We’re in an age where the old institutions are being eaten away from below. They look solid, undefeatable, until they suddenly collapse. The music industry has been fun to watch, the newspapers too. Who’s next?
There are many, many candidates. Here I just want to talk a bit more about Universities, which I think are currently in trouble, what with a higher education bubble, $99/month online universities with credentialing, free online video learning as championed by the Khan Academy, and now a free online AI course from the world’s best researchers via Stanford with some credentialling with 58,000 signups and counting.
Old economy industries are vertically integrated hierarchies rooted in high transaction costs, which tend to be geographically replicated (X many in each city).
One part of why they fall apart is that the cost of being hierarchical and vertical no longer pays, because all the separate pieces of value become able to stand on their own. Usually, there is one thing they do which provides all the revenue for the rest, and when that goes, the industry falls.
For the music industry, it was people buying cheap-to-produce media for high markup. Piracy was the scape goat, but iTunes really smashed them. For the newspapers, it was the demise of classified ads (most famously in the US this was replaced by Craigslist, who destroy a billion in newspaper revenue for every million they make).
For universities, it’s undergraduate degrees; these are about milking the middle class to pay for all the other things a uni does. We’d like to think it all goes on cutting edge research, and maybe some of it even does.
The other part of why they fall is when new solutions turn up that make geographic replication pointless. Examples include CD and DVD stores vs iTunes, local newspapers and their classified ads vs Craigslist/ebay/all the rest of the commercial ‘net, and bookstores vs Amazon et al.
For universities, geographical replication is standard, but all the new competing forms exist online. That competition is in two major camps: upstarts, and the top unis (Stanford, MIT, etc). What happens when geographical replication fails, is that the institutions with value propositions other than locality (eg: excellence, status, uniqueness) can dominate, but all the others fail. That’s what why MIT OCW works; accelerating the geographic replication decline pays for the survivors.
I’m interested here, though, in one of the de-integration aspects of this process, as they relate to universities. As far as I can see, unis provide students roughly these pieces of value:
- learning (largely replaceable with free online content / study guides)
- networking (replaceable online, in fact a lot of why nerds built the net in the first place)
- credentialing – this is still the hard one
Credentialing is the force behind the higher education bubble. People pay more and more to get that piece of paper. It’s an unjustifiable, unproductive, exploitative money pump. If you could route around that, you’d blow this industry to pieces.
Now one way to split credentialing off from the rest of the concerns of “education” is to provide something like “recognition for prior learning”. All kinds of institutions, like TAFE in Australia, or like lots of little accreditation bodies, dabble in this already. But, it’s tough; you have to test people rigorously to figure out if they deserve a credential or not, and you can easily make mistakes. That’s why we prefer the Unis, because we know the person had to more or less sit through X many years of study, so there’s some minimal learning assumable even if everything else fails.
But I’m wondering, can we crowdsource credentialing?
Take a social network, or even better a professional network like LinkedIn. Let people just add “qualifications” they have (“skills”? Is there a more appropriate word?). Then, crucially, get others to rate them.
To make this work, you need some kind of credibility rating for the raters. Credibility should be domain specific, and also person specific:
- if the rater is an expert in field X, they have higher credibility in field X
- if the rater has worked closely with person Y, they have higher credibility with respect to rating person Y
But also, a rater should have a general credibility factor – do their ratings match reality, or are they bullshitters? Maybe higher for more ratings, lower for ratings outside area of expertise, modified by how much their ratings match other people’s ratings in the context, maybe lowered for complaints registered about them.
How do we know you’ve worked closely with someone? It’s on the resume. Hard to game this without it being very visible. How do we know you’re an expert in X? Because of your highly rated “skills” in X, calculated as above. And so the loop closes.
The resulting skills above aren’t really credentials per se; they’re a little fuzzier than that. However, we don’t *actually* want credentials. We want a way to pick the best person for the job from a crowd, or determine whether a given person is capable of some given thing. This approach potentially works better than credentials.
That’s all I’ve got for now. I’d love to hear more thoughts on this.
(Massive credit to my darling wife; this emerged from a Saturday morning coffee conversation.)