Post #2920373

I can return to the culinary analogy I have been using recently to illustrate this point. We chew food that is hard to swallow, in order to make it easier to digest. And we have cooking techniques to make tough foods more tender, to reduce the amount of chewing needed. However, if one decided to automate and optimize digestion by minimizing the chewing needed, the logical solution would be to put all of our meals into a blender and serve them through feeding tubes. This technically solves the problem of indigestion, but is not a popular option (save for people too ill to chew food properly). There are other valuable benefits of eating, such as the sensory enjoyment of the experience or the ability to create a social event around a meal, which go beyond the mere ingestion of nutrients, and which would be negatively impacted by such an overemphasis on maximizing digestibility. This is not to say that blenders and similar devices are useless; but their use cases are situational. In a similar vein, using AI tools to make mathematical papers "as easy to read" as possible are not necessarily desirable; they can be useful in identifying particular pockets of "artificial difficulty" in a draft paper that would benefit from a rewrite (similar to how an overly tough piece of meat could be tenderized before serving), but using them to smooth out "natural difficulties" in a text that actually are of benefit for the reader to "chew over" can end up being counterproductive to the actual goal of advancing the collective understanding of the result by the community. (2/3)