The Turing Test: An Overview
In this essay, I describe in detail a hypothetical test contemporarily known as the Turing test along with it’s respective objective. In addition, I examine a distinguished objection to the test, and Turing’s consequential response to it.
Created by English mathematician Alan Turing, the Turing test (formerly known as the imitation game) is a behavioral approach that assesses a system’s ability to think. In doing so, it can determine whether or not that system is intelligent. This experiment initiated what is now commonly known as artificial intelligence.
In Turing’s test, an isolated interrogator attempts to distinguish the identities between discreet human and computer subjects based upon their replies to a series of questions asked during the interrogation process. Questions are generally generated through the use of a keyboard and screen, thus communication can only be made through text-only channels. For example, a sample question would contain something along the lines of “What did you think about the weather this morning?” and adequate responses could include, “I do tend to like a nice foggy morning, as it adds a certain mystery” or rather “Not the best, expecting pirates to come out of the fog” or even “The weather is not nice at the moment, unless you like fog”. After a series of tests are performed, if the interrogator fails at identifying the subject more than 70 percent of the time, that subject is deemed intelligent. Simply put, the interrogator’s ability to declare the machine’s capability of intelligence directly correlates to the interrogator’s inability to distinguish between the two subjects.
There are many objections to Turing’s theory. The most notable objection i...
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...ped with such knowledge, giving them the rudimentary ability to understand the semantics in which Searle describe. This too, can be reflected in Turing’s test, given that language is a prominent factor in the experiment.
In this paper, I have attempted to concisely yet methodically explain the Turing Test and its respective objection and rebuttals. Both Turing and Searle’s comparisons between humans and computers in a methodological manner alike illustrate their opposing views on the topic. However, following Searle’s reasoning against Turing’s experiment, it is clear that he lacks adequacy for his reasoning. This is most commonly found in Searle’s tendency to base his theories off assumptions. In doing so, Turing’s ideal responses effortlessly undermine any substance Searle might have had, thus proving his to be the stronger theory.
Cierra Smith
Andy Clark strongly argues for the theory that computers have the potential for being intelligent beings in his work “Mindware: Meat Machines.” The support Clark uses to defend his claims states the similar comparison of humans and machines using an array of symbols to perform functions. The main argument of his work can be interpreted as follows:
Searle's argument delineates what he believes to be the invalidity of the computational paradigm's and artificial intelligence's (AI) view of the human mind. He first distinguishes between strong and weak AI. Searle finds weak AI as a perfectly acceptable investigation in that it uses the computer as a strong tool for studying the mind. This in effect does not observe or formulate any contentions as to the operation of the mind, but is used as another psychological, investigative mechanism. In contrast, strong AI states that the computer can be created so that it actually is the mind. We must first describe what exactly this entails. In order to be the mind, the computer must be able to not only understand, but to have cognitive states. Also, the programs by which the computer operates are the focus of the computational paradigm, and these are the explanations of the mental states. Searle's argument is against the claims of Shank and other computationalists who have created SHRDLU and ELIZA, that their computer programs can (1) be ascribe...
John Searle’s Chinese room argument from his work “Minds, Brains, and Programs” was a thought experiment against the premises of strong Artificial Intelligence (AI). The premises of conclude that something is of the strong AI nature if it can understand and it can explain how human understanding works. I will argue that the Chinese room argument successfully disproves the conclusion of strong AI, however, it does not provide an explanation of what understanding is which becomes problematic when creating a distinction between humans and machines.
In Searle’s first argument against the distinction between the mental and physical, he assumes this mistaken assumption is largely due to one’s common-sense supposition that there indeed is a distinction between the mental and physical at some deep metaphysical level. Searle confronts this assumption with the simple fact that he believes Consciousness it is a systematic biological phenomenon, much like digestion, and as such, concludes, that consciousness is a feature of the brain as such such is part of the physical world. However, I agree with Searle in the sense that the through simple reduction there incidentally will be a metaphysical distinction between mental and physical, however I disagree with the way in which he counters this.
This world of artificial intelligence has the power to produce many questions and theories because we don’t understand something that isn’t possible. “How smart’s an AI, Case? Depends. Some aren’t much smarter than dogs. Pets. Cost a fortune anyway. The real smart ones are as smart as the Turing heat is willing to let ‘em get.” (Page 95) This shows that an artificial intelligence can be programmed to only do certain ...
He would say that it is still impossible for a computer to derive semantic information from merely syntax because the two things, according to him, are mutually exclusive when separate. It is impossible to gain any semantic information from syntax alone, which would mean that even if a robot was interacting with the world, the computer inside the robot is only getting syntactical information and processes it in syntactical terms only. It is also important to note, in the words of Searle, that a computer’s “operations have to be defined syntactically, whereas consciousness, thoughts, feelings, emotions, and all the rest of it involve more than syntax.” (Searle, p.681) Therefore, even though a robot would be able to simulate being a human, it cannot actually be a human. I then believe, with that evidence, Searle would conclude that the Robot reply would not satisfy the conditions needed for a computer to be able to
In this paper I will evaluate and present A.M. Turing’s test for machine intelligence and describe how the test works. I will explain how the Turing test is a good way to answer if machines can think. I will also discuss Objection (4) the argument from Consciousness and Objection (6) Lady Lovelace’s Objection and how Turing responded to both of the objections. And lastly, I will give my opinion on about the Turing test and if the test is a good way to answer if a machine can think.
