Every once in a while—and maybe more often than I’d like to admit—I re-read Clay Shirky. Today, I re-read “Ontology Is Overrated.”
And today, I’m ready to disagree with it around the margins.
On fortune telling. Yes, Shirky’s correct that we will sometimes mis-predict the future, as when we infer that some text about Dresden is also about East Germany and will be forever. But, no, that doesn’t have to be a very strong reason for us not to have some lightweight ontology that then inferred something about a city and its country. We can just change the ontology when the Berlin Wall falls. It’s much easier than re-shelving books, after all; it’s just rewriting a little OWL.
On mind reading. Yes, Shirky’s correct that we will lose some signal—or increase entropy—when we mistake the degree to which users agree and mistakenly collapse categories. And, yes, it might be generally true about the world that we tend to “underestimate the loss from erasing difference of expression” and “overestimate loss from the lack of a thesaurus.” But it doesn’t have to be that way, and for two reasons.
First, why can’t we just get our estimations tuned? I’d think that the presumption would be that we could at least give a go and, otherwise, that the burden of demonstrating that we just cannot for some really deep reason falls on Shirky.
Second, we don’t actually need to collapse categories; we just need to build web services that recognize synonymy—and don’t shove them down our users’ throats. I take it to be a fact about the world that there are a non-trivial number of people in the world for whom ‘film’ and ‘movies’ and ‘cinema’ are just about perfect synonyms. At the risk of revealing some pretty embarrassing philistinism, I offer that I’m one of them, and I want my web service to let me know that I might care about this thing called ‘cinema’ when I show an interest in ‘film’ or ‘movies.’ I agree with Shirky that we can do this based solely on the fact that “tag overlap is in the system” while “the tag semantics are in the users” only. But why not also make put the semantics in the machine? Ultimately, both are amenable to probabilistic logic.
Google showed it is the very best at serving us information when we know we care about something fuzzy and obscure—like “obstreperous minnesota.” I don’t think Shirky would dispute this, but it’s important to bear in mind that we also want our web services to serve us really well when we don’t know we care about something (see especially Daniel Tunkelang on HCIR (@dtunkelang)). That something might be fuzzy or specific, obscure or popular, subject to disagreement or perfectly unambiguous.
People and organizations tend to be unambiguous. No one says this fine fellow Clay Shirky (@cshirky) is actually Jay Rosen (@jayrosen_nyu). That would be such a strange statement that many people wouldn’t even understand it in order to declare it false. No one says the National Basketball Association means the National Football League them. Or if someone were to say that J.P. Morgan is the same company as Morgan Stanley, we could correct him and explain how they’re similar but not identical.
Some facts about people and organization can be unambiguous some of the time, too. Someone could argue that President Obama’s profession is sports, but we could correct her and explain how it’s actually politics, which maybe sometimes works metaphorically like sports. That doesn’t mean that Obama doesn’t like basketball or that no one will ever talk about him in the context of basketball. There may be more than a few contexts in which many people think it makes little sense to think of him as a politician, like when he’s playing a game of pick-up ball. But I think we can infer pretty well ex ante that it makes lots of sense to think of Obama as a politician when he’s giving a big televised speech, signing legislation, or meeting with foreign leaders. After all, what’s the likelihood that Silvio Berlusconi or Hu Jintao would let himself get schooled on the court? Context isn’t always that dependent.