Can or will computers ever think? Well this has been a subject of much debate between even the greatest minds, and yet there is still no answer. First of all I have would like you to answer a question. What is 4x13? Did you have to think to answer that? Yes? Well does that mean that a computer can think because it can answer that question. Well that is what we are going to set to answer and I think yes, depending on your definition of thinking.
First off let’s get something straight. When I refer to computers in this essay I am not referring only to the microprocessor sitting on your desk but to microprocessors that control robots of various structure.
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.
So you think that programing is different than learning. You might think the same as my grandma that programing is something where things are just drilled into you like people who are members of cults. Well when your teacher stood over you desk in elementary and do drilled you on the multiplication tables was that not programming? Would you know that 1x5 does not equal 10 if everyone you ever met said that it did. Another argument my grandma used was my little cousin and how when he runs into a wall he learns that it hurts so he doesn’t do it again. (Well actually he does it because he has a hard head). Yet a professor in Calgary builds robots that do not even contain a microprocessor yet it can learn. He builds them out of spare part from broken electronics such as walkman’s.
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.
What role will computers play in the future? What happens when artificial intelligence gets to the point of actually allowing machines to give birth to original thoughts, or suppose artificial intelligence became identical or superior to human intelligence? While attempting to answer these thought-provoking questions deeper questions arise that are more pertinent in our lives such as what defines being human, or as Morpheous says, “What is…real?” The Matrix as well as the novel Do Androids Dream of Electric Sheep, by Phillip K. Dick, attempt to answer these questions through different matrices. These matrices are implemented into stories to provoke thought and ask the question, what if?
The purpose of this paper is to present John Searle’s Chinese room argument in which it challenges the notions of the computational paradigm, specifically the ability of intentionality. Then I will outline two of the commentaries following, the first by Bruce Bridgeman, which is in opposition to Searle and uses the super robot to exemplify his point. Then I will discuss John Eccles’ response, which entails a general agreement with Searle with a few objections to definitions and comparisons. My own argument will take a minimalist computational approach delineating understanding and its importance to the concepts of the computational paradigm.
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
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
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 ...
2. Asimov, Isaac, and Karen A. Frankel. ROBOTS: Machines in Man's Image. New York: Harmony Books, 1985. p 2.
New advancements make it possible to not only program computers to do what people tell them to, but to think for themselves.
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 computer has been one of man’s most influential inventions, paving the way for greater achievements with time. Today, computers have become an essential component in fulfilling everyday tasks in both our professional and personal lives. Computers are used to store vast amounts of information, and even replace humans in factories throughout the world. We must now ask ourselves, is this reliance on computers aiding the human mind in achieving its full potential or rather replacing it and hindering our progress? Society has now become dependant on computers. How does this machine affect our youth and learning process? We have invented a machine with a greater, and faster learning capacity as our own. A new generation has risen that have used computers for most of their lives so it is not surprising that they have become highly dependent on the computer. As of now, humans only use less than twenty percent of their brains, and with computers doing most of our work, this number is slowly decreasing.
Nowadays, technology is a dominant feature in the lives of people around the world. Most of daily life activities involve the use of technology which is expanding every day through scientific innovations. However, such innovations do not always occur in every part of the world, but mostly in technologically developed countries, such as South Korea, the USA and Japan. Presently, the development of robotics science has become a subject of considerable attention in those countries. According to Weng, Chen and Sun (2009, 267), “Technocrats from many developed countries, especially Japan and South Korea, are preparing for the human–robot co-existence society that they believe will emerge by 2030.” The word “robot” was introduced in the beginning of 1920th by the Czech playwright Karel Capek from the Czech word “robota”, meaning “forced labor” (Robertson 2007, 373). According to Robertson (2007, 373), robot, in practical usage, can be defined as an autonomous or semiautonomous device that is used to perform its tasks either controlled by human, fractionally controlled and with human guidance or regardless of external actions that are performed by people. Regrettably, the majority of robots in the past centuries could not operate without human control and intervention. However, the progress in robotics over the past few decades enabled humanity to achieve soaring results in creation of autonomous humanoid robots.
The idea behind robots and their uses has been a compilation of thoughts stewing in the minds of engineers and physicists from as early as the 1700s. The first representations of these creations was in the textile production industry; i.e. Hargreaves’ spinning jenny around 1770 and Cropmton’s mule spinner around 1779. Once these ideas were put into action, the robot development seed was planted and its roots spread into the minds of many potential engineers. This ventured into the development of Numerical Control (NC) and Telecherics technologies in the robotic field. John Parson’s Numerical Control is a system that integrated numbers as a tool to control the machine/robot’s actions, and this led to the creation of a prototype at the Massachusetts Institute of Technology in 1952.
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.
There has always been controversy as to whether computers hurt the way people think. Computers have hurt society more than it has helped. Although computers have benefits such as helping you for school work in making quicker decisions for you, and it makes it easier to do essays by using word; it has also hurt society because it makes us become lazier, makes online dating dangerous, and makes people addicted to the Internet.