Progress in AI (2019)
Progress in AI




by Benjamin Kuipers


Has progress in AI been disappointing?



I like to consider AI to be the field that uses computational modeling
methods to investigate one of the great intellectual problems of all
time: What is Mind?  And how can a physical object have a mind?



I like to compare AI with Physics, which is the field that
investigates another of those great intellectual problems: What is the
World made of?  And how did it come to be?


Progress in AI


We use Summer 1956 to mark the beginning of the modern age in
Artificial Intelligence, commemorating the Dartmouth Workshop,
officially
the Dartmouth
Summer Research Project on Artificial Intelligence.



Naturally, there was important previous work, including the 1943
McCulloch-Pitts neuron model, Alan Turing’s seminal 1950 paper, and
Marvin Minsky’s SNARC neural network machine in 1951.



According to the
Wikipedia History
of Artificial Intelligence article,

  In 1958, Herbert Simon and Allen Newell wrote, “within ten
  years a digital computer will be the world’s chess champion”, and
  “within ten years a digital computer will discover and prove an
  important new mathematical theorem.”  

  In 1965, Herbert Simon predicted that “machines will be
  capable, within twenty years, of doing any work a man can do.”  

   In 1967, Marvin Minsky predicted that “Within a generation
  . . . the problem of creating `artificial intelligence’ will
  substantially be solved.”

  In 1970, Marvin Minsky, in an interview with Life Magazine,
  stated “In from three to eight years we will have a machine with the
  general intelligence of an average human being.”




These predictions seem dramatically over-optimistic.  However, . . .



It is quite understandable that young scientists, having discovered
new and fruitful approaches to a long-standing, extremely hard and
important problem, may be quite excited and optimistic about the
promise of future progress.  (Simon, Newell, and Minsky were in their
30s and early 40s when they made those predictions.)



Consider the first prediction, from 1958, that within ten years, a
digital computer will be the world’s chess champion.  In 1968, computer
chess was nowhere near the world-champion level, but by 1966 Richard Greenblatt's
Mac Hack had
played in numerous human amateur chess tournaments, and had achieved a
US Chess Federation rating of 1243.



In fact, it was not until 1997, four decades after the original
prediction, that IBM’s Deep Blue supercomputer defeated Gary Kasparov,
the world chess champion, in tournament play.  By 2017, after another
two decades, AlphaZero from DeepMind was able to learn, though
self-play, to defeat all other human or computer players at chess,
shogi, and Go.  Although there are vigorous chess competitions among
computers, and among hybrid human-computer collaborations, computers
are not eligible to play for the human world chess championship (any
more than forklift trucks are allowed to compete at weight-lifting in the
Olympics).



One must ask: when predicting the time-line for achieving a future
scientific and technological goal, that many experts predicted could
never be achieved at all, how large an error is a factor of four?



Progress in Physics


If I had to pick a beginning for the modern age of physics, I would
nominate the 1660s and 1670s when the differential and integral
calculus, that is, differential equations, were invented by Newton and Leibniz.



Differential equations are the appropriate mathematical language for
describing the continuous dynamical behavior of the physical world.
By providing a powerful and expressive language for scientific
hypotheses, and a set of solution methods capable of making strong
predictions from those hypotheses, differential equations enabled new
kinds of scientific progress.



Physics has made tremendous progress in the 350 years since the
creation of differential equations, but few people would say that the
problem of physics is “solved”.  (Although in 1878, Max Planck's 
thesis
advisor told him not to go into physics, because "almost
everything is already discovered".)


The Problem of the Mind


It is, of course, impossible to state reliably whether the “Problem of
Physics” or the “Problem of the Mind” is more difficult.



However, in my opinion, the Problem of the Mind is the more difficult
one.



Physical laws are believed to be spatially and temporally invariant.
They do present differently at different scales of certain parameter
spaces like velocity, mass, etc, because terms that are negligible at
one scale may become dominant at others.  The invariance that unifies
the classical domain with the quantum domain is still a matter of
faith rather than science, but it is generally believed, even if we
don’t yet understand how it might work.



The phenomenon of mind (as far as we know today), does not extend over
the same numbers of orders of magnitude as the phenomena of physics,
but the nature of intelligence, including perception, cognition, action,
communication, culture, etc, seem to be significantly more variable.



Perhaps this apparent complexity is due to our relative ignorance
about the mind, and in coming centuries, an underlying simplicity will
emerge.  But I doubt it.  Physics describes several layers at the
foundation of a hierarchy of scientific theories.  On top of Physics
are built (very roughly speaking) Chemistry, Biology, Psychology, and
Sociology-Anthropology, with increasing variability and complexity as
we proceed upward.



This suggests (with an extremely broad brush) that the Problem of the
Mind is significantly more complex than the Problem of Physics, and
arguably the Problem of Culture will be yet more complex.


Assessing Progress


Physics has made impressive progress in 350 years, but it is not yet “done”.



Only 60 years after starting to apply computational modeling methods
to the Problem of the Mind, it is not surprising that we are far from
“done”.



In my opinion, the last three prediction bullets above are
over-optimistic by at least one order of magnitude.  That is,
Artificial General Intelligence (AGI) will take at least one, and
perhaps several, centuries to achieve.  And that assumes that we can
keep our scientific, technological, social, political, and ecological
infrastructures on an even keel during that period.



These are some of the most fundamental problems that humanity is
trying to answer.  It is hardly surprising that they are problems for
the centuries and millennia, not just for years and decades.







Written 15 September 2019.

There is undoubtedly more to say.



BJK



