252
15 Risk-Informed Decision Making
Tolerance
Fig. 15.9 The blue squares represent for each dam the C max and the pessimistic probabilities of
failure (p fMax and C max ). Corporate tolerance is displayed in orange
• Dam 3 (tolerable) would be mitigated before the interdependence of Dam 2 on
Dam 3, which has an intolerable portion of risk, despite its probability being two
orders of magnitude lower.
From the above we note that risks, and in particular risk prioritizations, cannot be
defined by gut-feeling and intuition. The reason is simple: our human brain already
has enough trouble understanding the simultaneous effect of two parameters (i.e.,
probability of failure and cost of consequences) and the introduction of a third vital
one (the tolerance) certainly does not help the brain to make optimal decisions. Thus,
it is paramount to use rational approaches like the one discussed in this book to make
decisions involving risks, even for simple portfolios of four dams such as the one
discussed here, where decisions seem obvious!
The phenomenon, highlighted in (Kahneman and Tversky 1979), is the “availability
heuristic”. It is one of the very well-known cognitive biases that plague us humans
when we are confronted with decisions under uncertainty. The root cause of these
biases are prejudices and misconceptions. Indeed, we often assess the probability or
the magnitude, of an event by asking ourselves if there are “cognitively available”
examples. Those are readily available through memory as Daniel Kahneman (Nobel
Prize in Economics) and Amos Tversky demonstrated in a series of papers published
between 1971 and 1984.
Given the legal aspects linked to tailings dams failures, while staying away from
any legal discussion, we note that Figs. 15.9 and 15.10 become a powerful tool for
the so-called test of negligence and decision making. Below is a summary of the test
of negligence as practiced in various countries around the world.
15 Risk-Informed Decision Making
Tolerance
Fig. 15.9 The blue squares represent for each dam the C max and the pessimistic probabilities of
failure (p fMax and C max ). Corporate tolerance is displayed in orange
• Dam 3 (tolerable) would be mitigated before the interdependence of Dam 2 on
Dam 3, which has an intolerable portion of risk, despite its probability being two
orders of magnitude lower.
From the above we note that risks, and in particular risk prioritizations, cannot be
defined by gut-feeling and intuition. The reason is simple: our human brain already
has enough trouble understanding the simultaneous effect of two parameters (i.e.,
probability of failure and cost of consequences) and the introduction of a third vital
one (the tolerance) certainly does not help the brain to make optimal decisions. Thus,
it is paramount to use rational approaches like the one discussed in this book to make
decisions involving risks, even for simple portfolios of four dams such as the one
discussed here, where decisions seem obvious!
The phenomenon, highlighted in (Kahneman and Tversky 1979), is the “availability
heuristic”. It is one of the very well-known cognitive biases that plague us humans
when we are confronted with decisions under uncertainty. The root cause of these
biases are prejudices and misconceptions. Indeed, we often assess the probability or
the magnitude, of an event by asking ourselves if there are “cognitively available”
examples. Those are readily available through memory as Daniel Kahneman (Nobel
Prize in Economics) and Amos Tversky demonstrated in a series of papers published
between 1971 and 1984.
Given the legal aspects linked to tailings dams failures, while staying away from
any legal discussion, we note that Figs. 15.9 and 15.10 become a powerful tool for
the so-called test of negligence and decision making. Below is a summary of the test
of negligence as practiced in various countries around the world.