Reading List
As long promised (sorry!), here are some books and a few papers I recommend. I’ve read at least some of (almost) all of them and (almost) all of most titles I refer to (not all the textbooks).
Please leave errors and suggestions below, I’ll tweak and add over time and notify of updates. In particular I’ll add textbooks, history and philosophy which I’ve largely left out.
Coming soon:
Update to Trump v Biden blog of last September. Many interesting developments and the launch of the 2024 campaign may be only a few weeks away, if Trump announces on 4 July as is being discussed in Mar-a-Lago. Will live players use the next five months to build build build or waste the most important element in conflict, time, and let non-player characters stumble into a set of critical decisions in November…?
Review of the disintegration of the Tories in the context of Brexit, SW1 vs Vote Leave perspectives on risks of Brexit/Remain, and why some of the VL team decided to go to No10 in 2019 and save the trolley to Get Brexit Done despite our reservations. NB. The vaccine taskforce a) created huge value for the UK and the world, b) would no way have happened without [typo original!] Brexit and VL in No10 (original official advice was to go with the useless bureaucratic EU scheme even though we’d left so a fortiori it would have advised the same had Brexit not happened, but credit to the Cabinet Secretary for backing Vallance and me with the PM), c) the elite world resolutely refuses to consider procurement generally or the VTF in particular in the context of Brexit good/bad, d) in 2021 the VTF was effectively closed and turned into a normal entity rather than given the money and goal of replacing current vaccines with new ideas to solve the variants problem with safer technology, e.g nasal vaccines, e) this too is a non-subject in SW1. SW1 suffers such extremely powerful wilful blindness even an event as big as covid doesn’t puncture consciousness in many important ways.
Notes on Colin Gray’s Strategy and Defence Planning, following on from military innovation, The Kill Chain, nuclear (sorry for slow progress on Payne).
Something on how ideas change over different time scales. We look back on history and abstract over decades or centuries, judging the ideas that held sway for a few decades and sneering at how ‘formerly all the world was mad’ as Nietzsche put it. E.g Around 1848 nationalism was an elite opinion held by educated liberals who thought of liberalism and nationalism as naturally, and morally, connected, while uneducated peasants were less nationalistic. Then nationalism became generally despised by educated liberals, and so on… We can’t know how our own ideas will appear in the future but it’s fascinating how little we try to imagine how foolish our own views will inevitably appear to those looking back on us. ‘Elite opinion’ in London today is dominated by very similar people with very similar education and very similar views that inevitably include assumptions that will prove false — like ‘the British navy rules the waves’ (true and a useful heuristic for many decades then suddenly and drastically not true) — and ‘values’ that will seem evil/comical. Perhaps ‘America has elections every four years’, ‘power supply is ~100% reliable in the First World’, ‘Europe won’t see millions killed in wars again’, ‘nobody lives happily/normally to 200’, ‘robots can’t escape control and kill vast numbers of humans’, ‘children should study curricula controlled by the state’, ‘I support policies that undermine traditional ideas about the family’ will seem as quaint in 2052 as Bertrand Russell being taught by a grandfather who’d met Napoleon that British naval dominance is a fact of life.
How to predict news? If we could predict events like ‘the fall of the Berlin Wall’ better it would have huge value. Two adjacent questions: 1) what signals of memes/news predict that X is likely to emerge from the noise and become one of the few stories/memes that’s significant — e.g the process of ‘the Wall falling’ has started with small events which are detectable but almost nobody notices or realises what a big deal they will be in a few weeks, how soon can we detect ‘X is happening’ then predict ‘X is Y% likely to be a big story’, with what confidence?; 2) how to map the spread of memes and identify critical nodes in the network that, if influenced somehow, can amplify or dampen signals? In 2018 I asked some academics to consider this and we built a crude tool. Our impression was there is valuable low hanging fruit for governments, hedge funds, campaigns…
The Snippets format doesn’t work well and I’m rethinking how to do it. All ideas welcome. In the meantime I’ll post another tomorrow.
Please use comments below for reading suggestions, not general Q&A.
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