One of the most difficult challenges in developing Artificial Intelligence (AI) is to create a machine that “thinks” as intelligently as humans do. However, devising a definition for the word “think” itself is quite a task. This is because it is yet unclear as to what comprises a human being’s thoughts, and what is the driving force behind his/her intelligence. Is it a manifestation of the immortal soul or is it just a complex network of nerves comprising the nervous system? To create an intelligent machine or a computer, it is necessary to grant it with thinking capabilities that are at par with humans. If such an intelligent machine is ever created, how can we test whether it can think on its own? How can it be certified as Artificial Intelligence?
Alan Mathison Turing, a computer analyst, mathematician and cryptoanalyst, provided a simple solution to this problem. In a paper published in the Journal Mind, in 1950, Turing suggests that rather than creating complications by using the word “think”, defining it, or asking whether machines can “think”, it is easier to develop a task that requires thinking, and testing whether a machine can succeed in that task. In Turing’s own words, “Instead of attempting such a definition I shall replace the question by another, which is closely related to it and is expressed in relatively unambiguous words” (Turing, 1950, p. 433). These “unambiguous words” were in fact the “imitation game”, now known as “Turing’s Test”. This test suggested by Turing has been used ever since to test artificial intelligence. In spite of the technological advancements since the Turing test was first published, no machine has yet passed the test. Turing’s paper has been a frontrunner in all publications and researc...
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Oppy, G. and Dowe, D., 2011. The Turing Test. The Stanford Encyclopedia of Philosophy (Spring 2011 Edition). Available at: http://plato.stanford.edu/archives/spr2011/entries/turing-test/
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In the first three chapters of Kinds of Minds, Dennett introduces a variety of perspectives on what the mind is. From Cartesianism to Functionalism, Dennett outlines the evolution of thought about thought and the mind and explains his own perspective along the way. Cartesianism, as proposed by Descartes, proposes that the mind is who we are and characterizes the mind as a non physical substance that was completely separate from, and in control of, the physical body. In the strictest sense, Functionalism can be defined from Alan Turing’s perspective that a mind can be defined by what it can do. So from the Turing test, if an AI can fool a human into thinking it is also human, it must be at least as intelligent as the human. Using a plethora of anecdotes and examples, Dennett makes his position clear as he denounces Cartesianism and advocates for a functionalist based perspective in his own evolving definition of the mind.
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.
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.
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.
Smith, E. E. and Kosslyn, S. M. (2009). Cognitive psychology: Mind and brain. New Jersey: Pearson Education
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Lycan, W. G. (1980) Reply to: "Minds, brains, and programs", The B.B.S. 3, p. 431.
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.
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
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.
Artificial intelligence is a concept that has been around for many years. The ancient Greeks had tales of robots, and the Chinese and Egyptian engineers made automations. However, the idea of actually trying to create a machine to perform useful reasoning could have begun with Ramon Llull in 1300 CE. After this came Gottfried Leibniz with his Calculus ratiocinator who extended the idea of the calculating machine. It was made to execute operations on ideas rather than numbers. The study of mathematical logic brought the world to Alan Turing’s theory of computation. In that, Alan stated that a machine, by changing between symbols such as “0” and “1” would be able to imitate any possible act of mathematical
Artificial Intelligence “is the ability of a human-made machine to emulate or simulate human methods for the deductive and inductive acquisition and application of knowledge and reason” (Bock, 182). The early years of artificial intelligence were seen through robots as they exemplified the advances and potential, while today AI has been integrated society through technology. The beginning of the thought of artificial intelligence happened concurrently with the rise of computers and the dotcom boom. For many, the utilization of computers in the world was the most advanced role they could ever see machines taking. However, life has drastically changed from the 1950s. This essay will explore the history of artificial intelligence, discuss the