Andrew McAfee on Industrial Disruption

There are a lot of jobs and a lot of
tasks right now that do some combination of communication and pattern matching. And for me, that’s everybody from a radiologist, and a cardiologist, to a financial adviser, and an accountant. Down toward lower on the educational ladder, a customer service rep. We throw a lot of human labor at all those tasks right now, because up until quite recently, technology was not any good at them. Right? Throughout all of human history, if you wanted to listen to me
talking about this rate, figure out what I was talking about, figure out if I had
a question or a request, and try to satisfy that question or request. You had no alternative except to involve a human being in that. You did not have an alternative. Right now you have a decent alternative. That alternative is getting
better very, very quickly. And it will never be perfect. Human speech is really,
really weird and complex, but it’s striking how good
it’s getting very quickly. Also, we continue to learn that even in insanely complicated environments the machine learning systems are actually better than we are at teasing
out really weird, really subtle patterns, and doing the right thing based on that
pattern detection ability. That applies to a lot of jobs,
a lot of parts of the economy. So I do think even in the timeframe that you brought up,
which is five years, thanks to the cloud, and thanks to the fact that
we all carry around devices, you know, super computers in our pocket, these technology is going
to diffuse pretty quickly. And, I’m not saying that we’re gonna enter
an era of mass tech induced unemployment because I don’t think that’s the case, but I do think we’re
going to see an acceleration of what’s already going on, which is a whole
lot of creative destruction. Which is a whole lot of industries, companies, jobs, tasks being changed. And in some cases eliminated
by new technologies, and other ones cropping up. So I just think we’re going to see
a higher rate of churn, out there. The business history tells us that when a big technology transition happens, the companies that are on top
at the start of that transition, are not usually the ones
on top at the end of that transition. And I think we’re gonna
see that movie over again. I try to not go around just
instilling fear into business leaders, but when I talk to leaders
of incumbent organizations, I say guys, listen.
The pattern through history is really clear. What are you gonna do
to not be another data point in that history about smart, well-run companies that couldn’t execute the transition. That’s part of the reason that
Eric and I wrote our most recent book called “Machine Platform Crowd” is to, kind of,
provide some manual for disruption to business leaders out there. But even if you have the playbook, and maybe this is the playbook,
and maybe it’s not. Man, changing a big organization is incredibly difficult to do. Especially when it,
and all the people in it grew up in one technology regime. Just getting them to see
how different things are. It is a full on leadership task.

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