editione1.0.2Updated November 2, 2022
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I believe that at the end of the century the use of words and general educated opinion will have altered so much that one will be able to speak of machines thinking without expecting to be contradicted.Alan Turing*
This chapter covers Alan Turing, the initial developments of artificial intelligence at Bletchley Park in England, and how they helped break Germany’s codes and win World War II. I also describe the development of the Turing machine and Turing test, which became the golden test for testing artificial intelligence systems for decades. We’ll also meet Arthur Samuel and Donald Michie, who started early developments in artificial intelligence systems and created engines for systems to play games.
During the Second World War, the British and the Allies had the help of thousands of codebreakers located at Bletchley Park in the UK. In 1939, one of these sleuths, Alan Turing, a young mathematician and computer scientist, was responsible for the design of the electromechanical machine named the Bombe. The British used this device to break the German Enigma Cipher.* At the same location in 1943, Tommy Flowers, with contributions from Turing, designed the Colossus, a set of computers built with vacuum tubes, to help the Allies crack the Lorenz Cipher.* These two devices helped break the German codes and predict Germany’s strategy. According to US General Eisenhower, cracking the enemy codes was decisive for the Allies winning the war.
These events marked the initial development of artificial intelligence. In their free time during the war, Turing and Donald Michie, a cryptographer recruited to Bletchley Park, had a weekly chess game. While playing, they talked about how to write a computer program that would play against human opponents and beat them. They sketched their designs with pen and paper. Unfortunately, they never went ahead and coded their program. At the time, the state-of-the-art computer was the Atanasoff-Berry computer, designed to only solve linear equations. It would have been very hard for the pair to code a program that could beat humans using such computers. However, these meetings contributed to the early beginnings of the artificial intelligence field. Because of his work during and after the war, Turing became known as the father of theoretical computer science and artificial intelligence.
But when the war ended, the group that once worked together at Bletchley Park parted ways. Turing, however, did not stop his research; he continued in the computer field. He had already made a name for himself before the war with his seminal 1936 paper* on computing, explaining how machines like computers worked. This mathematical structure became the basis for modeling computers and was later named the Turing machine. Between 1945 and 1947, Turing designed the Automatic Computing Engine (ACE), an early electronic stored-program computer, at the National Physical Laboratory. He continued pursuing the idea of writing a chess program and worked on the theoretical framework for doing so. By 1948, he, working with David Champernowne, a former undergraduate colleague, began coding the program even though no computer at the time could run it. By 1950, he had finished Turochamp.
In 1952, he tried to implement Turochamp on a Ferranti Mark 1, the first commercially available general-purpose electronic computer. But the machine lacked enough computing power to execute Turochamp. Instead, Turing ran the computer program by hand, flipping through the pages of the algorithm. This exercise marked the first demonstration of a working artificial intelligence system. It would take 45 more years for a computer program to win against a chess world champion. The humble beginnings of AI started with Turing’s work.
With the rapid development in computing and AI, Turing wrote about the future of the field in his 1950 seminal paper “Computing Machinery and Intelligence.”* He predicted that by the 2000s, society’s opinion regarding artificial intelligence would shift completely due to technological advances. His prediction, in some ways, turned out to be correct.
Neural networks are computer systems that are modeled (more or less loosely) on how neurons in the human brain function and interact.
By 1945, Turing was already thinking about how to simulate the human brain with a computer. His Automatic Computing Engine created models of how the brain worked. In a letter to a coworker, he wrote, “I am more interested in the possibility of producing models of the action of the brain than in the practical applications to computing … although the brain may in fact operate by changing its neuron circuits by the growth of axons and dendrites, we could nevertheless make a model, within the ACE, in which this possibility was allowed for, but in which the actual construction of the ACE did not alter, but only the remembered data …”*
In 1948, Turing defined two types of unorganized machines, which would be the first computer models of brains and become the basis of neural networks. He based one on how transistors work and the other on how neural networks would eventually be modeled. Around the same time, he also defined genetic search to configure his unorganized machines by searching for the best model of a neural network for a given task.
Figure: Alan Turing, who founded the fields of theoretical computer science and artificial intelligence.
The Turing test is a game where players try to guess which of two participants is a computer. The evaluators are only aware that one of the two participants is a computer. The conversation uses text-only communication like a computer screen. If the judges cannot reliably tell the machine from the human, then the computer passes the test and can be said to exhibit human-level intelligence.
Alan Turing defined the Imitation Game in 1950; it later became more commonly known as the Turing test and became the golden test for figuring out if a computer exhibits the same intelligence as a human. In the party game that inspired the Imitation Game, a man and a woman occupy different rooms, and the onlookers try to guess who is in which room by reading their typewritten responses to questions. The contestants answer in a way that tries to convince the judges that they are the other person. In the Turing test, instead of a man and a woman, the interaction happens between a human and a computer.
Figure: The Turing test. During the Turing test, the human questioner asks a series of questions to both respondents. After the specified time, the questioner tries to decide which terminal is operated by the human respondent and which terminal is operated by the computer.
After the war, Michie, Turing’s friend and fellow codebreaker, became a senior lecturer in surgical science at the University of Edinburgh. Even though his day job was not related to AI, he continued working on the development of artificial intelligence systems, especially games.
Michie did not have access to a digital computer because they were too costly at the time. While many hurdles existed, he developed a program to play a perfect tic-tac-toe game with 304 matchboxes, each representing a unique board state.* Michie’s machine not only played tic-tac-toe but was also able to improve on its own over time—learning how to better play the game.
In 1949, a coder named Arthur Samuel, an expert on vacuum tubes and transistors at IBM, brought IBM’s first commercial general-purpose digital computers to the market. On the side, he worked to implement a program that, by 1952, could play checkers against a human opponent. It was the first artificial intelligence program to be written and run in the United States. He worked tirelessly, and in 1956, he demonstrated it to the public. Samuel improved the underlying software by hand, and when he had access to a computer, he made changes there.
As time passed, he started wondering if the machine could make the same improvements by itself, instead of him having to write the rules for the program by hand. He pondered whether the device could do all the fine-tuning itself. With this idea in mind, he published a paper titled “Some Studies in Machine Learning Using the Game of Checkers.”*
Machine learning is the process in which a machine learns the variables of a problem and fine tunes them on its own instead of humans hard-coding the rules for reaching the solution.
Samuel’s publication marked the birth of machine learning. One of the two learning techniques that Samuel described in his paper was called rote learning. Today, this technique is known as memoization, a computer science strategy used to speed up computer programs. The other method involved measuring how good or bad a specific board position was for the computer or its human opponent. By improving the measurement of a board state, the program could become better at playing the game. In 1961, Samuel’s program beat the Connecticut state checker champion. It was the first time that a machine trumped a player in a state competition, a pattern that would repeat in the years to come.
If after I die, people want to write my biography, there is nothing simpler. They only need two dates: the date of my birth and the date of my death. Between one and another, every day is mine.Fernando Pessoa*
The birth of artificial intelligence was seen with the initial development of neural networks including Frank Rosenblatt’s creation of the perceptron model and the first demonstration of supervised learning. That led to the Georgetown-IBM experiment, an early language translation system. Finally, the end of the beginning was marked by the Dartmouth Conference, at which artificial intelligence was officially launched as a field in computer science, leading to the first government funding of AI.