The great thing about Google is that it gives you exactly what you want. The problem with Google is that it gives you exactly what you want.
That’s what Todd Lohenry said to me a couple days ago when we were talking about managing knowledge, how to build expertise, and how to be recognised as an expert – three things he’s thought about a lot. And he’s got a point.
He has developed a method for handling a lot of incoming information that he calls the e1evation workflow. This is a clever system for finding, processing and sharing high-quality information.
The issue that he’s grappling with though, is how do you identify the areas that you need to know about? The problem is that search engines give you precisely what you ask for – and only that. So how can you tell if there is an important area of knowledge that relates to your specialty about which you’re unaware? A search won’t tell you.
There is a parallel here with the concept of T-Shaped skills – something that Ralph Ohr brought up in his first guest post here.
He quoted Nicholas Donofrio, who said:
The kind of people who will be best able to seize these opportunities are those I call “T-shaped” as opposed to “I-shaped.” I-shaped people have great credentials, great educations, and deep knowledge – deep but narrow. The geniuses who win Nobel prizes are “I-shaped,” as are most of the best engineers and scientists. But the revolutionaries who have driven most recent innovation and who will drive nearly all of it in the future are “T-shaped.” That is, they have their specialties – areas of deep expertise – but on top of that they boast a solid breadth, an umbrella if you will, of wide-ranging knowledge and interests. It is the ability to work in an interdisciplinary fashion and to see how different ideas, sectors, people, and markets connect. Natural-born “T’s are perhaps rare, but I believe people can be trained to be T-shaped. One problem is that our educational system is still intent on training more “I’s. We need to change that.
Google is an I-Shaped search engine – it goes very deep, but it isn’t broad. How do we get the breadth we need here?
This is another people-tech interaction issue. You can map the history of search using the matrix I’ve talked about before – by analysing where the intelligence sits in the system:
When the web started, there wasn’t much in the way of search. There was no systematic method for finding things, and no technology to support looking for stuff either – dumb tech and dumb people.
Then we had the first tools for searching the web – things like yahoo and lycos. These indices were compiled by hand, and put into categories by people using judgement. This was smart people with dumb tech. The problem with this approach is that it works fine when there are 32,000 websites to catalog, but it breaks when there are millions.
Enter google. With this, all of the intelligence is placed in the tech – the action is in the algorithm. The early search sites were hyphens, and the algorithm-driven ones are i-shaped. It’s possible that algorithms may eventually solve this problem. Bottlenose is a tool that is moving in this direction. And of course, once we hit the singularity, then it’s not an issue! Terri Griffith pointed me to Avogadro Corp, a book that outlines how this could happen. I’m still not sure if the outcome is really cool, or terrifying…
I think that to get to t-shaped search, we need to combine algorithmic filtering with some form of judgement-based filtering. That’s what gets us up into the corner with smart people using smart technology. Right now, we don’t know what will do the job – but solving this will trigger more disruption, and probably will make a bunch of money too.
Of course, it’s probably not enough to target a big disruption. If it were me, I’d be looking at problems that require t-shaped data to solve. Those are the most interesting ones around these days anyway.The solution will most likely come from someone experimenting around the edges. Larry Page and Sergei Brin weren’t trying to destroy yahoo and lycos when they started out – they just wanted to catalog books in libraries.
Solve a similar problem now, and you might solve the problem with Google.