Multi-credentialing

John Maeda of RISD has a riff about the future of college credentials, including the notion of an automated ‘degree’, which is generated by a machine based on the sum your achievements. He makes an analogy to Coinstar: pour in a bunch of individually valuable stuff, get out some paper which aggregates its value.

It’s not that crazy of an idea; it only sounds crazy because we are using our current terminology of credentials as a certificate of education.

A degree from Stanford has value because it is considered a predictor of ability. But it’s only that: a predictor, whose accuracy one takes on faith. I recall seeing studies indicating that one’s school is only a predictor of success early in one’s career; that in less than ten years, one’s alma mater is no longer detectable as a signal. [cite?]

So in that case, the diploma is a relatively weak predictor. In blunt terms, sure, 90% of the population could not get a Stanford BA. But those that do, might or might accomplish what one expects.

What if institutional credentials were empirical? Stanford and MIT could offer such credentials, based on their own emphases and models. A person could then have several ‘degrees’ from Harvard, Princeton and Caltech, as one’s accomplishment is used as an input into their respective models.

Which of course leads one to ask what a ‘degree’ is? As it stands now, it’s a _cred_ential, in that it communicates that one can _cred_ibly hope that your fresh new hire will do good work. But it is only weakly empirical. ‘Credibility’ is a loose idea that one falls back on in the absence of predictive data.

Imagine a better system, where Stanford, MIT and Carnegie-Mellon compete for predictive strength of their credentialing models. Where they forecast your success at age 20, revisit it when you turn 30, and open source the results.

Our current higher-educational institutions might serve that role, but it’s not what they do right now. If they’re smart, they’ll consider moving in that direction, or see themselves disrupted by nimbler, more-empirical, more-credible rivals.

Published October 28, 2013