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What Was John McCarthy’s Foundational Definition of Intelligence for AI?
Learn AI pioneer John McCarthy’s specific definition of intelligence. Understand his view of intelligence as the computational part of the ability to achieve goals, a concept that became central to the development of artificial intelligence systems.
Question
According to John McCarthy, what is intelligence?
A. The ability to adapt and solve problems in new situations.
B. Learning from experience, as defined by a consensus of experts.
C. The computational part of the ability to achieve goals in the world.
D. A concept exclusively connected to natural, human thought processes.
Answer
C. The computational part of the ability to achieve goals in the world.
Explanation
The AI pioneer’s description provided a concise, specific definition that emphasized the operational aspect of intelligence, allowing it to be replicated through machines and not just confined to biological entities.
John McCarthy, a founding figure in artificial intelligence who also coined the term, proposed this definition to create a framework for intelligence that was not exclusively tied to human or biological minds. His definition is pragmatic and engineering-oriented, breaking down a complex concept into components that could be simulated by a machine.
Deconstructing McCarthy’s Definition
The computational part: This is the core of his definition. It posits that the processes associated with intelligence—such as reasoning, problem-solving, and planning—are fundamentally computational. This means they can be described by algorithms and executed by a computer. It intentionally separates the “how” (computation) from the “what” (the biological brain).
- The ability to achieve goals: This component frames intelligence as functional and purpose-driven. An intelligent agent or system is not just processing information randomly; it is using that processing to accomplish specific objectives within its environment.
- In the world: This anchors intelligence to a practical context. A system’s ability to achieve goals is measured by its performance in a real or simulated environment, not in a theoretical vacuum.
- This definition was instrumental because it provided a clear, actionable goal for AI researchers: to build machines that could compute solutions to achieve specified goals.
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