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3 This was the case for example, of the US space shuttle, when the risk of mission failure was originally estimated in the order of 1/5,000.
4The 9/11 commission report (2004) points to a “failure of imagination” to anticipate these attacks, given past experience and new signals.
5This was the case of the US Airways flight 1549 out of JFK, which,in January 2009, safely landed on the Hudson when it had been crippled minutes earlier by a bird strike and could not reach a close airport.
6This was also the case of the Deepwater Horizon platform, which was destroyed by explosions and fire in 2011 after close calls that should have alerted the operators and altered their course of action (NAE, 2012). Yet, neither the operators nor the regulators saw reason to intervene earlier since no accident had happened.
7 This was the case for example of the Aloha Airlines in 1988 in Hawaii where part of the airplane fuselage broke apart in an explosive decompression and peeled off exposing the inside of the plane (NTSB, 1989).
8The same is true of data selection, for instance, as mentioned earlier, the choice of the Fukushima reactor designers to ignore all tsunami data older than 1,000 years.
9That was the dilemma in managing the financial crisis of 2008, when governments were facing several options: some favored the injection of stimulus capital first then the regulation of banking reserves and others the reverse.
10Of course, additional information may also increase the uncertainties about a risk and justifyincreased safety measures.
11Aleatory uncertainties are caused by randomness. They remain even when the probability of an event is known with certainty. Epistemic uncertainty refers to imperfect basic knowledge: it is the uncertainty about the probability of an event, for example when several hypotheses are possible, when experts disagree, etc.Separating the two types of uncertainty in the display of the results as a family of risk curves is especially useful either when the analysis applies to several systems and/or over several time periods, or when the decision maker is “ambiguity averse” and epistemic uncertainties affect his/her preference function (Paté-Cornell and Davis, 1994; Paté-Cornell and Fischbeck, 1995; Paté-Cornell, 1996).
12 This was the case of the importance of the auxiliary feed-water systems inthe safety of nuclear power plants as emphasized in the first PRA’s performed for these systems (USNRC, 1975).
13The HIV retrovirus had been present in the human population for decades before it was clearly identified and researched (Gallo, 2006).
14An example is a consumer‘s decision to stir his soup with a hair dryer, together with the manufacturer’s decision not to affix a label warning against this use.