For a long time, "AI" meant "unsolved hard problem" to hackers like us. Speech synthesis and recognition was AI. Text recognition was AI. Some compiler optimiza

For a long time, "AI" meant "unsolved hard problem" to hackers like us. Speech synthesis and recognition was AI. Text recognition was AI. Some compiler optimization was AI. Search was AI. Now, those things are, well, those things. They work. Things are a little different now. The feasibility of neural networks trained up on vast data sets means we have non-human systems with hunches. That is, we have AIs capable of delivering results without explanations. Take a look at Neal Stephenson's recent "Fall" for a social network that uses AI to generate "news" stories where the training metric is engagement. The consequence is the construction of an alternate social universe, and the kind of dystopia only Stephenson can dream up. https://www.worldcat.org/title/fall-or-dodge-in-hell/oclc/1148063262 https://www.worldcat.org/title/fall-or-dodge-in-hell/oclc/11... Human hunches are often accompanied by a sense of ethics. The agricultural savant who sexes hatchling baby chickens knows the success of the farm depends on a low error rate. The judge sentencing a culprit knows the consequence of making mistakes. I wonder how hard it would be to add a sense of ethics to neural network results? Maybe it's just a matter of managing the error rates. But this article suggests otherwise.