Page 291 - Mechanical Engineers' Handbook (Volume 2)

282 Analysis, Design, and Information Processing

A definitive discussion of debiasing methods for hindsight and overconfidence is presented
by Fischhoff, a definitive chapter in an excellent edited work. He suggests identifying faulty
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judges, faulty tasks, and mismatches between judges and tasks. Strategies for each of these
situations are given.
Not everyone agrees with the conclusions just reached about cognitive human infor-
mation processing and inferential behavior. Several arguments have been advanced for a
decidedly less pessimistic view of human inference and decision. Jonathan Cohen, 23,24 for
example, argues that all of this research is based upon a conventional model for probabilistic
reasoning, which Cohen calls the ‘‘Pascalian’’ probability calculus. He expresses the view
that human behavior does not appear ‘‘biased’’ at all when it is viewed in terms of other
equally appropriate schemes for probabilistic reasoning, such as his own ‘‘inductive proba-
bility’’ system. Cohen states that human irrationality can never be demonstrated in laboratory
experiments, especially experiments based upon the use of what he calls ‘‘probabilistic co-
nundrums.’’
There are a number of other contrasting viewpoints as well. In their definitive study of
behavioral and normative decision analysis, von Winterfeld and Edwards 25 refer to these
information-processing biases as ‘‘cognitive illusions.’’ They indicate that there are four fun-
damental elements to every cognitive illusion:
1. A formal operational rule that determines the correct solution to an intellectual
question
2. An intellectual question that almost invariably includes all of the information required
to obtain the correct answer through use of the formal rule
3. A human judgment, generally made without the use of these analytical tools, that is
intended to answer the posed question
4. A systematic and generally large and unforgivable discrepancy between the correct
answer and the human judgment
They also, as does Phillips, describe some of the ways in which subjects might have been
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put at a disadvantage in this research on cognitive heuristics and information-processing
biases. Much of this centers around the fact that the subjects have little experiential famil-
iarity with the tasks that they are asked to perform. It is suggested that as inference tasks
are decomposed and better structured, it is very likely that a large number of information-
processing biases will disappear. Thus, concern should be expressed about the structuring of
inference and decision problems and the learning that is reflected by revisions of problem
structure in the light of new knowledge. In any case, there is strong evidence that humans
are very strongly motivated to understand, to cope with, and to improve themselves and the
environment in which they function. One of the purposes of systems engineering is to aid
in this effort.

4.4 Interpretation
While there are a number of fundamental limitations to systems engineering efforts to assist
in bettering the quality of human judgment, choice, decisions, and designs, there are also a
number of desirable activities. These have resulted in several important holistic approaches
that provide formal assistance in the evaluation and interpretation of the impacts of alter-
natives, including the following:
• Decision analysis, which is a very general approach to option evaluation and selection,
involves identification of action alternatives and possible consequence identification
of the probabilities of these consequences, identification of the valuation placed by
the decision-maker on these consequences, computation of the expected utilities of