Modern society attempts to predict all manner of future events, from
hurricane tracks to oil price trends to asteroid impacts - in order better
to prepare for them. Growing capabilities in science and technology - especially
the ability of computers to rapidly process massive amounts of data - underlie
these efforts to foretell the future. Thus, it is no surprise that scientists,
policy makers, and issue advocates have together concluded that the primary
response to human-caused global climate change - popularly called "global
warming" - should be based on an assumption that scientific research can
accurately predict various climate futures. Alternative emissions scenarios
differentiate these various projections. A further assumption is that more
research can reduce uncertainty in climate change predictions and thus
drive a political consensus on needed action to prevent future climate
impacts on environment and society. Based on these assumptions the U.S.
Congress has appropriated in the past decade more than $20 billion to reduce
uncertainty through improved predictions. This talk examines the assumptions
of prediction and prevention that underlie the present response to climate
change and suggests that they are flawed, and perhaps even leading to climate
policies destined to fail. The talk suggests an alternative approach to
responding to climate change, and the resulting implications for science,
policy, and issue advocacy.