The key part of AI we don't know h0w to do yet. Good overview of current state and directions. What most all of us consider the important starting point for useful intelligence. It is often also has the ability to explain why and how it came to a conclusion.
Seeking Artificial Common Sense By Don Monroe in CACM
Communications of the ACM, November 2020, Vol. 63 No. 11, Pages 14-16 10.1145/3422588
Although artificial intelligence (AI) has made great strides in recent years, it still struggles to provide useful guidance about unstructured events in the physical or social world. In short, computer programs lack common sense.
"Think of it as the tens of millions of rules of thumb about how the world works that are almost never explicitly communicated," said Doug Lenat of Cycorp, in Austin, TX. Beyond these implicit rules, though, commonsense systems need to make proper deductions from them and from other, explicit statements, he said. "If you are unable to do logical reasoning, then you don't have common sense."
This combination is still largely unrealized; in spite of impressive recent successes of machine learning in extracting patterns from massive data sets of speech and images, they often fail in ways that reveal their shallow "understanding." Nonetheless, many researchers suspect hybrid systems that combine statistical techniques with more formal methods could approach common sense.
Importantly, such systems could also genuinely describe how they came to a conclusion, creating true "explainable AI" (see "AI, Explain Yourself," Communications 61, 11, Nov. 2018). ... "
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