Artificial Intelligence Current Status and Future Potential (1985) / Chapter Skim
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Artificial Intelligence: Current Status and Future Potential
Artificial Intelligence: Current Status and Future Potential
Pages 11-23
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From page 11... ...
In our early work, Al Newell, Cliff Shaw, and I referred to what we were doing as "complex information processing." But since that's a rather bland phrase compared with the challenging claim that our field has something to do with intelligence, it is the AI label that has stuck. A QUARTER CENTURY OF RESEARCH Ai has been very much in the public eye during the past two or three years.
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From page 12... ...
We tend to think of a computer application as automation if the task performed has a well-defined goal and structure and well-defined alternatives, and especially if it is performed in a carefully designed, simplified environment. Thus, automatic welding in a factory setting is automation and is not usually regarded as artificial intelligence; welding performed on pipes on an irregular sea bottom may require a device that is much more flexible in its responses, hence one that genuinely incorporates techniques of artificial intelligence.
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From page 13... ...
People, including some members of the computer science community, have often been extremely skeptical that computers could exhibit anything that could reasonably be called intelligence or could compete with humans in the quality of their performance of professional-level tasks. Only concrete demonstration with running and debugged computer programs has been able, step by step, to gain ground against that skepticism.
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From page 14... ...
symbols, output (write) symbols, create structures of symbols related in various ways, store symbols and symbol structures in a memory, compare symbol structures for identity or difference, and branch (adapt its behavior)
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From page 15... ...
Artificial intelligence thereby becomes a major direction in which we seek to increase productivity in our society, so that we will have the resources to meet the human, social, and security needs of that society. The second goal of Ai, or of the related field called cognitive science, is to understand and improve human thinking and learning processes, using the computer as a central tool to build models of those processes.
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From page 16... ...
It is a good environment in which to learn how people deal with complexity that forbids exhaustive search or exact algorithms. A study of human chess experts -- grand masters -- began to reveal the bases of their skill.
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From page 17... ...
The program may achieve its expert performance by borrowing some of the tricks that human professionals use in performing the same task, or it may rely largely on the brute force speed and memory size of modern computers. Most existing expert systems combine these two sources of power: they use heuristics, or rules of thumb, borrowed from people, in order to search selectively and intelligently, rather than depending on massive search by pure trial and error.
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From page 18... ...
In addition to the examples I have already mentioned, there are systems for interpreting the data in mass spectrograms, systems for configuring complex computer systems to meet the requirements of particular customers, systems for scheduling large job shops, systems for interpreting oil well drilling logs, and others. And as I mentioned earlier, the boundary is very vague between the expert systems that we call artificial intelligence systems and other kinds of highly automatic control systems.
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From page 19... ...
The underlying analytic techniques for designing and building such systems have been drawn mainly from control theory. Current robotics research aims at relaxing the limits on automation in two related directions: first by providing the machines with sophisticated sensory organs -- "eyes" and "ears" -- so that they can locate and manipulate the materials they are dealing with, and flexible manipulative faculties -- "hands" and "legs" -- so that they can perform complex actions in continually varying circumstances.
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From page 20... ...
SYSTEMS FOR SCIENTIFIC DISCOVERY To take a still deeper look into the future, I would like now to describe work that is still in the basic research stage and far from practical application. I refer to computer systems that, by examining empirical data, can discover new scientific laws.
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From page 21... ...
There are also the AM and EURISKO systems constructed by Douglas Lenat, which have labored mainly in the domain of mathematical discovery, and the META-DENDRAL system that discovered certain chemical laws relating to mass spectrogram analysis. Only the future will tell what potential these systems have for practical application.
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From page 22... ...
On the basis of experience in constructing and testing adaptive production systems of this kind, we can design learning experiences for human students that will allow them to acquire new skills (to build new productions in their minds)
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From page 23... ...
Our society has many needs that we do not feel are being met adequately. We are now engaged in a great national debate to determine how scarce resources are to be allocated among national security, health, consumer goods, investment, the environment, energy needs -- all of these in the face of a growing national debt.
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