Thu 18 Feb 2010
I'm not going to rehash the Google Buzz fiasco. But by this point we've learned a few interesting tidbits about how this disaster happened:
- Google rushed the product to launch, bypassing their normal testing process.
- They tested Buzz internally with their 20,000 employees, but no one sounded the privacy alarm, or perhaps no one sounded it loudly enough.
It's point #2 that's fascinating to me. When it came out, Buzz was so obviously broken to so many people, not just researchers and geeks, but many in the general public. How did 20,000 Google employees miss that? And what does that say about Google's internal culture?
I began to think about this more when I noticed a news story about how Google and other top Silicon Valley firms are claiming that the demographics of their workforces are trade secrets, refusing to release them. Really? Seems like kind of an obvious cover-up there. Google is an engineering culture, and engineers tend to be overwhelmingly white and male. And what does a white, male engineering culture get you? Buzz, apparently, and a ridiculous inattention to common sense privacy concerns.
I don't mean to bash on Google – they're far from the only company that's predominately white, male, and engineering dominated. But until now I think Google and others have played that card as an asset. They're proud of the fact that they don't have any social scientists around. They think they don't need them. There are lots of computer scientists and engineers who are now creeping into social spaces, claiming they can use massive data and computing to solve the hard problems that social scientists haven't been able to solve. Well, I call BS (a thousand times BS!), and I use Buzz as Exhibit A. I'm no longer shocked that some computer scientists can be that naive and narrow minded. But I still don't understand what's so hard about saying that we need each other. Smart at one thing != smart at everything.
So, do I think Google's internal culture will change? Not in the short term, and maybe not at all. Not unless they suddenly hire a slew of social scientists and put them in positions with real power over engineers, product direction. But I hope this Buzz experience could be the start of a slow realization that algorithms have no answers, they have no whys. They have stunningly small amounts of nuance and subtlety, which is where I'd argue real wisdom lies. And apparently they don't have much common sense either.