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 Turing test was a test that allows humans to evaluate the question “can machines think?” Turing evaluates that one should not ask if machines can think, but conduct an experiment which can prove that it can think. In order to answer this question, Turing created …show more content…
Objection (6) states “the analytical engine has no pretensions to originate anything. It can do whatever we know how to order it to perform” (A.M. Turing, pg.13). Lady Lovelace’s objection suggests that a machine can only do what we order them to do and that anything they do shouldn’t surprise us. However, Turing replies to this argument by stating that a machine can definitely take us by surprise. The reason he says this is because we humans are not a very brilliant on what we create and we are never one hundred percent sure of the things we program (Graham, Dowe). We tend to make small errors of the machinery we create just as estimating variables and thinking it’s all correct. This also leads back to Objection (4) because the idea of surprise “requires as much of a creative mental act” (A.M. Turing, pg. …show more content…
The reason I believe that the Turing test is a great test is because it not only difficult, but it allows the interrogator to think, and that is what I believe Turing looks for his test, the state of logical thought. This would prove that the machine or anything can basically think and feel. For example, If I were to be the interrogator and asked “Are you a woman?” and they both answered me “I am” I would be mentally disturbed and would have to ask new questions to find my answer, but the main point here was the fact I was mentally disturbed and that leads to emotion, which leads that if I were to figure out who was who, I would pass the test and I would have evidence that I can undoubtedly
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:
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.
This paper purports to re-examine the Lucas-Penrose argument against Artificial Intelligence in the light of Complexity Theory. Arguments against strong AI based on some philosophical consequences derived from an interpretation of Gödel's proof have been around for many years since their initial formulation by Lucas (1961) and their recent revival by Penrose (1989,1994). For one thing, Penrose is right in sustaining that mental activity cannot be modeled as a Turing Machine. However, such a view does not have to follow from the uncomputable nature of some human cognitive capabilities such as mathematical intuition. In what follows I intend to show that even if mathematical intuition were mechanizable (as part of a conception of mental activity understood as the realization of an algorithm) the Turing Machine model of the human mind becomes self-refuting.
The Turing Test is a method determining if a machine is capable of thinking or generating like a human. That will prove to be a strong or weak artificial intelligence (AI). It's testing the indistinguishable behavior of a machine to a human. The test consists of an evaluator who asks questions to two partners, one's a human and the other is a computer. There is no contact with the judge and the two partners who engage in the conversation. The answers are presented by texting only to conceal the truth behind the screen. The objective is to convince the judge that the computer is behaving like a human since it's responding like one. If the evaluator is 70% sure the responder is a human, the machine passes the test. In other words, the judge's
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 ...
Can machines think? This question, addressed by Descartes and Turing, leads to discussion of how thought is constructed and what is the mind made of. At the heart of the debate, there is a schism between Cartesian dualism and functionalism. Language is a method considered by both sides as evidence of thought and provides the test for intelligence. This essay will look at Descartes’ objections and Turing’s arguments for whether machine can ever think. This essay will argue that Turing’s, and the functionalist, view is correct. It questions whether Turing’s test provides sufficient evidence of machine intelligence, and uses Searle’s Chinese room to explain why intentionality matters.
The conditions of the present scenario are as follows: a machine, Siri*, capable of passing the Turing test, is being insulted by a 10 year old boy, whose mother is questioning the appropriateness of punishing him for his behavior. We cannot answer the mother's question without speculating as to what A.M. Turing and John Searle, two 20th century philosophers whose views on artificial intelligence are starkly contrasting, would say about this predicament. Furthermore, we must provide fair and balanced consideration for both theorists’ viewpoints because, ultimately, neither side can be “correct” in this scenario. But before we compare hypothetical opinions, we must establish operant definitions for all parties involved. The characters in this scenario are the mother, referred to as Amy; the 10 year old boy, referred to as the Son; Turing and Searle; and Siri*, a machine that will be referred to as an “it,” to avoid an unintentional bias in favor of or against personhood. Now, to formulate plausible opinions that could emerge from Turing and Searle, we simply need to remember what tenants found their respective schools of thought and apply them logically to the given conditions of this scenario.
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.
In 1931, Turing won an entrance to King’s college in Cambridge on scholarship. It was here that Turing was able to express his ideas freely. In 1932 Turing read Con Neumann’s work on the logical foundations of Quantum Mechanics. It was also here at Cambridge that Turing’s homosexuality became a big part of his identity. Turing went on to receive his degree in 1934 followed by a M.A. degree from King’s college in 1935, and a Smith prize in 1936 for his work on probability theory.
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.
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.
Although the majority of people cannot imagine life without computers, they owe their gratitude toward an algorithm machine developed seventy to eighty years ago. Although the enormous size and primitive form of the object might appear completely unrelated to modern technology, its importance cannot be over-stated. Not only did the Turing Machine help the Allies win World War II, but it also laid the foundation for all computers that are in use today. The machine also helped its creator, Alan Turing, to design more advanced devices that still cause discussion and controversy today. The Turing Machine serves as a testament to the ingenuity of its creator, the potential of technology, and the glory of innovation.
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...