Can Computers understand?
1) Thinking is the hallmark of understanding.
2) Only special machines can think.
3) If something can think it can understand.
4) Only special machines that can think can understand.
5) "Mental" states and their resulting actions are products of the center of activity (brain).
6) To understand, thoughts must be produced by the brain.
7) A computer's mental states and events are controlled by a program.
8) The program is not a product of the computer.
9) A computer does not produce "thoughts" in its brain.
10) A computer cannot understand.
John Searle addresses the point of the ability of Artificial
Intelligence (AI) to understand, in Mind Brains, and Programs. His main argument is that because AI's are computers and computers have no thoughts of their own, they cannot understand. Any actions being performed to simulate behavior are confined by the programs available to the computer. He presents the example of a man linking Chinese characters and appearing to know the language, but in reality the man is just following the instructions given to him
( the program). This example serves well to explain how although a computer can look like it understands a story, it can do no more than "go through the motions." Of course such a definitive standpoint on an issue as controversial as the capacity of an AI to understand will draw many critics. The criticism of his theory that I find to be the most credible is The Other Mind Reply offered by Yale University. This line of thinking asks: if behavior is what we can determine the presence of cognition through, and an AI passes a behavioral test, why don't we attribute cognition to it?
I myself do not believe in the philosophy of AI understanding, because to support either side on this issue one must have a belief for or against the
Much of his argument rests on the nearly indisputable belief that if we, as a
I will show that Kelly's response to the question of epistemic significance of peer disagreement is not compelling. In my explanation of Kelly's argument, I will show that it is contradictory of him to assert the first persons perspective and the right reasons view. I will then examine the third person perspective, and show that this is more compatible with the right reasons view. Nevertheless I will propose an objection in the form of a question. Specifically, why should the difference between first person and third person change my thinking skeptically? Would this view only be attractive from the third person view? The third person perspective, the right reasons view as Kelly explains it, plus what I will call external Validation of a belief makes a more compelling argument.
possibly be mistaken. He goes on to provide solid argument for his ideas. In Meditations
Do not believe in anyone theories without questioning it. It is important to prove that someone has the knowledge of what they speak.
references to support his claims. It is a very well configured piece, written in such a way
... of nature. In fact, this belief, which does beg the question, is what predominates his thinking.
"AAAS Board Resolution on Intelligent Design Theory." AAAS. N.p., 2002. Web. 7 Nov 2010. .
In about ½ of a page (single-spaced), please state whether you agree, disagree, or have a mixed opinion regarding the following statement and argue, via evidence and claims from what you have learned in class, why you have picked your stated position. Be sure to comprehensively explain and support your reasoning.
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.
Davis, Tom. The Theories of the Mind Lectures. Ed. G. Baston. Birmingham University. 9 Nov. 2000
Skepticism is the view that there is no way to prove that objects exist outside of us. Skeptics hold that we can not distinguish between dreams and reality, and therefore what we take to be true can very well be creations of our minds while we are nothing more than a simple piece of matter, such as a brain sitting in a vat that is connected to a machine that simulates a perfect representation of reality for the “brain” to live in.1 In the excerpt “Proof of an External World” from his essay of the same name, G.E. Moore responds to the skeptic’s argument by attempting to prove the existence of external objects. There are four parts to this paper. Firstly, I will explain Moore’s overall argumentative strategy and how he considers his proof to be rigorous and legitimate. Then, I will present Moore’s proof of the existence of an external world. Thirdly, I will discuss the responses that skeptics may have to Moore’s argument and how Moore defends his proof against the these responses. Finally, I will give my opinion on how efficiently Moore defends his claims against the skeptics’ responses.
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.
Both sides of the issue are supported by studies, facts and opinions. Therefore, your stance on the issue is yours to decide.
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.