Messes, problems and puzzles
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The JC’s amateur guide to systems theory™
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messes, problem and puzzles
(n.)
A coinage of Russell Ackoff and distinguishing between situations having neither a well-formed question nor an answer (“messes”), those which have a clear question but not an answer (“problems”) and those which have a clear question and a determinate answer (“puzzles”).
JC notes parenthetically that a bucket is missing here: those situations in which there exists an answer but not (yet) a question — call these ones “opportunities”, “unfulfilled use cases” or “solutions looking for problems” etc.[1]
Lost in the sound bite (if not on Ackoff himself): almost all situations we face are a permanently shifting, inchoate combination of all three. Of these, puzzles are the most soluble by algorithm — they are generic do not require nuanced framing and solving them is trivial , and therefore not valuable. Hence, “markets abhor commodities”: if everyone can do it, cheaply, there’s no margin in it.
(There is a value in puzzles, of course: ask a crossword fan. But that value cannot easily be reduced to a number. Especially if the crossword is embedded in a newspaper.)
Data modernists tend to treat messes as reducible to problems, and problems as reducible to puzzles, and the universal acid which works this magic is the symbol processing capacity of a Turing machine. Hence the headlong rush towards generative AI, quantum computing etc.
Contrarian view: adding targeted random pattern generators to an already messy system will not, we respectfully submit, make it simpler.
Nor is it true that questions, once formulated, and answers, once computed, stay put. This is precisely the definition of a complex system: the landscape dances, and it is not just the answers that update but the questions do, dynamically , in response to each other. Take the simple case of fashionable bars in 1990s Wellington.
Take Downtown bar scene. For a small town, the Wellington, New Zealand — once dubbed the “East Berlin of the South Pacific” — had a lively bar scene. The town had no shortage of recently-monied law and accounting graduates making their way through the corporate and administrative gears of central government, and with a large central university Wellington has a thriving alternative hiptster. Thanks to the city’s lousy weather and awkward geography — it's hard to find a dry flat space to sit down outside, let alone play sport, and its usually blowing a gale so no-one wants to do either. For months of the year all there is to do is drown your sorrows, so the bar scene, concentrated in a walkable space in between the university, the “city” and government, is energetic.
Within it there is — well, used to be , a sort of apex predation of hip hangouts: first the leftists and artistes will find and frequent some grungey out of the way bar then a few of the younger tuned -in progressive lawyers catch on, anxious to be on scene, then the civil servants. By the time the accountants cotton on the architects and musos have long gone and found another place to refuge from the smug little berks in their suits.
The bar ecosystem mutates, that is to say. By participating in it, you change it. There is something irreducible about “where its at” — if you solve it for scenario A it automatically reorganises itself as scenario B.
See also
- ↑ Distributed ledger technology, generative AI, wheels for suitcases for example.