Abstract
Random variables are commonly used to model unknown quantities, including the full gamut of risks, in the physical world. However, this generally is done without either a formal definition of randomness or even a convincing demonstration that truly random processes actually exist. Another source of mystery—the conspicuous analogy between randomness as the uncertainty of the outside world and free will as the uncertainty of the mind—offers the possibility that an understanding of randomness can offer an instructive glimpse into the fundamental principles of human behavior and ethics. This chapter considers the first of several challenges to a science of risk by addressing the subtleties and limitations associated with an understanding of randomness. It examines two types of uncertainty: knowable complexity (KC) and unknowable complexity (UC). It argues that no systematic approach to the study of randomness can ever: (1) confirm a source of uncertainty as UC; or (2) confirm some sources of uncertainty as KC without inevitably creating type-2 errors in other contexts.
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