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Artificial Intelligence: History, Concepts, and the Future

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Abstract

This paper traces the development of artificial intelligence from its conceptual origins in Charles Babbage's 19th-century work through Alan Turing's foundational theories, the rise of expert systems, and ambitious modern projects like Douglas Lenat's CYC. It examines the central philosophical question underlying AI research: what is intelligence, and can it truly be replicated in a machine? The paper surveys landmark milestones — including the Logic Theorist, IBM's chess program, SHRDLU, and BT's experimental "ant" programs — while weighing the arguments of both AI optimists and critics. It concludes by reflecting on the broader implications for what makes human life unique.

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What makes this paper effective

  • The paper opens with a vivid philosophical provocation — Leibniz's thought experiment — that immediately frames the central tension between mechanical description and conscious thought, drawing readers in before any technical content appears.
  • It uses a clear chronological structure, moving from Babbage to Turing to modern expert systems, which makes a complex intellectual history accessible and easy to follow.
  • The paper balances technical explanation with philosophical reflection, acknowledging both the achievements and the genuine limitations of AI research without overstating either side.

Key academic technique demonstrated

The paper effectively deploys expert testimony and direct quotation to advance its argument. Rather than relying solely on the author's voice, it weaves in authoritative perspectives — from Turing and Newell to Dreyfus and Ward — letting credible voices anchor each stage of the argument. This technique builds intellectual credibility while illustrating that the AI debate spans philosophy, computer science, and cultural commentary.

Structure breakdown

The paper opens with a philosophical epigraph and a framing paragraph that establishes the core dilemma. It then proceeds chronologically through the history of AI before pivoting to conceptual debates about the definition of intelligence. The middle sections evaluate specific AI systems (expert systems, SHRDLU, CYC) as concrete case studies. The closing section zooms out to the broader cultural and philosophical stakes, ending with a forward-looking reflection on what AI's progress means for human identity.

Introduction to Artificial Intelligence

"What if these theories are really true, and we were magically shrunk and put into someone's brain while he was thinking. We would see all the pumps, pistons, gears and levers working away, and we would be able to describe their workings completely, in mechanical terms, thereby completely describing the thought processes of the brain. But that description would nowhere contain any mention of thought! It would contain nothing but descriptions of pumps, pistons, levers!"

— Gottfried Wilhelm Leibniz (1679)

Not even a century ago — in fact, not even a half-century ago — few people could have imagined the present-day world with computers operating most government and business processes and the Internet running in millions of homes. Thus it would have been nearly impossible to comprehend artificial intelligence (AI) and the idea that scientists would try to create a machine capable of learning, adapting, reasoning, and correcting or improving itself. Whether or not this will become a reality is still unknown.

Origins and Early Milestones

AI pioneer Chris Langton says that this "intelligent entity" will never be possible. He believes that "when scientists are faced with the choice of either admitting that the computer process is alive, or moving the goalposts to exclude the computer from the exclusive club of living organisms, they will choose the latter." Is this true? Will humans never admit that a computer can actually function as real life? Or will they instead decide there is nothing special about life, and that humanity can therefore be designed, built, and replicated? At least for the time being, there is no answer to this dilemma.

According to the American Association for Artificial Intelligence, AI is "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines." The evolution of this science became notable as early as 1821, when Charles Babbage stared at a table of logarithms and said, "I think that all these tables might be calculated by machinery." From that point on, he devoted his life to developing the first programmable computer.

Much later, in 1943, Babbage's idea finally took hold when Warren McCulloch — a psychiatrist, cybernetician, philosopher, and poet — and Walter Pitts, a research student in mathematics, published an innovative paper combining early twentieth-century ideas on computation, logic, and the nervous system. The report promised to revolutionize both psychology and philosophy. The following year, those ideas were applied to develop the first American programmable computer, the Merck I.

It did not take long for British scientist Alan Turing to recognize the similarity between the computational process and human thinking. In his paper "Computing Machinery and Intelligence," he outlined the direction for the remainder of the century: developing computers for game playing, decision-making, natural language understanding, translation, theorem proving, and encryption code cracking.

The Turing Test and the Question of Intelligence

In the 1950s, Newell, Shaw, and Simon created the program Logic Theorist (later called General Problem Solver), which used recursive search techniques — defining a solution in terms of itself. IBM developed the first program capable of playing a full game of chess in 1957. The following year, Newell, Shaw, and Simon observed: "There are now in the world machines that think, that learn and that create. Moreover, their ability to do these things is going to increase rapidly until — in a visible future — the range of problems they can handle will be co-extensive with the range to which the human mind has been applied" (Simon, p. 3).

To help determine if and when a computer had actually become intelligent, Turing proposed the "imitation game," in which an interrogator would interview both a human being and a computer without knowing which was which, with all communication conducted through textual messages. Turing argued that if the interrogator could not distinguish between the two through questioning, it would be unreasonable to deny that the computer was intelligent. This concept is now commonly known as the Turing test for intelligence.

In 1967, a university computer won the first tournament match against a human chess player. World chess champion Gary Kasparov declared in 1988 that there was "no way" a grandmaster would be defeated by a computer in a tournament before 2000. Ten months later, he lost the bet. However, many people changed their position and argued that winning a championship chess game did not require "real" intelligence. For a number of observers, the connection between human and machine was becoming a little too close for comfort.

This was precisely why Turing had developed his test — any other attempt to define intelligence seemed to run into problems. The AI specialists themselves were not especially excited by the chess victory, because the computer — which relied on custom chips inside a machine — was seen as a kind of idiot savant, able to play a strong game of chess without any understanding of why it did what it did (Gershenfeld, 1999, p. 130).

As one critic noted, this represents a curious argument: it retroactively adds a clause to the Turing test, demanding that not only must a machine be able to match human performance at quintessentially intelligent tasks such as chess or conversation, but that the way it does so must also be deemed satisfactory (ibid).

3 Locked Sections · 880 words remaining
36% of this paper shown

Expert Systems and Their Limitations · 310 words

"Knowledge bases, inference engines, and their shortfalls"

The CYC Project and Common Sense · 320 words

"Lenat's ambitious attempt to give computers common sense"

AI, Artificial Life, and the Future · 250 words

"AI's broader implications for human uniqueness and the future"

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Key Concepts in This Paper
Turing Test Expert Systems CYC Project Common Sense Knowledge Base Machine Intelligence Artificial Life Natural Language Recursive Search Intelligent Machines
Cite This Paper
PaperDue. (2026). Artificial Intelligence: History, Concepts, and the Future. PaperDue. https://www.paperdue.com/study-guide/artificial-intelligence-history-concepts-future-172651

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