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C00005 00003	\smallskip\centerline{Copyright \copyright\ 1988\ by John McCarthy}
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\title{WHAT'S LEFT TO DO IN ARTIFICIAL INTELLIGENCE}
%omni[s88,jmc]		What's left to do in AI

	The main goal of artificial intelligence research,
to make computer programs as intelligent as people, was
proposed by Alan Turing in 1950.  He thought it could be
essentially done by 2000, but this now seems unlikely.
There is still no reason to suppose it impossible, provided
one avoids demanding that computer programs do what people
can't do either, e.g. decide arbitrary formulas of predicate logic
or quickly decide arbitrary formulas of propositional logic.

	Much positive progress has been made since 1950, e.g. expert
systems on the applied level and formalized nonmonotonic reasoning
on the basic research level.  Nevertheless, an important result
of the research is the identification of problems that remain, and
some of them look very difficult.  Here are a few, but I'm sure they
aren't all.  Also the brevity of this statement requires using
terminology that many readers will have to take metaphorically, with
the risk of misunderstanding.

	1. A sufficiently general language for expressing a database
of common sense knowledge.  A key problem is avoiding having to
list all exceptions.  Recent work on nonmonotonic reasoning provides
only a start on how to do it.

	2. The ability to decompose a problem into parts that can
be thought about separately followed by thinking about their
interaction.  That's why programs for playing {\it Go} are so far
behind programs for playing chess.

	3. Declarative expression of domain-dependent heuristics.
This is required to reduce the combinatorial explosion that affects
computerized logical reasoning about many problems.

\smallskip\centerline{Copyright \copyright\ 1988\ by John McCarthy}
\smallskip\noindent{This draft of OMNI[S88,JMC] TEXed on \jmcdate\ at \theTime}
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