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Essay writing on artificial intelligence
Essay writing on artificial intelligence
Essay writing on artificial intelligence
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Strong AI: What is it and how does it question the definition of the mind?
Strong AI, or strong artificial intelligence, is a class in artificial intelligence development that strives to develop computers that can operate on the human level. One of the ideas of strong AI is that digital computers can one day intellectualize on the same level as a human mind. The concept of strong AI provides insight on the relationship between the physical and mental states. With strong AI, the mind is analogous to programs and the brain is analogous to computer hardware. Strong AI provides a thought provoking philosophy on what constitutes a mind.
The Problems with Strong AI According to Searle
American philosopher, John Searle, believes that goals of strong
Searle’s strongest point is how computers lack semantics. One of the points he makes in his semantics versus syntax argument is that computers determine meaning from the physical appearance of symbols alone whereas a human derives meaning from the contents of its mind. This is a solid point because computer programs fail to run when they are not syntactically correct. They essentially fail to understand when the syntax of a program is incorrect. Humans can overcome syntactical errors and draw meaning based on the content in their minds.
My main critique on Searle’s argument is that he does not go into depth on how humans think. Searle’s main argument is that computers cannot reach human intellect because they can only understand what they are programmed to do, whereas humans can provide understanding based on the content of their minds. Theoretically, a computer can provide understanding based on the content of their “minds”, which would just be additional code that represents this content. I believe Searle does argue against this by stating that it is just additional syntax information, however he doesn’t provide any evidence that humans don’t do the
Computationalism: the view that computation, an abstract notion of materialism lacking semantics and real-world interaction, offers an explanatory basis for human comprehension. The main purpose of this paper is to discuss and compare different views regarding computationalism, and the arguments associated with these views. The two main arguments I feel are the strongest are proposed by Andy Clark, in “Mindware: Meat Machines”, and John Searle in “Minds, Brains, and Programs.”
It is easy for Searle to respond to this claim. There is no evidence that he needs to refute. He even says that he is "embarrassed" to respond to the idea that a whole system aside from the human brain was capable of understanding. He asks the key question which will never be answered by Lycan, "Where is the understanding in this system?" Although Lycan tries to refute Searle's views, his arguments are not backed with proof. Lycan responded by explaining that Searle is looking only at the "fine details" of the system and not at the system as a whole. While it is a possibility that Searle is not looking at the system as a whole, it still does not explain in any way or show any proof whatsoever as to where the thinking in the system is.
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. This is a view that is very attuned with (accepting) determinism. Determinism states that necessary causes must be for the occurrence to be. This deterministic cause and effect relationship is apparent in the physical world. Hard believing determinists see determinism as being exclusive of free will. Searle, being a materialist, views humans as just another material substance. He accepts determinism and rejects (libertarian) free will.
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...
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.
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
At the end of chapter two, Searle summarizes his criticism of functionalism in the following way. The mental processes of a mind are caused entirely by processes occurring inside the brain. There is no external cause that determines what a mental process will be. Also, there is a distinction between the identification of symbols and the understanding of what the symbols mean. Computer programs are defined by symbol identification rather than understanding. On the other hand, minds define mental processes by the understanding of what a symbol means. The conclusion leading from this is that computer programs by themselves are not minds and do not have minds. In addition, a mind cannot be the result of running a computer program. Therefore, minds and computer programs are not entities with the same mental state. They are quite different and although they both are capable of input and output interactions, only the mind is capable of truly thinking and understanding. This quality is what distinguishes the mental state of a mind from the systemic state of a digital computer.
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.
Carr starts off his argument by referencing a “2001 a space odyssey” released in 1968 about a computer named HAL that tries to kill the astronauts that are on the spaceship that HAL controls. Carr uses an excerpt from this movie to incite fear into his readers and fear clouds judgement and causes irrational ideas to be formed. This movie is an over exaggerated sci-fi thriller and not a realistic representation of what computers are becoming. At the conclusion of his argument Carr does not forget to leave his readers the way he greeted them, Carr quotes 2001: a space odyssey “i can feel it. I’m afraid” (Carr 328). Although emotions are a strong way to engage with a reader, strong emotions also distract readers from the actual argument and encourage the reader to make a decision based on their feeling rather than their actual brain. The fact that Carr uses emotion to convince his readers is quite ironic, considering he is arguing that new technology is limiting our ability to use our brains. In contrast Thompson’s article uses logic and reason to make his argument. At the same time Thompson’s article still engages readers and is just as interesting to read as Carr’s essay. Thompson’s article starts off pondering whether computers or humans are better at chess. To answer this
In this paper, I have attempted to concisely yet methodically explain the Turing Test and its respective objection and rebuttals. Both Turing and Searle’s comparisons between humans and computers in a methodological manner alike illustrate their opposing views on the topic. However, following Searle’s reasoning against Turing’s experiment, it is clear that he lacks adequacy for his reasoning. This is most commonly found in Searle’s tendency to base his theories off assumptions. In doing so, Turing’s ideal responses effortlessly undermine any substance Searle might have had, thus proving his to be the stronger theory.
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
John Searle developed two areas of thought concerning the independent cognition of computers. These ideas included the definition of a weak AI and a strong AI. In essence, these two types of AI have their fundamental differences. The weak AI was defined as a system, which simply were systems that simulations of the human mind and AI systems that were characterized as an AI system that is completely capable of cognitive processes such as consciousness and intentionality, as well as understanding. He utilizes the argument of the Chinese room to show that the strong AI does not exist.
...lligent, intentional activity taking place inside the room and the digital computer. The proponents of Searle’s argument, however, would counter that if there is an entity which does computation, such as human being or computer, it cannot understand the meanings of the symbols it uses. They maintain that digital computers do not understand the input given in or the output given out. But it cannot be claimed that the digital computers as whole cannot understand. Someone who only inputs data, being only a part of the system, cannot know about the system as whole. If there is a person inside the Chinese room manipulating the symbols, the person is already intentional and has a mental state, thus, due to the seamless integration of their systems of hardware and software that understand the inputs and outputs as whole systems, digital computers too have states of mind.
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...
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.