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
AI-driven "Design"? An Article by Jorge Arango jarango.com Like a programming language interpreter, GPT-3 translates the designer’s intent from a language they’re already familiar with (English) to one they need to learn (Figma’s information architecture, as manifested in its UI.) This can be easier for a new/busy designer, much like Python is easier and faster to work with than assembly language. But that’s not “designing” — at least not any more than compiling Python code is “programming.” In both cases, all the system does is translate human intent into a lower level of abstraction. Sure, the process saves time — but the key is getting the intent part right. I’ll be convinced the system is “designing” when it can produce a meaningful output to a directive like “change the product page’s layout to increase conversions.” aidesignintentabstraction