the last one, simply building an audience and calling it a community, as in “The community of our readers.” Though this may make for good press release material, calling your audience a community doesn’t actually make it one.

#3. Participation matters more than quality.

The order of things in broadcast is “filter, then publish.” The order in communities is “publish, then filter.” If you go to a dinner party, you don’t submit your potential comments to the hosts, so that they can tell you which ones are good enough to air before the group, but this is how broadcast works every day. Writers submit their stories in advance, to be edited or rejected before the public ever sees them. Participants in a community, by contrast, say what they have to say, and the good is sorted from the mediocre after the fact.

Media people often criticize the content on the internet for being unedited, because everywhere one looks, there is low quality — bad writing, ugly images, poor design. What they fail to understand is that the internet is strongly edited, but the editorial judgment is applied at the edges, not the center, and it is applied after the fact, not in advance. Google edits web pages by aggregating user judgment about them, Slashdot edits posts by letting readers rate them, and of course users edit all the time, by choosing what (and who) to read.

Anyone who has ever subscribed to a high-volume mailing list knows there are people who are always worth reading, and people who are usually worth ignoring. This is a way of raising the quality of what gets read, without needing to control what gets written. Media outlets that try to set minimum standards of quality in community writing often end up squeezing the life out of the discussion, because they are so accustomed to filtering before publishing that they can’t imagine that filtering after the fact can be effective.

#4. You may own the software, but the community owns itself.

The relationship between the owner of community software and the community itself is like the relationship between a landlord and his or her tenants. The landlord owns the building, and the tenants take on certain responsibilities by living there. However, the landlord does not own the tenants themselves, nor their relations to one another. If you told tenants of yours that you expected to sit in on their dinner table conversation, they would revolt, and, as many organizations have found, the same reaction occurs in online communities.

Community is made possible by software, but the value is created by its participants. If you think of yourself as owning a community when you merely own the infrastructure, you will be astonished at the vitriol you will face if you try to force that community into or out of certain behaviors.

#5. The community will want to build. Help it, or at least let it.

Healthy communities modify their environment. One of the surprises in the design of software that supports community is that successful innovations are often quite shallow. We have had the necessary technology to build weblogs since 1994, but weblogs themselves didn’t take off until 5 years later, not because the deep technology wasn’t there, but because the shallow technology wasn’t. Weblogs are primarily innovations in interface, and, as importantly, innovations in the attitudes of the users.

Because communal innovation often hinges as much on agreements among users as protocols among machines, communities can alter their environments without altering the underlying technology. If you spend any time looking at LiveJournal (one of the best overall examples of good community engineering) you will see periodic epidemics of the “Which type of pasta are you”-style quizzes. (“You’re fusilli — short and twisted.”) The quizzes are not hosted on LiveJournal servers, but they have become part of the LiveJournal community.

If LiveJournal had decided to create a complete, closed experience, they could have easily blocked those quizzes. However, they didn’t mistake owning the database for owning the users (see #4 above), so they let the users import capabilities from elsewhere. The result is that the community’s connection to LiveJournal is strengthened, not weakened, because over time the environment becomes fitted to the community that uses it, even though nothing in the software itself changes.

Hard Work

If you want to host a community online, don’t kid yourself into believing that giving reporters weblogs and calling the reader comments “community” is the same as the real thing. Weblogs operate on a spectrum from media outlet (e.g. InstaPundit) to communal conversation (e.g. LiveJournal), but most weblogs are much more broadcast than intercast. Likewise, most comments are write-only replies to the original post in the manner of Letters to the Editor, rather than real conversations among the users. This doesn’t mean that broadcast weblogs or user comments are bad; they just don’t add up to a community.

Real community is a self-creating thing, with some magic spark, easy to recognize after the fact but impossible to produce on demand, that draws people together. Once those people have formed a community, however, they will act in the interests of the community, even if those aren’t your interests. You need to be prepared for this.

The hallmark of a successful community is that it achieves some sort of homeostasis, the ability to maintain an internal equilibrium in the face of external perturbations. One surprise is that if a community forms on a site you host, they may well treat you, the owner of the site, as an external perturbation. Another surprise is that they will treat growth as a perturbation as well, and they will spontaneously erect barriers to that growth if they feel threatened by it. They will flame and troll and otherwise make it difficult for potential new members to join, and they will invent in-jokes and jargon that makes the conversation unintelligible to outsiders, as a way of raising the bar for membership.

