[ExI] The End of the Future
Anders Sandberg
anders at aleph.se
Tue Oct 4 07:51:17 UTC 2011
I'm sitting at a conference about philosophy and AI right now.
Yesterday's keynote talk was by Hubert Dreyfus and largely consisted of
him gloating about how he had been right about the failures of all the
AI pioneers that were passing by the MIT campus (Minsky, Simon, Lenat,
Brooks, Dennett...), all suffering from the "first step fallacy" (if you
have working first step of your architecture, then you can likely build
the whole thing). The fun part was that he was genuinely surprised by
the success of Watson - this is suddely a real result that from his
perspective simply couldn't happen. In any case, he had a very relevant
point: the real failure of the AI field has been that each new
generation has not seriously learned from the successes and failures of
the previous one.
I think this shows a general malaise of many fields: are there
incentives for progress or incentives for churn? You can get a great
academic career by investigating what your professor works on,
eventually inventing a "radical" different interpretation, and generally
producing plenty of papers - despite these papers not really adding
much, or dealing with a question that matters. Most AI researchers seem
to be doing something like this. Companies need to sell things, but if
they have the choice between making something genuinely new and
something reliably profitable, then most will sensibly go for the later
- and the customers are fine with that. And of course government policy
is almost always churn than real attempts at reform.
So, we might have a situation where we have created a situation where
incentives largely promote churn over innovation/progress. This likely
comes from 1) it is hard to distinguish genuine progress from
good-looking churn, 2) innovation is failure-prone and
funders/supporters don't want to be left holding the bag, 3) risk
aversion has been spreading, 4) our society and institutions have become
very complex, and getting the necessary focus to solve a big task is a
tough social problem.
To get around these, we need 1) better ways of detecting and
distinguishing progress from churn, which often involves better
institutional/societal memory, 2) changes in how incentives are
distributed (see Ioannidis paper in last week's Nature, or discussions
about science prizes), 3) making people more willing to take risks and
follow visions, 4) better forms of organisation (perhaps enabled by new
tech, perhaps by being tuned to maximizing progress).
--
Anders Sandberg,
Future of Humanity Institute
Philosophy Faculty of Oxford University
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