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Chinese Room Scenario by John R. Searle
Through the use of his famous Chinese room scenario, John R. Searle tries to prove there is no way artificial intelligence can exist. This means that machines do not posses minds.
The debate between those who are in favor of strong and weak artificial intelligence (AI) is directly related to the philosophy of mind. The claim of weak AI is that it is possible to run a program on a machine, which will behave as if it were a thinking thing. Believers of strong AI say that it is possible to create a program running on a machine which not only behaves as if it were thinking, but does actually think. Strong AI followers argue that an installation of a computer program is considered a mind as real as the mind of any human.
Searle's claim is that any installation of a program is an operation. The lack of meaning, he states, means that the computer program does not have true understanding and is not truly thinking, it is simply computing and processing symbols. He presents this argument by using his famous Chinese room. Searle begins by ta...
... in 21th century, and it might already dominate humans’ life. Jastrow predicted computer will be part of human society in the future, and Levy’s real life examples matched Jastrow’s prediction. The computer intelligence that Jastrow mentioned was about imitated human brain and reasoning mechanism. However, according to Levy, computer intelligence nowadays is about developing AI’s own reasoning pattern and handling complicated task from data sets and algorithms, which is nothing like human. From Levy’s view on today’s version of AI technology, Jastrow’s prediction about AI evolution is not going to happen. As computer intelligence does not aim to recreate a human brain, the whole idea of computer substitutes human does not exist. Also, Levy said it is irrelevant to fear AI may control human, as people in today’s society cannot live without computer intelligence.
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.”
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.
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.
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.
Regarding artificial intelligence in fiction, whether it is in books or movies, one of the greatest and most popular examples is the HAL 9000. The fiction character HAL 9000 is a heuristically programmed algorithmic computer and stars in the 1968 classic 2001: A Space Odyssey. In fact, the HAL 9000 just may be the most “true to life” or realistic artificial intelligent computer in all of fiction. Some may argue that this character is a good example of “Strong AI”, or strong artificial intelligence, which refers to the hypothesis that computers can potentially be programmed to be capable of thought due to the idea that the human mind is simply no more than a computational device itself. This fictional character is most certainly an example of “Strong AI” because the character HAL 9000 not only shows signs of self-awareness but also is capable of true reasoning.
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 ...
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.
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.
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...
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.
As our world expands through the growing abilities and applications of computers in our everyday lives, it seems that the role of the computer has been reversed. Before we knew that the computer only understood what we programmed it to understand; however, now the majority of our society is learning more from computers than they are able to input into it. Dumm (1986 p.69)
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...
...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.