This does not mean that hosting community is never worthwhile — the communal aspects of sites like Slashdot and Kuro5hin are a critical source of their value. It just means that it is hard work, and will require different skills and attitudes than those necessary to run a good broadcast site. Many of the expectations you make about the size, composition, and behavior of audiences when you are in a broadcast mode are actually damaging to community growth. To create an environment conducive to real community, you will have to operate more like a gardener than an architect.

Version 1.03 | September 3, 2002

A good deal has been written about the digital divide, the technological gap that exists between the developed and developing world. If you wanted a striking illustration of the problem, you could turn to Thabo Mbeki’s speech at the Information Society and Development Conference in 1996, where he told the delegates “Half of humanity has not yet made a phone call.”

Or, if you prefer, Kofi Annan’s 2000 speech to the Australian Press Club, where he said “Half the world’s population has never made or received a phone call.” Or Thomas Homer-Dixon’s version, from a speech in 2001: “…half the people on the planet have never made a phone call.” Greg LeVert of MCI said it at a telecom conference in 1994; Richard Klugman of PaineWebber said it in The Economist in 1995; Jeffery Sachs and Al Gore both said it in 1998; Reed Hundt and Steve Case both said it 2000; Michael Moore and Newt Gingrich both said it in 2001, as did Carly Fiorina and Melinda Gates; and not content with merely half, Tatang Razak of Indonesia told the UN’s Committee on Information “After all, most of the people in the world have never made a phone call…”, in speech from April of this year.

The phrase “Half the world has never made a phone call” or some variation thereof has become an urban legend, a widely believed but unsubstantiated story about the nature of the world. It has appeared countless times over the last decade, in essentially the same form and always without attribution. Where did that phrase come from? How did it take on such a life of its own? And, most importantly, why has it gotten so much airtime in the debate over the digital divide when it is so obviously wrong?

You Can’t Keep A Good Factoid Down 

The Phrase is such a serious and important statistic that only the boorish would question its accuracy. There is a kind of magical resonance in advancing arguments on behalf of half the world’s people, and it allows the speaker to chide the listener for harboring any lingering techno-optimism (“You think there’s a revolution going on? Half the world has never made a phone call!”) The Phrase establishes telecommunications access as a Big Problem and, by extension, validates the speaker as a Thinker-About-Big-Problems. 

But saying “Half the world has never made a phone call” makes no more sense than saying “My car goes from 0 to 60” or “It rained 15 inches.” Without including the element of time, you cannot talk about rate, and it is rate that matters in dynamic systems. Half the world had never made a phone call on what date? And what has the rate of telecom growth been since that date? Because it is that calculation and only that calculation which could tell us anything important about the digital divide.

Static Statements About Dynamic Systems 

Virginia Postrel, in her book “The Future and Its Enemies”, (ISBN: 0684862697) suggests that the old distinctions of right and left are now less important than a distinction between stasists and dynamists. Stasists are people who believe that the world either is or should be a controlled, predictable place. Dynamists, by contrast, see the world as a set of dynamic processes. This distinction is the key to The Phrase. Anyone who uses it is affirming the stasist point of view, even if unconsciously, because they are treating telecommunications infrastructure as if it were frozen in time.

To think about rate, we need three things: original time, elapsed time, and speed of change. The figure first appeared in print in late 1994, when the Toronto Sun quoted it as part of Greg LeVert’s speech at TeleCon ’94. (Mr. LeVert was no stasist — though he seems to have accidentally bequeathed us The Phrase, no one now remembers that he introduced it as a way of dramatizing the magnitude of the coming change, and went on to predict a billion new phones by 2000.) Therefore we can restore the question of rate by asking what has happened to the number of telephones in the world between the beginning of 1995 and now.

Restoring Rate

The ITU estimates that there were approximately 689 million land lines at the beginning of 1995, and a little over 1 billion by the end of 2000, the last year for which they have figures available. This is an average annual growth rate of just over 7%, and a cumulative improvement in that period of over 50%, meaning that the first two-thirds of the world’s phone lines were run between 1876 and 1994, and the remaining third were run between 1995 and 2000. Put another way, half again as many land lines were run in the last 6 years of the 20th century as were run in the whole previous history of telephony. So much for stasis. 

Of course not all of this growth touches the problem at hand — a new phone line in a teenager’s room may increase several sorts of telecom statistics, but the number of people making their first phone call isn’t one of them. Since The Phrase concerns the digital divide, we should concentrate on telecom growth in the less developed world. 

