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Essays on the turing test
The Turing test conclusion
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Can Computers think? Will they ever be able to think? I do not really have answers to these questions. In this essay I am not going to be able to tell you the answer, or pick a side myself, because I strongly believe that either side could be right. However, in this essay I will convince you that regardless of computers thinking or not, humans do think and process ideas through the same ways that they do. I will be doing this through the computational theory of the mind test by Alan Turing, and the counter thought-experiment of Turing’s test by John Searle I will be able to show you this fact.
When speaking about whether a computer (artificial intelligence) can think, I will be referring to the word think as having a brain that can compute
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They rely on their syntax (the initial agreed upon ‘grammar’) and not their semantics (the constructed ‘grammar’ agreed upon by a culture). A good example of this is apple (the fruit), and apple (the electronic company) both having the same syntax but can be used two very different ways. He states if a computer thinks in algorithms such as this and the computational theory of the mind is such, there is no reason a computer cannot have the same type of thinking as we do. His test called the “Imitation game” involved having a person, a machine and, a human interrogator in three separate rooms. The interrogator must ask questions all written down, to determine which person is in fact a person. If the computer convinces the interrogator he is a person, Turing insists this means computers are just as intelligent as humans? Although, no computer has passed the test yet, Turing believes the fact that they can come close and one day will be able to means they have the capabilities to think as we do.
John Searle’s counter theory to Turing’s test is an also very well recognized thought-experiment called the Chinese Room. He is in a room with a manual that explains to him how to respond to words or sentences passed to him on a piece of paper underneath a door. He speaks no Chinese but using the manual can think of responsive sentences to pass to a person on the other side, which cause him to seem as though he speaks perfect Chinese. He says he does this using the manual “for manipulating symbols and numerals (just as a computer does).”
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:
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.
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.
But what is intelligence? “Intelligence is often defined as the ability to adapt to the environment” (Sternberg). Computers can indeed adapt to their environment as demonstrated with various evolution simulators. The computer has been able to gather its surroundings, and come to appropriate decisions to best survive. How can a computer, this box with wires and electricity, even begin to come up with decisions on its own? Well, just like any other human, it has to learn.
...es, we evolve and change from that. A computer is unable to do that. When we succeed or do something right, we have a sense of pride and happiness. A computer like Watson is unaware of such emotions and takes no joy in being correct. We can be clever and cunning. A computer cannot.
I'll first talk about how Searle was lead to question the claim of computers being things that could actually think and were considered to have a strong sense intelligence based on the assumptions made by Alan Turing. He developed a test called the "Turing test" or, in other words, the "Imitation Game". The "Turing test" was a test that used a person (interrogator) who asked two subjects (a human and a computer) a series of questions that aided the integrator in determining which of the subjects was actually a human. (A.M. Turing, 1950, pg.) The assumptions based on the test included: If something has the ability to have thought then it is considered a thinker. The other assumption in question is that not only humans have the capability of having a mind, but other things including objects could also have a mind which makes them a thinking thing. These assumptions made Searle question on how the assumptions could be accurate, so in order to try to find a way to argue that the assumptions are not valid, so he created his experiment called the "Chinese Room Experiment". With this experiment, Searle was able to provide arguments that go against the claim proposed from the "Turing test" which I will discuss
Computers are machines that take syntactical information only and then function based on a program made from syntactical information. They cannot change the function of that program unless formally stated to through more information. That is inherently different from a human mind, in that a computer never takes semantic information into account when it comes to its programming. Searle’s formal argument thus amounts to that brains cause minds. Semantics cannot be derived from syntax alone. Computers are defined by a formal structure, in other words, a syntactical structure. Finally, minds have semantic content. The argument then concludes that the way the mind functions in the brain cannot be likened to running a program in a computer, and programs themselves are insufficient to give a system thought. (Searle, p.682) In conclusion, a computer cannot think and the view of strong AI is false. Further evidence for this argument is provided in Searle’s Chinese Room thought-experiment. The Chinese Room states that I, who does not know Chinese, am locked in a room that has several baskets filled with Chinese symbols. Also in that room is a rulebook that specifies the various manipulations of the symbols purely based on their syntax, not their semantics. For example, a rule might say move the squiggly
If a machine passes the test, then it is clear that for many ordinary people it would be a sufficient reason to say that that is a thinking machine. And, in fact, since it is able to conversate with a human and to actually fool him and convince him that the machine is human, this would seem t...
