Good Enough

Time is short this week, so just a quick pointer towards an old Collision Detection post in which Clive Thompson talks about iPods and briefly digresses into some differences between Apple and Microsoft computers:

Back in the early days of Macintoshes, Apple engineers would reportedly get into arguments with Steve Jobs about creating ports to allow people to add RAM to their Macs. The engineers thought it would be a good idea; Jobs said no, because he didn’t want anyone opening up a Mac. He’d rather they just throw out their Mac when they needed new RAM, and buy a new one.

Of course, we know who won this battle. The “Wintel” PC won: The computer that let anyone throw in a new component, new RAM, or a new peripheral when they wanted their computer to do something new. Okay, Mac fans, I know, I know: PCs also “won” unfairly because Bill Gates abused his monopoly with Windows. Fair enough.

But the fact is, as Hill notes, PCs never aimed at being perfect, pristine boxes like Macintoshes. They settled for being “good enough” — under the assumption that it was up to the users to tweak or adjust the PC if they needed it to do something else.

The concept of being “good enough” presents a few interesting dynamics that I’ve been considering a lot lately. One problem is, of course, how do you know what’s “good enough” and what’s just a piece of crap? Another interesting thing about the above anecdote is that “good enough” boils down to something that’s customizable.

One thing I’ve been thinking about a lot lately is that some problems aren’t meant to have perfect solutions. I see a lot talk about problems that are incredibly complex as if they really aren’t that complex. Everyone is trying to “solve” these problems, but as I’ve noted many times, we don’t so much solve problems as we trade one set of problems for another (with the hope that the new set of problems is more favorable than the old). As Michael Crichton noted in a recent speech on Complexity:

…one important assumption most people make is the assumption of linearity, in a world that is largely non-linear. … Our human predisposition treat all systems as linear when they are not. A linear system is a rocket flying to Mars. Or a cannonball fired from a canon. Its behavior is quite easily described mathematically. A complex system is water gurgling over rocks, or air flowing over a bird’s wing. Here the mathematics are complicated, and in fact no understanding of these systems was possible until the widespread availability of computers.

Everyone seems to expect a simple, linear solution to many of the complex problems we face, but I’m not sure such a thing is really possible. I think perhaps what we’re looking for is a Nonesuch Beast; it doesn’t exist. What are these problems? I think one such problem is the environment, as mentioned in Crichton’s speech, but there are really tons of other problems. The Nonesuch Beast article above mentions a few scenarios, all of which I’m familiar with because of my job: Documenation and Metrics. One problem I often talk about on this blog is the need for better information analysis, and if all my longwinded talk on the subject hasn’t convinced you yet, I don’t think there’s any simple solution to the problem.

As such, we have to settle for systems that are “good enough” like Wikipedia and Google. As Shamus Young notes in response to my posts last week, “deciding what is ‘good enough’ is a bit abstract: It depends on what you want to do with the emergent data, and what your standards are for usefulness.” Indeed, and it really depends on the individual using the system. Wikipedia, though, is really just a specific example of the “good enough” wiki system, which can be used for any number of applications. As I mentioned last week, Wikipedia has run into some issues because people expect an encyclopedia to be accurate, but other wiki systems don’t necessarily suffer from the same issues.

I think Wiki systems belong to a certain class of applications that are so generic, simple, and easy to use that people want to use it for all sorts of specialized purposes. Another application that fits this mold is Excel. Excel is an incredibly powerful application, but it’s generic and simple enough that people use it to create all sorts of ad hoc applications that take advantage of some of the latent power in Excel. I look around my office, and I see people using Excel in many varied ways, some of which are not obvious uses of a spreadsheet program. I think we’re going to see something similar with Wikis in the future (though Wikis may be used for different problems like documentation and collaboration). All this despite Wiki’s obvious and substantial drawbacks. Wikis aren’t “the solution” but they might be “good enough” for now.

Well, that turned out to be longer than I thought. There’s a lot more to discuss here, but it will have to wait… another busy week approaches.