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56 CH 4 ENGINEERING THE EARTH: MAKING DECISIONS UNDER UNCERTAINTY
of a group-based decision making process. How does an individual or an organization
know whether they are making a good decision at the time they are making that decision
(without the benefit of hindsight)? The question therefore begs: “Would you know a good
decision if you saw one?” Well, it depends. Without any field specific knowledge one
could be inclined to define decision making as “choosing between many alternatives that
best fit your goals.” However, the evident questions then are (1) how to define what is
best or optimal, one needs some criterion and the decision may change if this criterion
changes, and (2) what are your stated goals? Decision analysis theory provides sound
scientific tools for addressing these questions in a structured, repeatable way.
Uncertainty has an important role in making sound decisions. The existence of un-
certainty does not preclude one from making a decision. In fact, decision making under
uncertainty is the norm for most decisions of consequence. For example, in the personal
realm you already have experienced decision making under uncertainty when you went
through the college application process. Most readers of this book probably applied to
several colleges because there was uncertainty on gaining admission to the college of
one’s choice. Similarly, universities make offers to more students than they can accom-
modate because there is uncertainty on how many students will accept their offer. Uni-
versities often rely on historical data on acceptance rates to decide how many offers to
make. However, there is uncertainty because the past is not usually a “perfect” predic-
tor of the future. Universities develop other tools to deal with uncertainty, such as “early
acceptance” and “wait lists,” to provide a higher certainty that the university will not get
more acceptances than it can accommodate.
Decisions can be made without knowing the hard facts, an exact number, perfect in-
formation. In fact, uncertainty is often an integral part of decision making, not some
afterthought. One shouldn’t make a decision first and then question, what if this and
that event were to be uncertain? How would that affect my decision? Decision mak-
ing and uncertainty modeling are integral and synergetic processes, not a sequential set
of steps. Building realistic models of uncertainty, in the context of decision making is
what this book is about. Certainly in engineering application, no model of uncertainty
is relevant or even useful without a decision goal in mind. This is what this chapter
is about.
In most meaningful circumstances, a decision can be defined as a conscious, irrevo-
cable allocation of resources to achieve desired objectives. This definition very much
applies to any type of geo-engineering situation. The decision to drill a well, clean up a
site, construct aquifer storage and recovery facilities requires a clear commitment of re-
sources. One may go even to a higher level and consider policy making by government or
organizations as designed to affect decisions to achieve a certain objective. For example,
energy legislation that implements a tax on carbon can impact commitment of resources
as related to energy supply, energy conservation, carbon capture technology solutions.
The 10-point program in Figure 1.1 outlines clear objectives that will require allocation
of resources to make this happen.
At Stanford University, Professor Ron Howard has been a leader in the field of de-
cision analysis since 1966. He described this field as a “systematic procedure for trans-
forming opaque decision problems into transparent decision problems by a sequence of