Alan Mathison Turing was born in Paddington, London, on June 23, 1912. He was a precocious child and began his interests in science and mathematics at a young age, but was never concerned about other right-brain classes such as English. This continued until an important friend of his passed away and set Turing on a path to achieve what his friend could no longer accomplish. When his friend Christopher Morcom died, Turing was launched into thoughts in physics about the physical mind being embodied in matter and whether quantum-mechanical theory affects the traditional problem of mind and matter. Many say today that this was the beginnings of Turing’s Turning Machine and the test still used today for artificial intelligence, the Turing Test.
is false. To accomplish this, Searle uses the example of “the Chinese Room” to challenge strong AI, and to object to Turing’s test. Searle begins by stating to imagine himself in a room with a box of Chinese characters which he could not understand, but in the room he had a book of instructions in English which he could understand. Searle then states that if there was a group Chinese speakers’ outside of the room passing him messages in Chinese, he would not understand, but could reply with the symbols in with the use of the instructions to form an appropriate response. Furthermore, Searle states that the Chinese speakers would think that the speakers were speaking to a Chinese speaker; however, realistically they were talking to a confused John Searle. Therefore, as Searle states, if a computer were to be placed in Searle’s position, the rule would become the “computer program”, and the basket of symbols the “data base”, it would prove that the machine would not understand Chinese, but only simulate that knowledge, which is not truly
For years philosophers have enquired into the nature of the mind, and specifically the mysteries of intelligence and consciousness. (O’Brien 2017) One of these mysteries is how a material object, the brain, can produce thoughts and rational reasoning. The Computational Theory of Mind (CTM) was devised in response to this problem, and suggests that the brain is quite literally a computer, and that thinking is essentially computation. (BOOK) This idea was first theorised by philosopher Hilary Putnam, but was later developed by Jerry Fodor, and continues to be further investigated today as cognitive science, modern computers, and artificial intelligence continue to advance. [REF] Computer processing machines ‘think’ by recognising information
Turing tested if a computer was able to communicate with a human being and to see if it was indistinguishable from a human being. For example, if a machine was hidden behind a wall or could not be seen and developed a conversation with a human being in which the human did not recognize that he/she was talking to a machine, it would pass the Turning Test. As Descartes looked at parrots that can speak or even monkeys that are taught sign language would not be able to pass the turning test. The parrot’s or gorilla’s vocabulary and grammar skills would not be proficient to pass the Turning
Well as I said we first must define ‘to think’. What does that mean? Webster’s New Compact Dictionary defines ‘think’ as "1. Have a mind. 2. Believe. 3. Employ the mind.". It defines mind as ‘to think’. So does this mean that if you can think does this mean you have a mind? My opinion is that, according to this definition, computers can think. A computer can give you an answer to the question ‘What is 4x13?’, so it can think. What’s that? You say it’s just programmed to do that, if no one programmed it wouldn’t be able to do that. Well how did you know how to answer the question? Your teacher or parent’s or someone taught it to you. So you were programmed, same as the computer was.
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.
In the past few decades we have seen how computers are becoming more and more advance, challenging the abilities of the human brain. We have seen computers doing complex assignments like launching of a rocket or analysis from outer space. But the human brain is responsible for, thought, feelings, creativity, and other qualities that make us humans. So the brain has to be more complex and more complete than any computer. Besides if the brain created the computer, the computer cannot be better than the brain. There are many differences between the human brain and the computer, for example, the capacity to learn new things. Even the most advance computer can never learn like a human does. While we might be able to install new information onto a computer it can never learn new material by itself. Also computers are limited to what they “learn”, depending on the memory left or space in the hard disk not like the human brain which is constantly learning everyday. Computers can neither make judgments on what they are “learning” or disagree with the new material. They must accept into their memory what it’s being programmed onto them. Besides everything that is found in a computer is based on what the human brain has acquired though experience.