Alan Turing and AI: A Journey into the History of Artificial Intelligence

6 min readJun 17, 2023

Artificial intelligence (AI) has become integral to our modern lives, powering voice assistants, autonomous vehicles, and intelligent systems that can understand and respond to human behavior. But where did it all begin? The roots of AI can be traced back to the mid-20th century, with the groundbreaking work of British mathematician and computer pioneer Alan Turing.

Alan Turing — Father of Artificial Intelligence

Alan Turing’s theoretical work laid the foundation for AI as we know it today. In 1935, Turing introduced the concept of a universal computing machine, a theoretical device capable of performing any computation. This machine, known as the universal Turing machine, had a limitless memory and could modify its own program, paving the way for the idea of machines that can learn and improve.

Turing’s contributions to AI were not limited to theory. During World War II, he worked as a cryptanalyst at Bletchley Park, where he helped break the German Enigma code. It was during this time that he contemplated the possibilities of machine intelligence. Turing envisioned computers that could learn from experience and solve new problems using guiding principles, a process now known as heuristic problem-solving.

In 1947, Turing delivered a lecture in London, expressing his desire for a machine that could learn from experience. He also discussed the possibility of machines altering their own instructions to achieve this goal. Although Turing’s ideas were ahead of their time, they laid the groundwork for future advancements in AI.

Chess and AI

One area where Turing applied his ideas was in the game of chess. He recognized chess as a domain that could challenge AI systems and provide a testing ground for problem-solving methods. While Turing experimented with designing chess programs, the lack of available computing power at the time limited his progress. It was not until the advent of stored-program electronic digital computers that the first true AI programs could be developed.

Early AI Milestones

Early milestones in AI were achieved through the development of AI programs:

◾1950s

▪ ️Christopher Strachey wrote the first successful AI program

◾1952

▪️ Anthony Oettinger developed Shopper, a rote learning program to simulate a shopping experience.

▪️ Arthur Samuel’s checker’s program, written in 1952, was one of the first examples of evolutionary computing, where successive generations of the program compete and evolve to improve their performance.

▪️ In the field of logical reasoning and problem-solving, Allen Newell, J. Clifford Shaw, and Herbert Simon created the Logic Theorist. The program could prove theorems from Principia Mathematica, demonstrating the power of AI in logical reasoning tasks.

▪️ John McCarthy combines elements of IPL with lambda calculus to create the programming language LISP (List Processor).

▪️Development of the General Problem Solver (GPS), which could solve a wide range of puzzles using a trial-and-error approach.

◾1960

▪️ LISP becomes the principal language for AI work in the United States.

▪️Alan Robinson invents the resolution theorem-proving technique at Argonne National Laboratory, leading to the development of the logic programming language PROLOG.

▪️AI also made its way into human-like conversation with programs like Eliza and Parry. Eliza, developed by Joseph Weizenbaum simulated a human therapist.

◾1970s

▪️PROLOG gains popularity and becomes widely used for AI work in Europe and Japan.

▪️Alain Colmerauer implements PROLOG at the University of Aix-Marseille, France.

◾1980s

▪️Fifth-generation languages, based on PROLOG, are developed at the Institute for New Generation Computer Technology in Tokyo for use on nonnumerical parallel computers.

◾1990s

▪️Development of languages for reasoning about time-dependent data using tense logic, allowing statements to be located in the flow of time.

◾21st century

▪️Advancements continue in AI programming languages and techniques, including machine learning, deep learning, and neural networks.

▪️Ongoing research and innovation in AI languages and frameworks to address complex problems and improve AI capabilities.

▪️The integration of AI programming languages into various industries and applications shapes the future of artificial intelligence.

The Turing Test

In 1950, Turing introduced the Turing test, a practical test for computer intelligence. The test involves a computer, a human interrogator, and a human foil. The interrogator interacts with both the computer and the human foil through a keyboard and display screen, attempting to determine which is the computer. If the computer can successfully convince the interrogator that it is human, it is considered an intelligent entity.

While the Turing test remains a benchmark for AI, no AI program has yet passed it in its pure form. However, recent advancements in natural language processing and chatbot technology. Back in 2012, Ray Kurzweil renowned author and futurist, predicted at the Journal‘s CFO Network annual conference in Washington, that in 2029, computers will have the capacity to pass the Turing test.

It is now 2023 and the development of ChatGPT has reignited discussions about the test’s components being met sooner than we expect.

Source:
Artificial intelligence — Evolutionary computing | Britannica
Turing machine — Wikipedia

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