BoundedRationality_TheAdaptiveToolbox.pdf

110 Gary Klein
reasonable level. The point is to find the right answer. The concept of optimization
may not be meaningful for mathematics or logic, where the solution is either
correct or incorrect, not optimal versus nonoptimal. Questions of fact do permit
optimization (e.g., the third longest river in the world, the empty weight of a
Boeing 757 aircraft) because the accuracy of the answer can be scaled.
Questions of value do not permit optimization. If I have three job offers and
need to select one, I cannot optimize because there is no way to demonstrate
whether I have made the optimal choice. I can use some form of decision analysis
to compare the options. However, methods such as multiattribute utility analysis
do not address the difficulty of generating options (perhaps I should
continue to seek more job offers rather than settling for these three). They do not
help me find accurate values for the evaluation dimensions I select or the ratings
I assign.
2. The decision maker's values must be stable. For researchers such as
Fischhoff (1991), Slovic (1995), and March (1978), this is a troubling require
ment. If values are not stable, then the exercise of decision analysis loses much
of its force. The choice made at time^ (e.g., which of three job offers to accept)
will not necessarily match the choice at time,4 plus one hour. Fischhoff s reading
of the data is that values are labile, rather than stable. If that is true, then one's
choice will vary depending on one's mood, and, in the worst case, one's values
at the end of a long session of decision analysis may depart from one's values at
the beginning, calling the whole analysis into question. We might try to salvage
things by suggesting that the session was successful in helping the person clarify
values, but, whether or not this was true, it is not the same thing as helping the
person make the optimal choice.
March goes further. He is concerned about the need to generate accurate predictions
of future states but is even more concerned about the stability of future
tastes. Optimization assumes that tastes and values are absolute, relevant, stable,
consistent, and precise. Experience suggests that these assumptions are unrealistic.
The difficulty may be in the concept of "values" as decomposable elements
of a decision analysis equation.
Further, if we do not trust decision makers to select an option directly, without
decomposition, because we do not trust these judgments, why would the
smaller judgments of value for each option on each evaluation dimension be any
more reliable? The advantage gained by decomposing the problem into smaller
units is to reduce the cognitive complexity of the task, but this advantage may be
canceled because the task of rating options on evaluation dimensions is less
practiced.
3. The situation must be stable. Pitz (1992) has noted that decision analysis
is not suited for decisions that dynamically adapt, such as the hedge clipping described
by Connolly (1988). Connolly contrasted hedge clipping, in which we
make each cut on the basis of the results of the previous cut, to tree felling, in
which we decide in advance how to cut down the entire tree. In practice, if