Key questions on Common Upper Ontology
Response to
The illusion of the AI mythology, illustrated
There is a good deal of concrete, practical evidence of the advance of
AI, as there is about the need for knowledge bases that define the entities,
attributes, constraints, etc. and their relationships in information systems in
a more formal language than data dictionaries do - in other words -
ontologies. Look; back in the 19th century, the Luddites were against
power looms, but neither their arguments nor their axes kept the use of power
looms at bay for very long.
4/20/2004 2:48
PM
The AI scholars are imposing something on us.
http://www.bcngroup.org/beadgames/graphs/twentythree.htm
I do not think that these individuals disbelieve in the core issues that they claim, and there are many perfectly ok things that are mixed in with what is really a non-sense notion. But, I have said many times that AI is like a religious fundamentalism, and shares similarities to the fundamentalism of reductionist science. When one believes in something there is selective memory and a re-interpretation of evidence. But this is not science.
Why should we treat natural intelligence with ignorance about its full nature?
What is to be gained by acting as if any computer can be smarter than humans, or even that computers can be smart? Why oversell anything?
The AI scholars make fun of those who try to shut down the funding streams for continuation of projects whose justification is questionable. They act as if not very much money and social capital has been given in support of AI. But how many PhDs in AI are there: one thousand, two thousand, three thousand? We have paid for this illusion over and over again, and DARPA’s Director is setting us up one more time to pay for AI one more time.
TESTIMONY OF DR. TONY TETHER,
DIRECTOR
The problem is that these scholars have never had anyone say no that is able to match the mathematics and also include natural science. Except for Sir Roger Penrose, Robert Rosen and a few dozen others. In many cases, the challenges can be simply ignored. Who cares? We have an entire network of academic departments and have the control of large budgets at DARPA, NIST and NSF.
But there are alternatives that have not been funded, and these alternatives do not simply ignore the natural sciences.
But they do not get funded because of the power of the AI intellectual authorities. Specifically one points to the fact that AI scholars continually treat funding proposals from the knowledge sciences with great distain and influence program managers (who really often do not have a clue) to not fund work that is deemed fundable by a broad peer review. I will not go into specifics here.
The argument is:
Herb wrote, "I continue
to marvel at the fact that, after 45 years, the naysayers can still be taken
seriously, when they deny that computers (sometimes) think, or place that happy
possibility in the distant future. I am afraid that at the outset of our
adventure I greatly underestimated the emotional need many members of our
species have to believe in its uniqueness. Patience! All that will pass."
Herb Simon was just wrong. The inference is as poor as any example of poor reasoning. It is not the human’s need to be superior to computers that is in question here. This is something manufactured to be cute. Humans are humans. Living systems are living systems. Physical systems are physical systems. Abstractions and formalism are abstractions and formalisms.
At one point someone might believe that parallel dimensions exists, and that we just have not discovered how to talk with the people in these dimensions. But this is not science, and it does not become science because Herb Simon or anyone else wants to claim something not yet proved to be something that should be expected and paid for by the government.
Have there been advances in all kinds of things because of the AI research? OF COURSE. The point is that we should now understand that this well is dry, and turn our funding to the fertile fields of the knowledge sciences.