Artificial Intelligence – The Revolution Hasn’t Happened Yet (2018)

The problem had to do not just with data analysis per se, but with what database researchers call “provenance” — broadly, where did data arise, what inferences were drawn from the data, and how relevant are those inferences to the present situation? While a trained human might be able to work all of this out on a case-by-case basis, the issue was that of designing a planetary-scale medical system that could do this without the need for such detailed human…

Well said: > Thus, just as humans built buildings and bridges before there was civil engineering, humans are proceeding with the building of societal-scale, inference and decision making systems that involve machines, humans and the environment. Just as early buildings and bridges sometimes fell to the ground — in unforeseen ways and with tragic consequences — many of our early societal scale inference and decision making systems are already exposing serious conceptual flaws.

This is a common sentiment, and pundits have been making similar remarks for decades. This author writes "Sixty years later, however, high-level reasoning and thought remain elusive." That's the wrong problem with AI. The trouble with AI is that it still sucks at manipulation in unstructured situations and at "common sense". Common sense can usefully be defined as getting through the next 30 seconds of life without a major screwup. At, at least, the competence level of the average squirrel…