Whether you are speaking to corporate managers, Silicon Valley script kiddies, or seasoned academics pitching commercial applications of their research, you’re likely to hear a lot of claims about what AI is going to do.
Hysterical discussions about
AI machine learning’s applicability begin with a breathless recap of breakthroughs in predictive modeling (9X.XX% accuracy on ImageNet!, 5.XX% word error rate on speech recognition!) and then abruptly leap to prophesies of miraculous technologies that AI will drive in the near future: automated surgeons, human-level virtual assistants, robo-software development, AI-based legal services.
This sleight of hand elides a key question—when are accurate predictions sufficient for guiding actions?