Charles Haynes wrote on 8/22/18 2:00 AM August 22, 2018:
Pearl has been spruiking his causality formalisms for years, but they don't
seem to have caught on despite widespread dissemiy of the ideas. I've read
them and my reaction was "hm, interesting" rather than "oh! I see how this
could be useful"
Anyone else have opinions on why his ideas haven't caught on more generally?
It's too hard to make computers think that way? Much easier to show them
what you want and have them select a series of linear transformations
that make it so. This is not how humans think, but, hey, you can model
almost anything that way, so why not do it if you can throw the data and
the cycles at it?
Humans seem to do a lot more reasoning by association than causal
thinking. We also reason by analogy, which no one seems interested in
teaching machines to do. A lot of our thinking is tangled up with our
perceptual systems, which works well for us but would require millions
of years of evolution to replicate in machines.
Humans arguably aren't reasoning machines, and there's a lot more to
thinking than the ability to construct proofs. Our ability to construct
story might be more fundamental than our ability to probe causality.
--hmm
-- Charles
On Wed., 22 Aug. 2018, 5:28 am Bharat Shetty, <bharat.she...@gmail.com>
wrote:
Sharing an intriguing interview with Judea Pearl related to his book "The
Book of Why", a book that I have been reading and enjoying.
"In his new book, Pearl, now 81, elaborates a vision for how truly
intelligent machines would think. The key, he argues, is to replace
reasoning by association with causal reasoning. Instead of the mere ability
to correlate fever and malaria, machines need the capacity to reason that
malaria causes fever. Once this kind of causal framework is in place, it
becomes possible for machines to ask counterfactual questions — to inquire
how the causal relationships would change given some kind of intervention —
which Pearl views as the cornerstone of scientific thought. Pearl also
proposes a formal language in which to make this kind of thinking possible
— a 21st-century version of the Bayesian framework that allowed machines to
think probabilistically.
Pearl expects that causal reasoning could provide machines with human-level
intelligence. They’d be able to communicate with humans more effectively
and even, he explains, achieve status as moral entities with a capacity for
free will — and for evil."
https://www.quantamagazine.org/to-build-truly-intelligent-machines-teach-them-cause-and-effect-20180515/
PS: If there are similar mind-bending and worldview changing books, holler
about them at me.
Regards,
- Bharat
