The question of machine thinking involves the notation of a machine being capable of thinking the way humans think. It would be common for people to quickly say that machines cannot think like them because computers do not have a biological brain or because machines are tools and they cannot work without the help of people. For example, typewriters are only capable of the action of putting words on paper when the person typing presses on the keys, otherwise, the typewriter is just a piece of metal. This example shows that machines are dependent on the information that is given or inputted into the machines and would suggest that all of the thinking is done by the people who put in the information.
Others who oppose the previous idea would say
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Just like the brain being able to send signals throughout the body, machines send out signals to their parts so that the machines can operate and fulfill their functions. This article also mentions that machines can operate faster than humans brains can, but are limited to the amount of memory they can hold in order to manage more complex computing. This raises the question of whether or not machines are capable of thinking about more complex problems if they could hold more information than humans. This relationship between the human brain and machines shows that machines are capable of human thought, or supports the idea that the human brain think like computing machinery. According to Professor Aiken, who is the head of Harvard’s computational laboratory, "When a machine is acting badly, we consider it a responsible person and blame it for its stupidity. When it 's doing fine, we say it is a tool that we clever humans built." This quote from Professor Aiken explains how people think about machines even though the two claims are contradictory to each other. It also shows a difference between human thinking and machine computing; machine computing is completely objective in contrast to human thinking (The Thinking Machine, …show more content…
Machine can used stored information, either computations and/or inputs, to perform actions that avoid errors or undesired results. For example, in an article about a machine navigating itself toward the exit of a maze, the machine was able to reach the end of the maze through the process of elimination or trial and error for the possible paths. Furthermore, it was able to reach the end in another attempt without any mistakes by using the information gathered during the first attempt. The significance of this article is that the shows how machines use previous information to become more efficient in producing results (Ross, 1938). This idea can also be applied to the logic piano, the machine had to go through a test run in order to see how well it could produce a result and then its configuration, or its previous information, is modified to produce results more efficiently and without mistakes.
The consequences of my answer to whether machines can think like humans could concern how morality would affect machines or whether free will is present in machines. With the concept of morality, machines would make objective judgements about controversial ideas that could differ from how humans would judge the ideas even though machines can similarly to humans. For example, the logic piano could logically conclude from a set of given premises that good people can kill babies is morally right because it is logically
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:
deep need to probe the mysterious space between human thoughts and what is a machine can
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.
Since antiquity the human mind has been intrigued by artificial intelligence hence, such rapid growth of computer science has raised many issues concerning the isolation of the human mind.
Technology Is What You Make It The articles “How Computers Change the Way We Think” by Sherry Turkle and “Electronic Intimacy” by Christine Rosen argue that technology is quite damaging to society as a whole and that even though it can at times be helpful it is more damaging. I have to agree and disagree with this because it really just depends on how it is used and it can damage or help the user. The progressing changes in technology, like social media, can both push us, as a society, further and closer to and from each other and personal connections because it has become a tool that can be manipulated to help or hurt our relationships and us as human beings who are capable of more with and without technology. Technology makes things more efficient and instantaneous.
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.
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...
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.
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
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.
Most of the day the human mind is taking in information, analyzing it, storing it accordingly, and recalling past knowledge to solve problems logically. This is similar to the life of any computer. Humans gain information through the senses. Computers gain similar information through a video camera, a microphone, a touch pad or screen, and it is even possible for computers to analyze scent and chemicals. Humans also gain information through books, other people, and even computers, all of which computers can access through software, interfacing, and modems. For the past year speech recognition software products have become mainstream(Lyons,176). All of the ways that humans gain information are mimicked by computers. Humans then proceed to analyze and store the information accordingly. This is a computer's main function in today's society. Humans then take all of this information and solve problems logically. This is where things get complex. There are expert systems that can solve complex problems that humans train their whole lives for. In 1997, IBM's Deep Blue defeated the world champion in a game of chess(Karlgaard, p43). Expert systems design buildings, configure airplanes, and diagnose breathing problems. NASA's Deep Space One probe left with software that lets the probe diagnose problems and fix itself(Lyons).
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...
Our minds have created many remarkable things, however the best invention we ever created is the computer. The computer has helped us in many ways by saving time, giving accurate and precise results, also in many other things. but that does not mean that we should rely on the computer to do everything we can work with the computer to help us improve and at the same time improve the computer too. A lot of people believe that robots will behave like humans someday and will be walking on the earth just like us. There should be a limit for everything so that our world would remain peaceful and stable. At the end, we control the computers and they should not control us.
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
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.