TITLE: The Magic at the Heart of AI
AUTHOR: Eugene Wallingford
DATE: November 30, 2013 9:45 AM
DESC:
-----
BODY:
This paragraph from
The Man Who Would Teach Machines to Think
expresses a bit of my uneasiness with the world of AI these days:
As our machines get faster and ingest more data, we allow ourselves
to be dumber. Instead of wrestling with our hardest problems in
earnest, we can just plug in billions of examples of them. Which
is a bit like using a graphing calculator to do your high-school
calculus homework -- it works great until you need to actually
understand calculus.
I understand the desire to solve real problems and the resulting
desire to apply opaque mathematics to large data sets. Like most
everyone, I revel in what Google can do for me and watch in awe
when Watson defeats the best human Jeopardy! players ever. But
for me, artificial intelligence was about more than just getting
the job done.
Over the years teaching AI, my students often wanted to study
neural networks in much greater detail than my class tended to go.
But I was more interested in approaches to AI and learning that
worked at a more conceptual level. Often we could find a happy
middle ground while studying genetic algorithms, which afforded
them the magic of something-for-nothing and afforded me the
potential for studying ideas as they evolved over time.
(Maybe my students were simply exhibiting
Astrachan's Law.)
When I
said goodbye to AAAI
a few years ago, I mentioned Hofstadter's work as one of my early
inspirations -- Gödel, Escher, Bach and the idea of
self-reference, with its "intertwining worlds of music, art,
mathematics, and computers". That entry said I was leaving AAAI
because my own work had moved in a different direction. But it
left unstated a second truth, which The Man Who Would Teach
Machines to Think asserts as Hofstadter's own reason for
working off the common path: the world of AI had moved in a
different direction, too.
For me, as for Hofstadter, AI has always meant more than
engineering a solution. It was about understanding scientifically
something that seemed magical, something that is both deeply
personal and undeniably universal to human experience, about how
human consciousness seems to work. My interest in AI will always
lie there.
~~~~~
If you enjoy the article about Hofstadter and his work linked above,
perhaps you will enjoy a couple of entries I wrote after he visited
my university last year:
-----