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Artificial Intelligence Overview
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"The sad thing about artificial intelligence is that it lacks artifice and therefore intelligence." - Jean Baudrillard John Searle is an established author and professor. He has written books about language and understanding. He wrote Speech Acts (1969), The Mystery of Consciousness (1997), and Rationality in Action (2001). Searle is the Willis S. and Marion Slusser Professor of the Philosophy of Mind and Language at the University of California, Berkeley. (214) John Searle wrote an article that was first published in the Wall Street Journal on February 11, 2011. He examined the performance of IMB's super computer, Watson. He wanted to explore the idea of what Watson understood. (214) Watson is a computer that was created by IBM and named after the company's first CEO. In February 2011 Watson was a contestant on the trivia game show Jeopardy. His two opponents were former show champions. Watson beat his human counterparts. In Searle's article, "Watson Doesn't Know It Won on 'Jeopardy!'", his thesis begins by talking about the vast opinions of people who felt as though Watson's …show more content…
He begins by asking the reader to imagine that John Searle, himself, was locked in a room full of Chinese symbols. He refers to those symbols in this analogy as "the database". He would be given a manual in English called "the program", and he was referred to as "the computer". Then people on the other side of this room would pass Searle symbols in Chinese, and then he in turn would decipher those symbols using his English manual and the return the correct answers. To the people on the other side of that wall, it would appear that Searle knew what his answers meant since they were correct. He uses this comparison to make the point that Watson knew as much of his answers on Jeopardy as Searle did in that locked room. It was all just programmed information that neither one of them
Smarter than You Think starts out with a cautionary tale of how in 1997 world chess champion Garry Kasparov was beaten by Deep Blue, an I.B.M. supercomputer. This was a considered a milestone in artificial intelligence. If a computer could easily defeat a chess champion, what would happen to the game and its players? A year after Kasparov was defeated by the program he decided to see what would happen when a computer and person were paired up. He called this collaboration the centaur; A hybrid consisting of the algorithms and history logs of chess as well as the brain to “analyze their opponents’ strengths and weaknesses, as well as their moods.” ...
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:
Both Searle and Lycan agree that individual objects within a system cannot be considered thinking. In other words, both Searle and Lycan believe that in the example of the Chinese room, the man does not understand the language by himself. It is very obvious to Lycan that an object as part of a system cannot understand or think on its own. He argues that it must be part of a greater system which as a whole system can understand the Chinese. It is this whole system that understands. Lycan criticizes Searle for looking to much at the individual parts of a system and not at the system as a whole. Lycan even pokes fun at Searle when he says, "Neither my stomach nor Searle's liver nor a thermostat nor a light switch has beliefs and desires." The man who responds in Chinese using the "data banks" of Chinese symbols is, according to Lycan, understanding as part of a system. Although as an individual, the man is unable to "understand" Chinese, he can, as a whole system understand it.
Searle's argument delineates what he believes to be the invalidity of the computational paradigm's and artificial intelligence's (AI) view of the human mind. He first distinguishes between strong and weak AI. Searle finds weak AI as a perfectly acceptable investigation in that it uses the computer as a strong tool for studying the mind. This in effect does not observe or formulate any contentions as to the operation of the mind, but is used as another psychological, investigative mechanism. In contrast, strong AI states that the computer can be created so that it actually is the mind. We must first describe what exactly this entails. In order to be the mind, the computer must be able to not only understand, but to have cognitive states. Also, the programs by which the computer operates are the focus of the computational paradigm, and these are the explanations of the mental states. Searle's argument is against the claims of Shank and other computationalists who have created SHRDLU and ELIZA, that their computer programs can (1) be ascribe...
Searle’s argument is one against humans having free will. The conclusion comes from his view on determinism and his view on substances. His view on substances is a materialist one. To him, the entire world is composed of material substances. All occurrences can be explained by these materials.
I will begin by providing a brief overview of the thought experiment and how Searle derives his argument. Imagine there is someone in a room, say Searle himself, and he has a rulebook that explains what to write when he sees certain Chinese symbols. On the other side of the room is a Chinese speaker who writes Searle a note. After Searle receives the message, he must respond—he uses the rulebook to write a perfectly coherent response back to the actual Chinese speaker. From an objective perspective, you would not say that Searle is actually able to write in Chinese fluently—he does not understand Chinese, he only knows how to compute symbols. Searle argues that this is exactly what happens if a computer where to respond to the note in Chinese. He claims that computers are only able to compute information without actually being able to understand the information they are computing. This fails the first premise of strong AI. It also fails the second premise of strong AI because even if a computer were capable of understanding the communication it is having in Chinese, it would not be able to explain how this understanding occurs.
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.
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 ...
In “Can Computers Think?”, Searle argues that computers are unable to think like humans can. He argues this
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.
Soldiers sown from dragon teeth, golden robots built by Hephaestus, and three-legged tables that could move under their own power - the Greeks were the first to cross the divide between machine and human. Although the history of Artificial Intelligence (AI) began with these myths and speculations, it is becoming a part of everyday life. How did it evolve so quickly, and what are its implications for the future?
Specifically, in how the theory likens conscious intelligence to a mimicry of consciousness. In Alan Turing’s study of computing and consciousness, he developed the Turing Test, which essentially led to the notion that if a computing machine or artificial intelligence could perfectly mimic human communication, it was deemed ‘conscious’. REF. However, many do not agree and instead argue that while computers may be able to portray consciousness and semantics, it is not commensurable to actual thought and consciousness. Simulation is not the same as conscious thinking, and having a conscious understanding of the sematic properties of the symbols it is manipulating. This flaw was portrayed in John Searle’s thought experiment, ‘The Chinese Room’. Searle places a person who cannot speak Chinese in a room with various Chinese characters and a book of instructions, while a person outside of the room that speaks Chinese communicates through written Chinese message passed into the room. The non-Chinese speaker responds by manipulating the uninterpreted Chinese characters, or symbols, in conjunction with the syntactical instruction book, giving the illusion that they can speak Chinese. This process simulated the operation of a computer program, yet the non-Chinese speaker clearly had no understanding of the messages, or of Chinese, and was still able to produce
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.
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...
...on, adaptation, and planning for the future. The computer is unable to win because it cannot think like a human, and that is why we humans are smarter than computers to this day (The Daily Galaxy 1-3).