Tim O’Reilly and Nick Carr had quite a back and forth last week about the nature and future of cloud computing. It’s worth a read if you’ve got the time. If not, here are the highlights (and a few additional thoughts). It started with O’Reilly claiming that

The cloud platform, like the software platform before it, has new rules for competitive advantage. And chief among those advantages are those that we’ve identified as “Web 2.0″, the design of systems that harness network effects to get better the more people use them.

Carr takes issue with that:

Let’s stop here, and take a look at the big kahuna on the Net, Google, which O’Reilly lists as the first example of a business that has grown to dominance thanks to the network effect. Is the network effect really the main engine fueling Google’s dominance of the search market? I would argue that it certainly is not.

That might sound wrong to a lot of people. The idea that Google learns from its users is a pretty popular interpretation of the situation. The explanation goes something like this: Every time you click on a link you train the system a bit better. So the reason Google is so great is that there are so many people using it.

But that’s not quite accurate. Carr again:

What Google did was to successfully mine the “intelligence” that lies throughout the public web (not just within its own particular network or user group). The intelligence embedded in a link is equally valuable to Google whether the person who wrote the link is a Google user or not. In his new post, in other words, O’Reilly is confusing “harnessing collective intelligence” with “getting better the more people use them.” They are not the same thing.

It’s not that using Google makes Google better, it’s that using the Web in general makes Google better. That’s an important distinction, but it might obscure the meaning and the significance of “network effect.” Carr points out that effective cloud computing services (like Google) do leverage the collective intelligence of the Web, but that “this has nothing to do with the network effect as O’Reilly defines it.” He’s right–O’Reilly does seem to explicitly make the network effects here about cases when the more people use a particular service the better than service gets.

But O’Reilly has a response to this:

Consider Google: The underlying network that Google is based on is one that they neither own nor control, the web itself. It has both endogamous end exogamous elements. No one controls it; its richness and diversity depends on that fact. And yet, there is a benefit to belonging. If there weren’t, sites would use their robots.txt file to tell Google and other search engines to stop spidering them.

Yes, you might say: but other search engines have access to that same network. And here, of course, is the first lesson: Google is better at spidering that network than their competitors. They thus benefit more powerfully from the network that we are all collectively building via our web publishing and cross-linking. Nick correctly points out that Google has built superior systems, and that these are the source of their competitive advantage. But that’s a diversion. Why did they build those superior systems? To harness the power that was hidden in the network more effectively than their competitors.

Carr has another response and even an additional follow-up. This conversation could go on a long time. And it will–not this particular exchange but the broader discussion about cloud computing, network effects, collective intelligence, and a host of other factors that are converging to produce the Web as we know it today: not a bunch of linked information, but also a plethora of usefuls tools and social technologies. Even The Economist had a special report this month on the future of IT.

But the interesting thing about this little tiff between Carr and O’Reilly–two pretty big names in this space–is how specific and even technical it gets. “Network effects” and “collective intelligence” are the sort of phrases that can become buzzwords. They have in many instances and have been rightly lampooned as such. In this exchange though, there’s an argument about how to very precisely define those concepts.

Is Google’s success a result of harnessing a network effect? Well, it depends on whether that’s understood to mean a dynamic generated by its own users or whether  it is a more expansive, covering the structure of the Web as a whole.

Carr points out that O’Reilly described sites that leveraged network effects as ones that get better with more users. Carr responds that more people using Google doesn’t necessarily improve it. O’Reilly responds that it’s not just searchers that use Google, but websites themselves. They (or more specifically their administrators) participate merely by being indexed. But blocking Google’s spiders is opting out of something, not joining as a user. Now we have to ask where we draw the boundaries of inside the “network” that causes the “effects”–a question that impacts who we consider “users”, a question that impacts the precise definition of that word.

It might be easy to dismiss debates like this as academic. In a way they are academic but that doesn’t make them worth dismissing. These debates will determine the language and concepts that informed people use to discuss complex issues arising from new technological and social innovations on the Web.

A sophisticated terminology will only become more important as time goes on. A lot of these terms get thrown around by Web 2.0 cheerleaders without a lot of concern for precision. That’s going to have to end soon and it’s important to know what these  phrases really mean to the people thinking hardest about them.