Paper: SCALA POLITICA – Politics and Governance Under Scaling and Uncertainty

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Most of the tension resides between 1) Embedded, complexity-minded, multiscale/fractal localism (politics as an ecology/complex adaptive system), and 2) Abstract one-dimensional universalists and monoculturalism (politics as a top-down engineering project). We go beyond the verbalism; we rely on information theory, complexity theory, uncertainty approaches (say fragility), and probabilistic rigor to look at politics with the same eyes as we examine highly dimensional interactive elements such as nature, biological systems, internet networks, and medical issues.

Link to Paper – academia.edu/38433249/Scala_Politica

[Medium] Foreword for Cut the Knot: Probability Riddles by Alexander Bogomolny

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How do you learn a language? There are two routes; the first is to memorize imperfect verbs, grammatical rules, future vs. past tenses, recite boring context-free sentences, and pass an exam. The second approach consists in going to a bar, struggling a little bit and, out of the need to blend-in and integrate with a fun group of people, then suddenly find yourself able to communicate. In other words, by playing, by being alive as a human being. I personally have never seen anyone learn to speak a language properly by the first route. Also, I have never seen anyone fail to do so by the second one.

Read the complete foreword on Medium.

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Nassim on CNBC Squawk Box: Global coronavirus response a case study of government incompetence and denial

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In a “Squawk Box” interview, Taleb specifically pointed to the importance of coronavirus testing. While countries have improved their capacity since the early days of the Covid-19 outbreak, Taleb said there has been a failure to develop quick, efficient testing at a scale that can cut off chains of transmission early. It also has the least economic cost, he said.

Link to the interview: cnbc.com/2020/11/02/…

Paper: On single point forecasts for fat-tailed variables

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Abstract

We discuss common errors and fallacies when using naive “evidence based” empiricism and point forecasts for fat-tailed variables, as well as the insufficiency of using naive first-order scientific methods for tail risk management.

We use the COVID-19 pandemic as the background for the discussion and as an example of a phenomenon characterized by a multiplicative nature, and what mitigating policies must result from the statistical properties and associated risks. In doing so, we also respond to the points raised by Ioannidis et al. (2020).

Link to Paper – sciencedirect.com/science/article/pii/…