Risk, Uncertainty, & Democracy

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

Micromort - A Unit Of Measure Of Risk

One problem we have is that risk is usually both relative and cumulative in nature. Vaccines work because they reduce the overall risk of death dramatically, but in almost every case, some risk remains. So you’re not eliminating a threat, you’re just lowering the odds that it will impact you. And you can reduce the risk further by adding additional measures, like masking or social distancing. So to understand the total risk that you face in a given situation, you have to understand the base rate of danger that you’re confronting, and then the relative impact of the interventions you’re considering, whether it’s wearing a seat belt or putting on a mask.

Another problem with risk is that it often revolves around very small probabilities, which can lead to all sorts of base-rate confusion. You’ll read an article about a new study that finds eating bacon doubles the risk of pancreatic cancer and it’ll sound terrifying. (I am making these numbers up, so do not adjust your diet based on them.) But what if your initial odds of getting pancreatic cancer are 1 in 100,000? Then you can just as accurately say that eating bacon will change your odds of getting pancreatic cancer from from .00001 to .00002. That doesn’t sound nearly as worrisome.

A few decades ago the Stanford professor Ronald Howard proposed a unit of measure for mortality risk. He called it the “micromort.” One micromort equaled a one-in-one-million chance of dying. Howard was an expert in decision theory, and he had recognized that many of life’s most complicated decisions—particularly medical ones—involved complicated assessments of risk probability. Howard imagined the micromort as a common framework that, for example, a doctor could use with a patient to describe the risks of undergoing a specific procedure—and the risks of not undergoing the procedure.

The standard never really took off, but it has seen something of a revival in the COVID age.

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And in the event that you feel untroubled by COVID’s current micromort levels and are planning a sporty vacation somewhere this spring, I present to you, courtesy of Wikipedia, a list of potential recreational activities ranked by micromort levels:

• Skiing: .7 micromorts per day
• Scuba diving: 5 micromorts per dive
• Running a marathon: 7 micromorts per run
• Skydiving: 8 micromorts per jump
• Climbing Mt. Everest: 37,932 micromorts per ascent

Plan accordingly.

- More Here

One of the reasons I adore Taleb is because for the first time in history, there is this one person who spent his entire life on meditating, acting and finally succeeding in educating the masses on the concept of risk. Thank you for that Taleb!! 

History will immortalize him but yet sapiens refuse to comprehend risk. I think, risk should be part of our emotional repertoire on par with happiness, grief, disgust, and anger. Maybe risk is already part our emotions - every living creature evolved with innate risk dial but we might have subsided it by sheer lack of our unawareness.