The manifold problems of technology forecasting


Yogi Berra and others are reported to have said that "prediction is
very hard, especially about the future."  That is true of politics,
and it is also true of technology.

While the general impression that technology forecasts are far too
optimistic is true, it is not universally true.  Yes, we don't live in
underwater cities, nor do we commute in helicopters.  However, there
are many technologies that have surprised not only the general public,
but sometimes even their inventors and promoters, with their success.
Such has been the case with wireless telephony.  Before that, computers
were also underestimated (with Ken Olsen of DEC, one of the great figures
in the development of minicomputers, famously expressing his doubts
about the need for computers in homes).  And before that, cars, and
before them railroads, also surprised with their wide spread.  In many,
even most, cases, what people do with a technology differs widely from
what inventors had in mind.

The main difficulty in technology prediction is the human factor.
What will people want to do with the wonderful gizmo you have just
invented?  Perhaps they will just turn up their noses and not do
anything with it.  Thus it should not be surprising that forecasting
in this area is difficult.  However, there are some general principles
that do apply much of the time.  One of them, quite well known, is that
the penetration of new technologies tends to follow the logistic curve,
the S-shaped curve that appears in many areas.

Another general principle, not as quantitative, nor as well known,
contradicts the general expectation that new technologies will replace
old ones.  Instead, new technologies frequently serve to strengthen their
predecessors.  (Thus, in popular language of the last few decades, they
are "sustaining" and not "disruptive.")  An excellent example is that of
railroads and horses.  The rail was expected to kill the horse.  This was
a common expectation on the part of both proponents and opponents of the
new offspring of the emerging metal and steam technologies.  Instead, the
number of horses grew.  In Britain, their numbers did not peak until 1905.
The issue was that while transport on rails was fast and inexpensive, the
"first mile" problem of getting to the rails required horses.  With the
general growth of the economy that was facilitated by railroads, there
was more and more to carry to the rails.  And even railroads used horses
extensively, for switching cars in their yards, for example.

Similar phenomena occur commonly in other settings, and often lead to
serious mistakes in planning.  How many times have you seen predictions
and promises that better communications, such as faster Internet
access, will stimulate telecommuting and decrease road congestion?
Such predictions are almost certainly wrong.  At least they have
been consistently wrong for about two centuries.  Many, often very
knowledgeable, observers, thought that transportation and communication
were substitutes for each other.  But the uniform experience to this
age has been that they are complements, and grow in parallel.  Yes,
you may work from home, but chances are that you will make more trips
to meet clients, or for family and other reasons, and in the end will
travel more than before (barring major upsets, such as an stronomical
rise in price of fuels).

So what can we conclude?  Most of all, that the future is hard to
predict, so we have to prepare for the unexpected.  Second, though,
we should keep in mind that among the most common unexpected phenomena
is the resilience of old technologies, services, and business methods,
and their propensity to adopt some of the innovations that we work on.