From the beginning of 1995 to the end of 2000, 8 countries achieved compound average growth rates of 25% or more for land lines per 100 people (against a world average of 7%), meaning they at least tripled the number of land lines over the whole period. They were, in order of rate, Sudan (which improved six-fold), Albania, China, Sri Lanka, Viet Nam, Ghana, Nepal, and Cambodia — not exactly the G8. China alone went from 41 million land lines to 179 million in those 6 years. And there were 35 additional countries, including India, Indonesia, and Brazil, with annual growth of between 10 and 20% from 1995 to 2000, meaning they at least doubled the number of land lines in that period.

And mobile telephony makes the change in land lines look tectonic. In 1995, there were roughly 91 million cellular subscribers. By 2000, the number had risen to 946 million, a ten-fold increase. Twenty-seven countries had growth rates of over 100% annually, meaning that, at a minimum, they doubled and doubled again, 6 times, achieving better than sixty-fold cumulative growth (not 60%, but a factor of 60), and 22 of those had better than hundred-fold growth. Senegal went from around 100 subscribers (not 100 thousand subscribers, 100 subscribers) to 390 thousand. Egypt went from 7 thousand to almost 3 million. Romania went from 9 thousand to almost 4 million. An additional 44 nations with no measurable wireless penetration in 1995 had acquired wireless subscribers by 2001.

Because wireless infrastructure does not require painstaking building-by-building connectivity, nor is it as hampered by state-owned monopolies, it offers a way for a country to increase its telephone penetration extremely quickly. By the end of 2000, there were 25 countries where cell phone users made up between two-thirds and nine-tenths of the connected populace. In these countries, none of them wealthy, a new telecommunications infrastructure was deployed from scratch, during the same years that keynote speakers and commencement invitees were busily and erroneously informing their listeners that half the world had never made a phone call.

Two Answers

So, in 2002, what can we conclude about the percentage of the world that has made a phone call?

The first, and less important answer to that question goes like this: Between 1995 and 2000, the world’s population rose by about 8%. Meanwhile, the number of land lines rose by 50%, and the number of cellular subscribers by over 1000%. Contrary to the hopelessness conveyed by The Phrase, telephone penetration is growing much faster than population. It is also growing faster in the developing world than in the developed world. Outside the OECD, growth was about 130% for land lines and over 2,300% for cellular phones — 14 million subscribers at the beginning of 1995 and 342 million by the end of 2000. If we assume that LeVert’s original guess of half was right in 1994 (a big if), the new figure would be “Around two-thirds and still rising.”

There is another answer to that question though, which is much more important: It doesn’t matter. No snapshot of telephone penetration matters, because the issue is not amount but rate. If you care about the digital divide, and you believe that access to communications can help poor countries to grow, then pontificating about who has or hasn’t made a phone call is worse than a waste of time, it actively distorts your view of the possible solutions because it emphasizes a stasist attitude. 

Though a one-time improvement of 5% is better in the short run than a change that improves annual growth by 1%, the latter solution is better in the medium run, and much better in the long run. As as everything from investment theory to Moore’s Law has shown, it’s hard to beat compound growth, and improving compound growth in the spread of telephones requires reducing the barriers between demand and supply. Some countries have had enormously favorable rates of growth in the last decade, so we should ask what has gone right in those countries. It turns out that money is less important than you might expect. 

Examples from the Real World

In 1995, Brunei had almost twice as many land lines and 50 times as many cell phones per capita as Poland, not to mention more than twice the per capita GDP. By the end of 2000, Poland exceeded Brunei in land lines, and had even matched it in cell phone penetration. Brunei is smaller, easier to wire, and much much richer, but Poland has something that all Brunei’s money can’t buy — a dynamic economy. Ireland similarly outgrew Denmark and Egypt outgrew Kuwait, even though the faster growing countries were the poorer ones.

The Democratic Republic of Congo lost 16 thousand of its 36 thousand fixed lines but grew overall, because it added 140 thousand cell phones. Its unsurprising that people would abandon the state as a provider of telephones in a country riven by civil war. What is surprising is that Venezuela had the same pattern. Venezuela, with a monopoly telecom provider, saw its per capita penetration of land lines fall by 0.3% annually, while cell phone use exploded. In both cases, the state was an obstacle to telephone usage, but the presence of a private alternative meant that telephone penetration could nevertheless increase.

