Path: utzoo!utgpu!jarvis.csri.toronto.edu!mailrus!csd4.milw.wisc.edu!bbn!apple!voder!pyramid!prls!philabs!linus!mbunix!bwk From: bwk@mbunix.mitre.org (Barry W. Kort) Newsgroups: comp.ai Subject: Re: Polanyi in the Chinese Room. Summary: Comments on Understanding and Comprehension. Keywords: Deep Understanding Message-ID: <52020@linus.UUCP> Date: 1 May 89 14:08:59 GMT References: <2471@nmtsun.nmt.edu> Sender: news@linus.UUCP Reply-To: bwk@mbunix (Barry Kort) Organization: The MITRE Corporation, Bedford, Mass. Lines: 42 I enjoyed reading Clifford Adams' essay, "Artificial Intelligence and Learning--A Changing Perspective." I find myself increasingly amused by the debate over "True Understanding." After reading Feynman's anecdotes about Brazilian physics students (in _Surely You're Joking, Mr. Feynman_), I now differentiate between shallow understanding and deep understanding. I believe there is no theoretical limit to the depth to which one can achieve understanding. I find the word "understanding" a bit problematical, because I don't fully understand what the word means. I prefer the word "comprehension" because its etymology is clearer. "Comprehend" means "to capture with". I capture knowledge by constructing a mental model that resembles (in both structure and behavior) the object of my contemplation. Often, I need to construct a physical model to play with, or a computer model to interact with before I can get a good mental picture. Using Lisp as a metaphor, I measure the depth of my understanding by the number of levels of "chunking" or decomposition between my overall model, and its atomic constituents. I also measure my depth of understanding by the number and richness of concrete instances of an abstract model. Here is where computers and AI are a bit behind humans. When it comes to models, analogies, metaphors, and parables, computers are just getting started. Symbolic representation is in its infancy. For me to understand something well, I need multiple interchangeable models. I need a verbal or mathematical representation, which I can manipulate formally, and I also need a visual or geometric representation which I can manipulate like a cartoon in my head (or on my computer graphics display). To my mind, the next great advance in computer understanding comes with the computer's ability to project an animated color image that graphically represents (re-presents) the structure and behavior of a system by transforming a symbolic (i.e. ASCII) representation into a visual (or audible) form. Bi-directional information-preserving transformations are the central tool of modeling. We see examples in Fourier Transforms, Analytical Geometry, Digital Signal Processing, Holograms, Analog Computers, and various Duality Theories. --Barry Kort