>using them for data labeling would be a waste of resources
Would it? It seems like they can spend a few months extracting intelligence and "taste" from their engineers then get years worth of it back from the AI.
I wouldn't trust any engineers I know of with their "taste". At best it's a highly skewed view of the world. At worst, it's outright opposite to genpop.
Are there any examples of this actually working? I keep seeing this fantasy repeated but have not seen a plausible explanation for how they wouldn't be contibuting to the pile of negative examples which are just as valuable if not more.
Poison pilling skills is a thing, though finding evidence for it is difficult given the crux is an absence of information. The baseline instruction and training is given to the model by the expert, but edge cases are willfully neglected. The degree of neglect generally determines how detectable it is, but if all the SMEs are in on it a lot of them will probably persist. Effectiveness and impact are obviously relative to the system and the edge case. Not particularly different from the fallout previously seen during the offshoring era.