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:
Webster's Collegiate Dictionary defines intelligence as the capacity to apprehend facts and propositions, to reason about them, and the ability to understand them and their relations to each other. A. M. Turing had this definition in mind when he made his predictions and designed his test, commonly known as the Turing test. His test is, in principle, simple. A group of judges converse with different entities, some computers and some human, without knowledge of which is which. The job of the judges is to discern which entity is a computer. Judges may ask them any question they like, "Are you a computer?" excepted, and the participants may answer with anything they like, and in turn, ask questions of the judges. The concept of the test is not difficult, but creating an entity capable of passing the test with current technology is virtually impossible.
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
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.
...ing Test and scientists of AI have different opinions about it. However there are some facts of which we can be sure of. The Turing Test was invented by a great scientist, it has had a long and rich history of 55 years and has played an important role in the science of Artificial Intelligence.
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.
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.
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.
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 ...
Alan Turing left an indelible mark on the world with technological inventions, extraordinary talent, and productive habits. His dedication to hard work and perseverance against the discouragement of bullying provide fantastic examples for anyone to emulate. Also, the inventions of the Turing Machine and the Bombe were the primary reasons why computers existed during the last sixty years, and were important factors in the demise of Nazi Germany. Finally, for one to truly understand why Turing was important in world history, he should envision life without modern technology and
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 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.
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...