We define risk as representing any situation where some events are not known with certainty. This means that the prospects for risk are prevalent. In fact, it is hard to consider any situation where risk does not play a role. Risk can relate to weather outcomes (e.g., whether it will rain tomorrow), health outcomes (e.g., whether you will catch the flu tomorrow), time allocation outcomes (e.g., whether you will get a new job next year), market outcomes (e.g., whether the price of wheat will rise next week), or monetary outcomes (e.g., whether you will win the lottery tomorrow). It can also relate to events that are relatively rare (e.g., whether an earthquake will occur next month in a particular location, or whether a volcano will erupt next year). The list of risky events is thus extremely long. First, this creates a significant challenge to measure risky events. Indeed, how can we measure what we do not know for sure? Second, given that the number of risky events is very large, is it realistic to think that risk can be measured? In this chapter, we address these questions. We review the progress that has been made evaluating risk. In particular, we review how probability theory provides a formal representation of risk, which greatly contributes to the measurement of risk events. We also reflect on the challenges associated with risk assessment.

Before we proceed, it will be useful to clarify the meaning of two terms: risk and uncertainty. Are these...