Gaider replied by citing the oft-used argument that AI models can often be trained on copyrighted material, which \u201copens up any use of it to all sorts of future legal issues \u2013 even if one chooses to ignore the moral implications, which one really shouldn\u2019t\u201d.<\/p>\n
He also noted, however, that while some argue AI can be used for handling repetitive tasks, such tasks can sometimes be important for less experienced developers to do because it helps them to understand and learn the craft.<\/p>\n
\u201cHonestly, what does it help with?\u201d Gaider asked. \u201cDoes it make the work more efficient? Does it improve the work? It wouldn\u2019t be so bad if generative AI was seen more as an assistant, doing the drudgery while leaving more important tasks for the worker, but we seem to be seeing more and more of the reverse \u2013 the AI is set to do the important work and the worker is around to \u2018clean up\u2019.<\/p>\n
\u201cIn all my time as a narrative designer I\u2019ve never once encountered a situation where editing an inferior product took less time than simply throwing it out and redoing it would have, or resulted in anything better than mediocre.<\/p>\n
\u201cAnd while there\u2019s potential for AI handling the drudgery, I also think we have to be very careful about not eliminating every task which is useful for training juniors. How are we going to train up the next generation of devs if we eliminate every entry-level task?\u201d<\/p>\n
Gaider said this extended to programming, specifically referring to the growing trend of \u2018vibe coding\u2019, where developers describe their vision in plain English and AI codes it for them, rather than having the developer write the code themselves.<\/p>\n