Newell, A., & Simon, H. A. (1976). Computer science as empirical inquiry: Symbols and search. Commun. ACM, 19(3), 113–126. https://doi.org/10.1145/360018.360022
Summary
In this article, Simon & Newell argue that intelligence can be defined as the ability to generate and test solutions. Thus, to determine if something is intelligent, we need a set of necessary conditions for this ability. For Simon & Newell, these necessary conditions are satisfied by a physical symbol system.
Key terms
- Scientific enterprise = an activity where scientific hypotheses are developed and then verified by empirical inquiry.
- Law of qualitative structure = a concise characterization of the essential nature of a scientific discipline, which define the scope of knowledge in that discipline and “how the whole science operates”; examples include the cell doctrine in biology, plate tectonics in geology, the germ theory of disease, and the doctrine of atomism.
- Physical symbol system = collections of patterns and the processes that modify them; “a machine that produces through time an evolving collection of symbol structures.”
- Symbol = physical patterns that serve as components of an entity called a expression.
- Expression = also symbol structure; a composition of tokens, or instances, of symbols which are related to each other in some physical way.
- Designation = “an expression designates an object it, given the expression, the systems can either affect the object itself or behave in ways dependent on the object.”
- Interpretation = a special form of dependent action where, given an expression that designates a process, the system is able to carry out the process.
- The Physical Symbol System Hypothesis = a law of qualitative structure which claims “a physical symbol system has the necessary and sufficient means for general intelligent action.”
- Heuristic search = a second law of qualitative structure for AI where “symbol systems solve problems by generating potential solutions and testing them” (i.e., searching).
Reading notes
On the nature of science and empirical inquiry
Computer science is the study of the phenomena surrounding computers. … The machine—not just the hardware, but the programmed, living machine—is the organism we study.
- Meta-scientific understanding of a discipline must always struggle to catch up with scientific progress: “For the hare as lecturer will have to make an annual sprint to overtake the cumulation of small, incremental gains that the tortoise of scientific and technical development has achieved in his steady march. Each year will create a new gap and a new sprint, for in science there is no final word.”
- Scientific progress is made when it leads to technological progress: “[Society] needs to understand that, as in any science, the gains that accrue from such experimentation and understanding pay of in the permanent acquisition of new techniques; and that it is these techniques that will create the instruments to help society in achieving its goals.”
- Laws of qualitative structure define the scope of knowledge in discipline: “All sciences characterize the essential nature of the systems they study. These characterizations are invariably qualitative in nature, for they set the terms within which more detailed knowledge can be developed.”
Now that [the theory] is accepted, the whole earth seems to offer evidence for it everywhere, for we see the world in its terms.
On intelligence, in general
We measure the intelligence of a system by its ability to achieve stated ends in the face of variations, difficulties, and complexities posed by the task environment.
- Intelligence is a primary concern of computer science: “All information is processed by computers in service of ends, and we measure the intelligence of a system by its ability to achieve stated ends in the face of variations, difficulties, and complexities posed by the task environment.”
Intelligence [can be equated with] ability to extract and use information about the structure of the problem space, so as to enable a problem solution to be generated as quickly and directly as possible.
Computer science as an empirical discipline
Each new program that is built is an experiment. It poses a question to nature, and its behavior offers clues to an answer.
- Computer science is an empirical discipline: “Actually constructing the machine poses a question to nature; and we listen for the answer by observing the machine in operation and analyzing it by all analytical and measurement means available. Each new program that is built is an experiment. It poses a question to nature, and its behavior offers clues to an answer.”
- “We would have called it an experimental science, but like astronomy, physics, and geology, some of its unique forms of observation and experience do not fit a narrow stereotype of the experimental method.”
Physical symbol systems
The two most significant classes of symbol systems with which we are acquainted are human beings and computers.
- Physical symbol systems consist of patterns and processes for modifying patterns: “The most important properties of patterns is that they can designate objects, processes, or other patterns, and that, when they designate processes, they can be interpreted. Interpretation means carrying out the designated process.”