This multiplicity of meanings would have likely vexed Frank Knight, whose 1921 book Risk, Uncertainty, and Profit argued that risk that differed from uncertainty or hazard on account of being calculable. ‘The essential fact is that “risk” means in some cases a quantity susceptible of measurement’, he wrote, drawing on the example of a champagne producer who knows that a certain percentage of bottles will break during production. Because the risk of breakage is predictable and quantifiable, its associated costs can be passed along to the consumer alongside other expenses, like labor (Knight Citation1921, 19–20). Uncertainty, on the other hand, involved that about which ‘the conception of an objectively measurable probability or chance is simply inapplicable’ (231). This was a distinction that John Maynard Keynes echoed both his Treatise on Probability (1921) and his comments on The General Theory: ‘About these matters [e.g. the price of copper in twenty years time] there is no scientific basis on which to form any calculable probability whatsoever. We simply do not know’ (Keynes Citation1937, 214).
A century later, it is evident that Knight’s narrow definition of risk has been largely overtaken by a more expansive, and ambiguous, alternative. On the one hand, advances in risk modeling such as the Monte Carlo method – and the securities and derivatives it helped popularize – have enabled financial services firms to commodify and price risk in novel ways. Yet, as the contribution by Andrea Saltelli underscores, there are good reasons to look critically at the increasingly complex and often opaque mathematical models used in estimations of risk. Infamous in this regard is the former CEO of Goldman Sachs, David Viniar, who claimed in 2007 that the bank had experienced ‘25 standard deviation events, several days in a row’. As John Kay and Mervyn King have argued in Radical Uncertainty (Citation2020), tools developed to understand risk cannot fully tame uncertainty. It is not just that models might not correspond with the underlying reality they purport to describe, but that the mere existence of a model projects an unwarranted sense of security.
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As this brief survey suggests, thinking about risk, uncertainty, and democracy in the twenty-first century is a practice that cuts across disciplines, subject matter, and time periods. Trying to craft a comprehensive volume would be a fool’s errand, and the contributions included here only begin to scratch the surface. In lieu of comprehension, we have aimed to model a different way of thinking and speaking about risk – one that moves away from technocratic approaches to center the workings of power, and that can be applied to a broad range of analyses. We trust readers will find something worthwhile in our efforts.
- Full Paper Here
