2/ One of the earliest applications to be systematized for instance, was life insurance for widows.
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3/ Though many applications in science/tech are agnostic to risk-versus-luck angle, most social uses are on that spectrum and focus on risk
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4/ Application of statistics/probability to stock markets is not about luck either, since beating market beyond historical gains is zero-sum
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5/ i.e. since markets themselves create no wealth, if you beat history, it's because someone else is beaten by history by betting wrong
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6/ There is another field that has this somewhat dismal/pessimistic risk-oriented flavor: psychology
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7/ Throughout much of its history, psychology has been about mental illness and pathologies rather than making good minds better
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8/ When positive psychology came along, many were excited by the promise, but it degeneratd into a bit of a New Age cult.
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9/ But the motive was laudable and worthy, and I think positive psychology *is* beginning to shed New Age trappings and deliver good results
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10/ I think lesson can be ported. There is room for a "positive probability theory" and "positive statistics" focusing on luck, not risk
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11/ Taleb made a big contribution towards theory of non-zero-sum luck/serendipity, but domain lock-in limited him to negative black swans
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13/ Fundamental theory/concepts won't change, since it is an axiomatized math field, but shift in emphasis to max-luck over min-risk is big
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14/ So #musklevel challenge to data/stats/probability wonks: invent a rigorous theory of luck/serendipity using hacking as first example
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what about real options/capital budgeting or venture capital as a base domain?
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best path to bottling up a million dollars with code is to MVP in distribution loops, not in features or data.
Most luck is in distro.
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