Innovations, Energy for Change, Fall 2009.pdf - Renewable and ...

Vinod Khosla
Figure 4. Hypothetical Scenario of Required Per-Capita Carbon Emissions
Trends
Developing technology to allow for rapid response is critical but we must also
allow for a rapid, maybe even automatic, policy response.
FORECASTING, AND BLACK SWANS
Forecasting is an inexact science—as multiple examples over the years have shown.
In particular, much economic forecasting is essentially a regression of old data; it
cannot account for technological evolution, shifts, and shocks because these cannot
be predicted. One of the more famous examples is McKinsey’s 1980 estimation
of the mobile phone market in 2000 for AT&T: it forecast a market size of approximately
1 million phones. The actual market in 2000 exceeded 100 million—an
error by a factor of 100. Similarly, the Energy Outlook Retrospective from the
Energy Information Administration (EIA) noted that on average, its forecast of
average oil prices had been off by 52%; natural gas prices were off by 64%, and coal
prices were off by 47%. 9 The fundamental problems here are those of forecasting:
gaining false precision at the expense of accuracy, obscuring underlying assumptions,
and inputting what is measureable while ignoring what is not. Furthermore,
most forecasts fail to recognize that extreme events with high unpredictability are
responsible for most of society’s evolutions—what author Nicholas Nassim Taleb
calls a “Black Swan.” Three features characterize a Black Swan event:
30 innovations / fall 2009