Unlearning
sivers.org
sivers.org
“I can't understand why people are frightened of new ideas. I'm frightened of the old ones.”
I haven't heard it before.
I wish this reasoning was more common. At least in my experience, argument-by-authority seems to be the plague on the insecurities in our industry. In reality, being labeled "an expert in X" more often than not does nothing but completely disqualify someone from being able to fairly compare X with the alternatives.
Why would you start a business selling MP3s if you thought the future of the music business was subscriptions? And vice versa.
I would say that I'm on neutral ground, being neither predominately in either industry. That said, I feel that the current method of distribution for music (CD and iTunes) is completely outdated compared to the great advances that we've seen in other areas of technology. With the drive towards users wanting free content, there has to be a way for artists to capitalize on this.
I obviously cannot wish for the world's top artist to be working for minimum-wage salaries, but seriously, there must be better ways to make money than for record companies to strong-arm individuals into paying ridiculous sums of money for "sharing" copyrighted content.
It's not as important to predict exactly as to identify key drivers, trends, and dynamics. As to the unlearning aspect, I think it's a question of letting go of internal mental constraints imposed by prior limits that have been obsoleted by new developments.
Jeff Bezos has suggested Amazon focuses on "invariants" or things that are going to continue to be true for a broad range of potential futures.
So how do you unlearn?
As for how to figure out what to unlearn, well, the metric I've been running on lately is to look at who is making predictions, and then see who is wrong in the end. Some people are right through sheer luck, of course, and some people who end up wrong are "essentially right" and ended up being wrong for no other reason than sheer bad luck, but in general it's the most useful metric I've found. Applying it to a specific case is hard, but it's worth a try. Oh, and this is slow, but then, a fast metric for this sort of thing would be suspect anyhow (prone to instability).
It turns out that once you start looking around, a lot of people are wrong about a lot of things, even some things that are conventional wisdom. It's really astonishing how few people hold themselves or others accountable for their predictions.
(Also, I'm not saying this is the only useful metric... it's just the only one I can come close to even just summarizing in a quick post, though.)
[1] http://www.overcomingbias.com/2007/07/making-beliefs.html