Bangladesh, with a per capita GDP of $1,570, has had annual cellular growth of nearly 150%, in part because of programs like the Grameen Bank’s Village Phone, which loans a phone, collateral free, to women in Bangladeshi villages, who in turn resell the service to their neighbors. This is double leverage, as it not only increases the number of phones in use, but also increases the number of users per phone.

These examples demonstrate what makes The Phrase so pernicious. Something incredibly good is happening in parts of the world with dynamic economies, and that is what people concerned with the digital divide should be thinking about. If the world’s poor are to be served by better telecommunications infrastructure, there are obvious things to be done. Make sure individuals have access to a market for telephone service. Privatize state telecom companies, introduce competition, and reduce corruption. And perhaps most importantly, help stamp out static thinking about telecommunications wherever it appears. Economic dynamism is a far better tool for improving telephone use than any amount of erroneous and incomplete assertions on behalf of half the world’s population, because while The Phrase has remained static for the last decade or so, the world hasn’t.

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Version History: This is version 1.03 of this essay, from September 3, 2002. Version 1.0 was published June 30, 2002, 1.01 appeared on July 3, and 1.02 appeared July 19th.

Changes from 1.0 to 1.01: I realized after publishing the original essay that the ITU statistics run from January 1 to January 1, meaning that the 1995-2001 period is 6 elapsed years, not 7. To make this clear, I re-wrote the sections “Restoring Rate”, “Two Answers”, and the first paragraph of “Lessons from the Real World” to refer to “the end of 2000” or “2000” as the stop date for the growth figures, and to list the elapsed time as 6 years.

This means that the changes described here happend in less time, i.e. at a faster rate, than I originally suggested. The only place it materially affects the numerical conclusions is in 30 countries which had in excess of 100% annual growth. Only 26 of these countries had 100-fold growth (i.e. a compound average growth rate of above 116%). The remaining 4 grew between 64 and 100-fold.

Changes from 1.01 to 1.02: Re-wrote the second paragraph. I had incorrectly located Kofi Annan’s speech at the ITU, rather than at the Australian Press club (though he has said it in several other venues as well, including his Millenium Report, and the World Economic Forum in Davos in 2001.) Fiorina’s use of The Phrase dates from 2001, not 1999. I also added the references to Steve Case and Melinda Gates. The paragraph in its original form can be found at the link to version 1.0, above.

Changes from 1.02 to 1.03: Noted that the 8 countries listed as having the highest percentage of wired telecom growth, in the paragraph beginning “From the beginning of 1995 to the end of 2000…”, all had growth rates in excess of 25%, not merely 20%. (Thanks to Jennifer Weaver of Wired, who edited a version of this article to appear there.)

Wired telecom penetration in the developing world 2001 was 230% of what it was in 1995, meaning it grew 130%. Changed the 230% figure to 130% in the paragraph beginning “The first, and less important answer to that question…” to reflect the growth rate, rather than absolute penetration. Likewise changed the 2,400% figure for wireless to 2,300%, for the same reason.

Changed the wireless figures, in the paragraph beginning “And mobile telephony makes the change in land lines…” to include the 44 countries that created divide-by-zero errors when using the ITU statistics, because their measurable wireless penetration was 0 in 1995.

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NOTES: The statistics on teledensity used here are drawn from the International Telecommunication Union (www.itu.int/). The statistics page is at www.itu.int/ITU-D/ict/statistics/, and the documents concerning compound and overall growth in main telephone lines and cellular subscribers between 1995 and 2001 are atwww.itu.int/ITU-D/ict/statistics/at_glance/main01.pdf and www.itu.int/ITU-D/ict/statistics/at_glance/cellular01.pdfrespectively.

The estimates for the developing world were derived by treating the membership of the Organization for Economic Co-operation and Development (OECD, www.oecd.org) as a proxy for the developed world. Growth in the developing world was then derived by recalculating the totals from the ITU documents after removing the 30 countries in the OECD.

The figure for population growth was derived from the US Census Bureau’s estimates of world population in 1995 and 2001. www.census.gov/ipc/www/worldpop.html

The original Toronto Sun piece, from the Business section of October 13th of 1994) read:

So you think the world is wired? Half the world's population — an astounding three billion people -- has never made a phone call, a telecommunications conference was told Wednesday.
  
"Most people on Earth live more than two hours from a telephone," Greg LeVert, president of U.S. giant MCI's Integrated Client Services Division, told delegates to TeleCon '94 in Toronto.
  
Things are changing fast, though.
  
"Nearly a billion more people will have access to a telephone by 2000," LeVert said.