It is not surprising that reaching human-level AI has proved to be difficult and progress has been slow---though there has been important progress. The slowness and the demand to exploit what has been discovered has led many to mistakenly redefine AI, sometimes in ways that preclude human-level AI---by relegating to humans parts of the task that human-level computer programs would have to do. In the terminology of this paper, it amounts to settling for a bounded informatic situation instead of the more general common sense informatic situation.
Overcoming the ``brittleness'' of present AI systems and reaching human-level AI requires programs that deal with the common sense informatic situation---in which the phenomena to be taken into account in achieving a goal are not fixed in advance.
We discuss reaching human-level AI, emphasizing logical AI and especially emphasizing representation problems of information and of reasoning. Ideas for reasoning in the common sense informatic situation include nonmonotonic reasoning, approximate concepts, formalized contexts, concepts as objects, and self-awareness.
John McCarthy is a pioneer in the field of Artificial Intelligence. He created the LISP language in 1958. For his research he received a Turing Award in 1971, a Kyoto Prize in 1988, and the National Medal of Science in 1990.
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