Heuristics That Almost Always Work An Article by Scott Alexander astralcodexten.substack.com Sometimes there’s a Heuristic That Almost Always Works, like “this technology won’t change everything” or “there won’t be a hurricane tomorrow”. And sometimes the rare exceptions are so important to spot that we charge experts with the task. But the heuristics are so hard to beat that the experts themselves might be tempted to secretly rely on them, while publicly pretending to use more subtle forms of expertise. …Maybe this is because the experts are stupid and lazy. Or maybe it’s social pressure: failure because you didn’t follow a well-known heuristic that even a rock can get right is more humiliating than failure because you didn’t predict a subtle phenomenon that nobody else predicted either. Or maybe it’s because false positives are more common (albeit less important) than false negatives, and so over any “reasonable” timescale the people who never give false positives look more accurate and get selected for. expertiseheuristicsprediction
Beauty and compression An Article by Scott Alexander astralcodexten.substack.com The Buddha discusses states of extreme bliss attainable through meditation: Secluded from sensual pleasures, secluded from unwholesome states, a bhikkhu enters and dwells in the first jhāna, which is accompanied by thought and examination, with rapture and happiness born of seclusion. ...If you could really concentrate on a metronome, it would be more blissful than a symphony. The jhāna is also a strong contender as a theory of beauty: beauty is that which is compressible but has not already been compressed. The Abode of the Unsymmetrical beautysilencesensesattention
Negative Creativity An Article by Scott Alexander slatestarcodex.com Coming up with entirely novel ideas is really, really hard. Misinterpretation as inspirationSit Down And Think About It For Five Minutes ideascreativitymetaphor
Feature parity An Article martinfowler.com Whilst Feature Parity often sounds like a reasonable proposition, we have learnt the hard way that people greatly underestimate the effort required, and thus misjudge the choice between this and the other alternatives. For example even just defining the 'as is' scope can be a huge effort, especially for legacy systems that have become core to the business. Most legacy systems have 'bloated' over time, with many features unused by users (50% according to a 2014 Standish Group report) as new features have been added without the old ones being removed. Workarounds for past bugs and limitations have become 'must have' requirements for current business processes, with the way users work defined as much by the limitations of legacy as anything else. Rebuilding these features is not only waste it also represents a missed opportunity to build what is actually needed today. These systems were often defined 10 or 20 years ago within the constraints of previous generations of technology, it very rarely makes sense to replicate them 'as is'. softwarefeaturesrepair