Before delving into what the test attempts to do, I will give some background to the author of said test.
Alan Mathison Turing OBE FRS (Born 23 June 1912, Died 7 June 1954 (41 years)) was an English mathematician, computer scientist, logician, cryptanalyst, philosopher and theoretical biologist. Turing was highly influential in the development of theoretical computer science, providing a formalisation of the concepts of algorithm and computation with the Turing machine, which can be considered a model of a general-purpose computer and is widely considered to be the father of theoretical computer science.
After graduating from King’s College, Cambridge, in 1938, Turing earned a doctorate degree from Princeton University.
During World War II, Alan Turing worked for the Government Code and Cypher School at Bletchley Park, Britain’s codebreaking centre that produced Ultra intelligence, working in the section responsible for German naval cryptanalysis.
Turing devised techniques for speeding the breaking of German ciphers, including improvements to the pre-war Polish bomba method, an electromechanical machine that could find settings for the German Enigma machine.
After the war, Turing worked at the National Physical Laboratory, where he designed the Automatic Computing Engine, one of the first designs for a stored-program computer. In 1948, Turing joined Max Newman’s Computing Machine Laboratory at the Victoria University of Manchester, where he helped develop the Manchester computers and became interested in mathematical biology. Turing wrote on the chemical basis of morphogenesis and predicted oscillating chemical reactions such as the Belousov–Zhabotinsky reaction, first observed in the 1960s. Despite these accomplishments, he was never fully recognised during his lifetime because much of his work was covered by the Official Secrets Act.
Turing addressed the problem of artificial intelligence and proposed an experiment that became known as the Turing test, an attempt to define a standard for a machine to be called ‘intelligent’.
The idea was that a computer could be said to ‘think’ if a human interrogator could not tell it apart, through conversation, from a human being. In the paper, Turing suggested that rather than building a program to simulate the adult mind, it would be better to produce a simpler one to simulate a child’s mind and then to subject it to a course of education.
A reversed form of the Turing test is widely used on the Internet today. The CAPTCHA test is intended to determine whether the user is a human or a computer.
Originally called the imitation game by Alan Turing in 1949, the idea is to test a machine’s ability to exhibit intelligent behaviour equivalent to, or indistinguishable from, that of a human.
Turing proposed that a human evaluator would judge natural language conversations between a human and a machine designed to generate human-like responses. The evaluator would be aware that one of the two partners in conversation was a machine, and all participants would be separated from one another. The conversation would be limited to a text-only channel, such as a computer keyboard and screen, so the result would not depend on the machine’s ability to render words as speech. If the evaluator could not reliably tell the machine from the human, the machine would be said to have passed the test. The test results would not depend on the machine’s ability to give correct answers to questions, only on how closely its answers resembled those a human would give.
Since the Turing test is a test of indistinguishability in performance capacity, the verbal version generalises naturally to all of human performance capacity, verbal as well as nonverbal.
There is no real way for us to tell whether or not a machine truly understands human semantics. The test simply judges machines on their ability to converse with human-like eloquence, not human-like understanding. This limitation has led some AI researchers to argue the Turing Test is less relevant than it used to be.
Although Alan Turing came up with an influential test while considering whether or not machines can think Turing’s test is not a sufficient indicator of artificial intelligence. Not only does Turing’s test fail to account for whether or not a machine understands its input and output, it also accounts for neither a machine’s ability to recognise patterns nor its ability to apply common knowledge or sense.
Beyond the limitations of the test itself, many AI researchers feel the Turing Test is irrelevant today. With advances in data science and cloud computing, there’s been a growing focus on natural language processing (NLP) and creating large language models like ChatGPT, BERT and now Bard.
Over the past decade, NLP technology has improved dramatically, thereby allowing machines to better understand and generate human-like language with increasing accuracy. Recently, Google created a chatbot called LaMDA that was so good, one of the AI researchers working on it believed it achieved sentience.
There is no official list of questions to pose to the human and machine during a Turing test. Asking the following types of questions, though, can help you tell the machine’s answers from the human’s because they require the interlocutor to generate thoughtful, context-rich, socially appropriate responses.
- Open-ended questions like, “What’s a skill or talent you’d like to develop and why?”
- Opinion questions like, “What is your perspective on technology and its impact on mental health?”
- Emotional questions like, “What’s something from the past that you long for?”
- Personal questions like, “What was it like to fall in love for the first time?”
- Hypothetical scenarios like, “Imagine that you are a museum curator in the future. What artifacts of today would you display in the museum and why?”
- Self-assessment questions like, “How do you think you performed on this test? How human-like are your answers to my questions?”
How to pass the Turing test? After a Q&A series between the judge and the two interlocutors, the judge then evaluates the interlocutors’ responses. Some of the criteria may include:
- Creativity
- Empathy
- Natural language use
- Ethical considerations
- Relevance
If the machine can convince the human judge that it’s human, or if the human judge cannot distinguish between the human’s and machine’s responses, then the machine has passed the Turing test.
While the Turing Test has been a foundational concept in Artificial Intelligence, it has also faced criticism.
In 1980, philosopher John Searle proposed the “Chinese Room Argument,” challenging the idea that passing the Turing test equates to true intelligence.
Searle argued that a machine could pass the Turing test by simply manipulating symbols without understanding them, which does not constitute genuine thinking.
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