And say I used some standard non-AI scheduling software like Mindbody or JaneApp to schedule an appointment with my mechanic and asked for an appointment to have my tires changed and rotated. If I ended up having my oil changed because the software simply schedules the most common kind of appointment, this would be a clear sign that the software is buggy and no reasonable person would argue that zero effort should go into fixing this bug. And yet, this is a common argument that people are making with respect to AI (itās probably the most common defense in comments on this topic). The argument goes a bit further, in that thereās this explanation of why the bug occurs thatās used to justify why the bug should exist and people shouldnāt even attempt to fix it. Such an explanation would read as obviously ridiculous for a āclassicalā software bug and is no less ridiculous when it comes to ML. Perhaps one can argue that the bug is much more difficult to fix in ML and that itās not practical to fix the bug, but thatās different from the common argument that it isnāt a bug and that this is the correct way for software to behave.
