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I don't understand how that would cause grief. Seems totally irrational to me.
by xcv123 3y ago
I don't understand how that would cause grief. Seems totally irrational to me.
- ggm 3y agoThese words are applied to living people. Applied to machines they create states of belief outside the cognoscenti what is going on. It's as if we called programming "magic" and programmers "wizards" and then kids ask "is Harry potter real" and somebody says "yes" It's not hallucinating. It's an analogy. But analogies are not definitional. We're going to wind up in conversations about AGI and use of imprecise analogistic language will alter how people discuss this problem. Sorry you think I'm irratinal. I think you're being obtuse and not considering real world consequences of the ontologies used outside of the field.
- nercury 3y agoDon't "run" programs, don't let them "spawn" threads, don't allow CPU to "follow" instructions, don't "read" or "write" files, should I keep going? All these words used to mean humans doing things, we have been anthropomorphising the machines since the beginning. You are fighting a loosing battle here, better to just calm down and relax.
- dleeftink 3y agoA warm-up exercise before going into any programming task is coming up with names for the methods and interfaces I intend to implement. A more difficult exercise is coming up with apt names without anthropomorphising--something I rarely succeed at. I'm often drawn to analogs in the musical realm (Scales, Sequences, Signals, Tuning), carpentry (Blueprints, Components, Scaffolding), libraries (Resources, Pages, Indices), the natural world (Roots, Trees, Seeds, Leaves), physical media (Slots, Packages), publishing (Versions, Releases) and even cooking (Mixers, Recipes). We often understand technology by way of analogy or prior experiences. Whenever dealing with the abstract or unknown, metaphors are often the first tool to make sense of them [0]. [0]: https://en.m.wikipedia.org/wiki/Metaphors_We_Live_By https://en.m.wikipedia.org/wiki/Metaphors_We_Live_By
- ben_w 3y ago"Computer" being a former job title would've been on my list :)
- xcv123 3y agoI see from your other comments you still don't fully understand that these algorithms are automatically generated based on their training data. That's what we mean by "machine learning". It figures out the algorithm by itself through an iterative "learning" process that builds a predictive model. Training/Learning are perfectly reasonable terms in this context. They learn patterns in data automatically. These are not explicitly programmed by humans.
- hexaga 3y agoIt's fairly clear that they understand that much. The objection is that the word 'learn' is generally used in reference to how humans learn. There is a lot implied in this usage, and a long history of use by the general populace. By overloading it as 'things that are kinda like human learning, in some ways' you must ignore swathes of that implicit meaning to remain correct while using it. It is no longer a phenomena, but a class of phenomena. The problem they pose is that people aren't going to do that - they'll continue using 'learn' as a stand-in for 'human learning' even when discussing ml adjacent topics, and that is damaging to effective discourse. Practically speaking, that ship has sailed. Regardless, it's a reasonable take. You can literally see their implied scenario play out in this thread - they claim that llms are doing machine-like learning rather than human-like learning (an entirely uncontroversial claim, humans are almost certainly not transformers in disguise) and the conditioned response is along the lines of "you're wrong, they do learn! obviously you don't understand the most trivial aspects of machine learning!" This exchange merely proves their point (which is really the observation): overloading this word in particular causes grief. Misunderstandings abound and arguments arise from no actual disagreement in object level reality.