The next catastrophe

Preparedness is one of things that governments are for

 If a coronal mass ejection (cme) were to hit, all sorts of satellite systems needed for navigation, communications and warnings of missile attacks would be at risk. 

 Large parts of the planet could face months or even years without reliable grid electricity

 The Economist 25 June 2020

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Niall Ferguson: The AI Boom Is a House of Cards, Tyler Cowen: Not so fast

AI is driving markets and GDP growth—but the underlying financing resembles the 19th-century railroad industry, which had its own share of crashes. Financial history can help us here. If you’re unsure if there’s an AI bubble, refer to the historian Charles Kindleberger’s five-stage model: Displacement: Some change in economic circumstances creates new and profitable opportunities for certain companies. Euphoria or overtrading: A feedback process sets in whereby rising expected profits lead to rapid growth in share prices. Mania or bubble: The prospect of easy capital gains attracts first-time investors and swindlers eager to defraud them. Distress: The insiders discern that expected profits cannot possibly justify the now-exorbitant price of the shares and begin to take profits by selling. Revulsion or discredit: As share prices fall, the outsiders stampede for the exits, causing the bubble to burst altogether. We are currently at stage 3. Niall Ferguson The Free Press 17 November 2025...
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Cognitive blind spots

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Cognitive blind spots are undermining our ability to see the world as it is, rather than as we would like it to be. At the start of the 21st century, western elites generally assumed that globalisation, democracy and the free market were self-evidently good, and would keep spreading, creating peace. N o longer.  FIS, Swiss Federal Intelligence Service, has published a manual about cognitive blind spots. 18 different cognitive biases that hamper our thinking, such as “group think” (adhering to the cosy assumptions of our tribe), “anchoring” (relying exclusively on whatever information we see first, say on social media),  “confirmation bias” (only seeing data that reinforces pre-existing views),  “mirror imaging” (assuming others think like us),  “absence of evidence” bias (failing to think about the data we lack)  and “survivorship bias” (judging data only with success stories, not failures). Gillian Tett Financial Times 2 January 2026 https://www.ft.com/content/...
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Martin Wolf; The next crash - Why this time might not be different

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Stock markets are not only ignoring the obvious threats, but seem imbued with extreme optimism. In the autumn of 1929, Irving Fisher, one of the greatest American economists, stated: “Stock prices have reached what looks like a permanently high plateau.”  This turned out to be one of the most incorrect forecasts ever made: in short order, US and global stock markets were hit by the Great Crash, which was followed by the Great Depression. Maybe markets were in some sense “right” before the crash and wrong after it. But who cared? For investors and the hundreds of millions of people across the world whose lives were upended by the disaster, the gods of the stock market had failed for a generation. Why might this story be relevant today? The answer is that the valuation of US stocks is even higher today than in September 1929.  The first global financial crisis after the disaster of the 1930s in 2007-09: the easy monetary — and relaxed regulatory — policies adopted after the stoc...
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