AI used to be a science. In the old days (back when AI didn’t work very well), people were attempting to develop a working theory of cognition.
Those scientists didn’t succeed, and those days are behind us.
I claim many of them did succeed, for example:
George Boole invented boolean algebra in order to establish (part of) a working theory of cognition—the book where he introduces it is titled “An Investigation of the Laws of Thought,” and his stated aim was largely to help explain how minds work.[1]
Ramón y Cajal discovered neurons in the course of trying to better understand cognition.[2]
Turing described his research as aimed at figuring out what intelligence is, what it would mean for something to “think,” etc.[3]
Shannon didn’t frame his work this way quite as explicitly, but information theory is useful because it characterizes constraints on the transmission of thoughts/cognition between people, and I think he was clearly generally interested in figuring out what was up with agents/minds—e.g., he spent time trying to design machines to navigate mazes, repair themselves, replicate, etc.
Geoffrey Hinton initially became interested in neural networks because he was trying to figure out how brains worked.
Not all of these scientists thought of themselves as working on AI, of course, but I do think many of the key discoveries which make modern AI possible—boolean algebra, neurons, computers, information theory, neural networks—were developed by people trying to develop theories of cognition.
The opening paragraph of Boole’s book: “The design of the following treatise is to investigate the fundamental laws of those operations of the mind by which reasoning is performed; to give expression to them in the symbolical language of a Calculus, and upon this foundation to establish the science of Logic and construct its method; to make that method itself the basis of a general method for the application of the mathematical doctrine of Probabilities; and, finally, to collect from the various elements of truth brought to view in the course of these inquiries some probable intimations concerning the nature and constitution of the human mind.”
From Cajal’s autobiography: ”… the problem attracted us irresistibly. We saw that an exact knowledge of the structure of the brain was of supreme interest for the building up of a rational psychology. To know the brain, we said, is equivalent to ascertaining the material course of thought and will, to discovering the intimate history of life in its perpetual duel with external forces; a history summarized, and in a way engraved in the defensive neuronal coordinations of the reflex, of instinct, and of the association of ideas” (305).
The opening paragraph of Turing’s paper, Computing Machinery and Intelligence: “I propose to consider the question, ‘Can machines think?’ This should begin with definitions of the meaning of the terms ‘machine ‘and ‘think’. The definitions might be framed so as to reflect so far as possible the normal use of the words, but this attitude is dangerous. If the meaning of the words ‘machine’ and ‘think ’are to be found by examining how they are commonly used it is difficult to escape the conclusion that the meaning and the answer to the question, ‘Can machines think?’ is to be sought in a statistical survey such as a Gallup poll. But this is absurd. Instead of attempting such a definition I shall replace the question by another, which is closely related to it and is expressed in relatively unambiguous words.”
I claim many of them did succeed, for example:
George Boole invented boolean algebra in order to establish (part of) a working theory of cognition—the book where he introduces it is titled “An Investigation of the Laws of Thought,” and his stated aim was largely to help explain how minds work.[1]
Ramón y Cajal discovered neurons in the course of trying to better understand cognition.[2]
Turing described his research as aimed at figuring out what intelligence is, what it would mean for something to “think,” etc.[3]
Shannon didn’t frame his work this way quite as explicitly, but information theory is useful because it characterizes constraints on the transmission of thoughts/cognition between people, and I think he was clearly generally interested in figuring out what was up with agents/minds—e.g., he spent time trying to design machines to navigate mazes, repair themselves, replicate, etc.
Geoffrey Hinton initially became interested in neural networks because he was trying to figure out how brains worked.
Not all of these scientists thought of themselves as working on AI, of course, but I do think many of the key discoveries which make modern AI possible—boolean algebra, neurons, computers, information theory, neural networks—were developed by people trying to develop theories of cognition.
The opening paragraph of Boole’s book: “The design of the following treatise is to investigate the fundamental laws of those operations of the mind by which reasoning is performed; to give expression to them in the symbolical language of a Calculus, and upon this foundation to establish the science of Logic and construct its method; to make that method itself the basis of a general method for the application of the mathematical doctrine of Probabilities; and, finally, to collect from the various elements of truth brought to view in the course of these inquiries some probable intimations concerning the nature and constitution of the human mind.”
From Cajal’s autobiography: ”… the problem attracted us irresistibly. We saw that an exact knowledge of the structure of the brain was of supreme interest for the building up of a rational psychology. To know the brain, we said, is equivalent to ascertaining the material course of thought and will, to discovering the intimate history of life in its perpetual duel with external forces; a history summarized, and in a way engraved in the defensive neuronal coordinations of the reflex, of instinct, and of the association of ideas” (305).
The opening paragraph of Turing’s paper, Computing Machinery and Intelligence: “I propose to consider the question, ‘Can machines think?’ This should begin with definitions of the meaning of the terms ‘machine ‘and ‘think’. The definitions might be framed so as to reflect so far as possible the normal use of the words, but this attitude is dangerous. If the meaning of the words ‘machine’ and ‘think ’are to be found by examining how they are commonly used it is difficult to escape the conclusion that the meaning and the answer to the question, ‘Can machines think?’ is to be sought in a statistical survey such as a Gallup poll. But this is absurd. Instead of attempting such a definition I shall replace the question by another, which is closely related to it and is expressed in relatively unambiguous words.”