One of the hottest topics that modern science has been focusing on for a long time is the field of artificial intelligence, the study of intelligence in machines or, according to Minsky, “the science of making machines do things that would require intelligence if done by men”.(qtd in Copeland 1). Artificial Intelligence has a lot of applications and is used in many areas. “We often don’t notice it but AI is all around us. It is present in computer games, in the cruise control in our cars and the servers that route our email.” (BBC 1). Different goals have been set for the science of Artificial Intelligence, but according to Whitby the most mentioned idea about the goal of AI is provided by the Turing Test. This test is also called the imitation game, since it is basically a game in which a computer imitates a conversating human. In an analysis of the Turing Test I will focus on its features, its historical background and the evaluation of its validity and importance.
The official foundations for "artificial intelligence" were set forth by A. M. Turing, in his 1950 paper "Computing Machinery and Intelligence" wherein he also coined the term and made predictions about the field. He claimed that by 1960, a computer would be able to formulate and prove complex mathematical theorems, write music and poetry, become world chess champion, and pass his test of artificial intelligences. In his test, a computer is required to carry on a compelling conversation with humans, fooling them into believing they are speaking with another human. All of his predictions require a computer to think and reason in the same manner as a human. Despite 50 years of effort, only the chess championship has come true. By refocusing artificial intelligence research to a more humanlike, cognitive model, the field will create machines that are truly intelligent, capable of meet Turing's goals. Currently, the only "intelligent" programs and computers are not really intelligent at all, but rather they are clever applications of different algorithms lacking expandability and versatility. The human intellect has only been used in limited ways in the artificial intelligence field, however it is the ideal model upon which to base research. Concentrating research on a more cognitive model will allow the artificial intelligence (AI) field to create more intelligent entities and ultimately, once appropriate hardware exists, a true AI.
...at today is known as the Turing Test. This was a test where a person would ask questions from both a human and a machine without knowing which was which. If after a reasonable amount of time the difference between the two was not obvious, then the machine was thought to be somewhat intelligent. A version of this test is still used today by the Boston Museum of Computers to host a contest of the best artificial machines for the Loebner Prize.
Specifically, in how the theory likens conscious intelligence to a mimicry of consciousness. In Alan Turing’s study of computing and consciousness, he developed the Turing Test, which essentially led to the notion that if a computing machine or artificial intelligence could perfectly mimic human communication, it was deemed ‘conscious’. REF. However, many do not agree and instead argue that while computers may be able to portray consciousness and semantics, it is not commensurable to actual thought and consciousness. Simulation is not the same as conscious thinking, and having a conscious understanding of the sematic properties of the symbols it is manipulating. This flaw was portrayed in John Searle’s thought experiment, ‘The Chinese Room’. Searle places a person who cannot speak Chinese in a room with various Chinese characters and a book of instructions, while a person outside of the room that speaks Chinese communicates through written Chinese message passed into the room. The non-Chinese speaker responds by manipulating the uninterpreted Chinese characters, or symbols, in conjunction with the syntactical instruction book, giving the illusion that they can speak Chinese. This process simulated the operation of a computer program, yet the non-Chinese speaker clearly had no understanding of the messages, or of Chinese, and was still able to produce
The Turing test was a test introduced by Alan Turing (1912-1954) and it involves having a human in one room and an artificial intelligence, otherwise known as a computer, in another and as well as an observer. Turing himself suggested that as long as the observer is unaware whether it’s a human or a computer in either room the computer should be regarded as having human-level intelligence. (Nunez, 2016). But does the “human-level” intelligence mean it should be considered to be conscious? Is it more important to be clever or to be aware of being clever? Is it moral to create a conscious being that just serves our purposes? Aside from the moral implications there are technical implications and parameters
The traditional notion that seeks to compare human minds, with all its intricacies and biochemical functions, to that of artificially programmed digital computers, is self-defeating and it should be discredited in dialogs regarding the theory of artificial intelligence. This traditional notion is akin to comparing, in crude terms, cars and aeroplanes or ice cream and cream cheese. Human mental states are caused by various behaviours of elements in the brain, and these behaviours in are adjudged by the biochemical composition of our brains, which are responsible for our thoughts and functions. When we discuss mental states of systems it is important to distinguish between human brains and that of any natural or artificial organisms which is said to have central processing systems (i.e. brains of chimpanzees, microchips etc.). Although various similarities may exist between those systems in terms of functions and behaviourism, the intrinsic intentionality within those systems differ extensively. Although it may not be possible to prove that whether or not mental states exist at all in systems other than our own, in this paper I will strive to present arguments that a machine that computes and responds to inputs does indeed have a state of mind, but one that does not necessarily result in a form of mentality. This paper will discuss how the states and intentionality of digital computers are different from the states of human brains and yet they are indeed states of a mind resulting from various functions in their central processing systems.
The position that computers are intelligent is supported by three points: refusing to say that computers are intelligent is prejudice towards computers, being intelligent does not mean that one must be knowledgable in all fields; being intelligent in a single area also proves to display intelligence, and there is no single qualification for intelligence; intelligence is measure...
In order to see how artificial intelligence plays a role on today’s society, I believe it is important to dispel any misconceptions about what artificial intelligence is. Artificial intelligence has been defined many different ways, but the commonality between all of them is that artificial intelligence theory and development of computer systems that are able to perform tasks that would normally require a human intelligence such as decision making, visual recognition, or speech recognition. However, human intelligence is a very ambiguous term. I believe there are three main attributes an artificial intelligence system has that makes it representative of human intelligence (Source 1). The first is problem solving, the ability to look ahead several steps in the decision making process and being able to choose the best solution (Source 1). The second is the representation of knowledge (Source 1). While knowledge is usually gained through experience or education, intelligent agents could very well possibly have a different form of knowledge. Access to the internet, the la...