On the eve of the big Jeopardy! match, Peter Norvig’s opinion piece in the New York Post (!) today, The Machine Age looks at AI’s progress over the past sixty years and lays out six surprising lessons we’ve learned.

• The things we thought were hard turned out to be easier.
• Dealing with uncertainty turned out to be more important than thinking with logical precision.
• Learning turned out to be more important than knowing.
• Current systems are more likely to be built from examples than from logical rules.
• The focus shifted from replacing humans to augmenting them.
• The partnership between human and machine is stronger than either one alone.

When took Pat Winston’s undergraduate AI class in 1970, only the first of those ideas was current. It’s a good essay.

Of course, after we we’ve exploited the new data-driven, statistical paradigm for the next decade or so, we’ll probably have to go back to figuring out how to get logic back into the framework.

Related posts:

1. Lessons from salesmen and nurses
2. Hotel minibar keys open Diebold voting machines
3. The singularity: when machines become conscious
4. Cloud computing with Hadoop
5. Making machines, and computer games, intelligent