IEEE Spectrum June, 2008 - 35

ing achievement, but it is not immediately obvious that it would launch a
new era of much faster growth, with
doubling times measured in months
or less. After all, more and more capable machines have been replacing and
aiding humans for centuries without sparking such an explosion. To
answer that objection, we've got to
start with the fundamentals: what economic theory says about growth rates.

cypress semiconductor

o keep a modern economy
thriving, we must accomplish
many mental tasks. Some people (we call them engineers)
have to design new products,
systems, and services. Other people have
to build, market, transport, distribute, and
maintain them, and so on. These myriad
tasks are mostly complements, so that
doing one task better increases the value
of doing other tasks well. But for each task,
humans and machines may also be substitutes; it can be a wasted effort to have them
both do the same task.
The relative advantages of humans
and machines vary from one task to the
next. Imagine a chart resembling a topographic cross section, with the tasks
that are "most human" forming a human
advantage curve on the higher ground.
Here you find chores best done by humans,
like gourmet cooking or elite hairdressing.
Then there is a "shore" consisting of tasks
that humans and machines are equally
able to perform and, beyond them an
"ocean" of tasks best done by machines.
When machines get cheaper or smarter
or both, the water level rises, as it were,
and the shore moves inland.
This sea change has two effects. First,
machines will substitute for humans by
taking over newly "flooded" tasks. Second,
doing machine tasks better complements
human tasks, raising the value of doing
them well. Human wages may rise or fall,
depending on which effect is stronger.
For example, in the 1920s, when the
mass-produced automobile came along,
it was produced largely by machines,
with human help. So machines dominated that function-the assembly of cars.
The resulting proliferation of machineassembled cars raised the value of related
human tasks, such as designing those
cars, because the financial stakes were
now much higher. Sure enough, automobiles raised the wages of machinists
and designers-in these cases, the complementary effect dominated. At the same
time, the automobile industry lowered the
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pay of saddle makers and stable hands, an
example of the substitution effect.
So far, machines have displaced relatively few human workers, and when
they have done so, they have in most
cases greatly raised the incomes of other
workers. That is, the complementary
effect has outweighed the substitution
effect-but this trend need not continue.
In our graph of machines and humans,
imagine that the ocean of machine tasks
reached a wide plateau. This would
happen if, for instance, machines were
almost capable enough to take on a vast
array of human jobs. For example, it
might occur if machines were on the very
cusp of human-level cognition. In this
situation, a small additional rise in sea
level would flood that plateau and push
the shoreline so far inland that a huge
number of important tasks formerly in
the human realm were now achievable
with machines. We'd expect such a wide
plateau if the cheapest smart machines
were whole-brain emulations whose relative abilities on most tasks should be
close to those of human beings.
In such a scenario, the economy would
start growing much faster, for three reasons. First, we could create capable
machines in much less time than it takes
to breed, rear, and educate new human
workers. Being able to make and retire
machine workers as fast as needed could
easily double or quadruple growth rates.
Second, the cost of computing has long
been falling much faster than the economy has been growing. When the workforce is largely composed of computers,
the cost of making workers will therefore fall at that faster rate, with all that
this entails for economic growth.
Third, as the economy begins growing
faster, computer usage and the resources
devoted to developing computers will
also grow faster. And because innovation is faster when more people use and
study something, we should expect computer performance to improve even faster
than in the past.
Together these effects seem quite
capable of producing economic doubling times much shorter than anything
the world has ever seen. And note that
this forecast does not depend on the
rate at which we achieve machine intelligence capabilities or the rate at which
the intelligence of machines increases.
Merely having computer-like machines
able to do most important mental tasks
as well as humans do seems sufficient to
produce very rapid growth.

expert View:

t.J. rodgers
WHO HE IS
Founder and CEO of Cypress
Semiconductor Corp., in San
Jose, Calif., known for his
brash opinions about the
business world and politics.
Owner of the Clos de la Tech
winery and vineyards, in
California, where he's trying
to make the best American
pinot noir.
SINGULARITY
WILL OCCUR
Never
THOUGHTS
"I don't believe in
technological singularities.
It's like extraterrestrial
life-if it were there,
we would have seen it
by now. However, I do
believe in something
that is more powerful
because it is real-namely,
exponential learning. An
exponential function has
the property that its slope
is proportional to its value.
The more we know, the
faster we can learn.
"Technological transitions
are required to maintain
an exponential rate of
learning. The first airplanes
were certainly not as
good as well-appointed
trains in moving masses
comfortably, but the
transition later proved
essential to maintaining
our progress in human
mobility. Gene splicing is a
breakthrough technology
but has not yet done (or
been allowed to do) a lot for
mankind. That will change.
"I don't believe in the good
old days. We will be freer,
more well-educated and
even smarter in the future-
but exponentially so, not as
a result of some singularity."

juNE 2008 * iEEE SpEctrum * NA

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Table of Contents for the Digital Edition of IEEE Spectrum June, 2008