Race Against The Machine is a very interesting book. It’s gotten a lot of popularity
because it’s targeting an issue that is front and center for a lot of people in the
United States and around the world, namely the issue of jobs creation and unemployment.
Essentially, the thesis of the book – the authors Erik Brynjolfsson and Andrew McAfee
make the point that their goal is to introduce technology as a key engine of the changes
that we’re looking at in terms of unemployment and job creation.
So the book really focuses very heavily on the pace of technology innovation, at one
level highlighting the exponential improvement in price and performance of technologies, but
then focuses on the impact that has in terms of increasingly taking away jobs through automation,
that more and more jobs, jobs that we thought were going to be immune from automation, are
increasingly becoming vulnerable to automation because of the power of technology.
At that level, I think it’s a very powerful book. Technology is advancing at a very
rapid pace and it is becoming more and more able to take over activities that we, as humans,
have been performing. I think the issue is, though, by framing the challenge as a
technology challenge, what they miss is the reason why these jobs are so vulnerable to
technology. Essentially, if you step back and look at
what the modern corporation is and how it evolved, it evolved through a model that we
describe as a “push model.” Basically, it has to do with developing forecasts and
predictions and then making sure that the right people are in the right place at the
right time and following tightly scripted activities to respond to that demand.
In stepping back from that, that’s a formula for automation. If you have tightly scripted
jobs that are highly standardized where there’s no room for individual initiative or creativity,
machines by and large can do those kinds of activities much better than human beings.
They’re much more predictable. They’re much more reliable. We as human beings have
flaws. We tend to get distracted. We tend to go off into unexpected areas.
So I think that the real reason that we have such an issue in terms of unemployment and
job loss through automation is that we’ve crafted these jobs exactly so that they would
be vulnerable to automation. We’ve put kind of a bull’s eye target on workers around
the United States and around the world and said, “Come after me. Shoot me. I’m
the target for automation.” Technology’s not the root cause. Technology is simply
going after the target that’s been put on the screen.
The root cause is how we’ve defined work in companies and that the opportunity now
is to step back and say, “Is that the way we need work to be done?” One of the
issues is this formula for how work is conducted was developed in the last century, and it
was based on a set of infrastructures and assumption of a stable environment that made
it easy to define standardized highly-scripted work.
Now we’re in a world that’s more rapidly changing, more uncertainty, more of those
extreme events that Taleb calls the "black swans" that make it really critical for us
as individuals in the workplace to take much more initiative, to be constantly exercising
creativity and imagination to respond to the unexpected events. That’s a very different
model of work. It requires a very different way of organizing our institutions and a different
set of work practices that are much harder to automate.
When you have that kind of imagination, creativity, trust-based relationships that are required
to really address these hard problems, it makes it much less vulnerable to that kind
of automation. So my belief is that if you focus on that as the root cause, now the problem
is not technology. The problem is how do we innovate our institutions and our work
practices so that we, in fact, can – the authors have a very nice phrase that they
call rather than “race against the machines,” we ought to start “racing with the machine.”
Unfortunately, I don’t think they developed that very well in the book. They kind of
offer it as a case for optimism at the very end without a lot of deep content, but the
content I think about racing with the machine is stepping back and reassessing what are
institutions for? What kinds of work practices are required in order to pursue that institutional
mission? And in that context, I think you now are able to race with the machine.