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.
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.
It seems evident at this point that a human mind is not...
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... the same thing that Searle does in his work: intentionality. I do not think that understanding synonymous with intentionality. In fact, I think that intentionality is the only definite way to get out of the double bind and still prove the Chinese room argument to be true. Intentionality is not a form of understanding, but rather seems to be a form of consciousness that is something a human can explain, but not ascribe to something else.
The Chinese room argument certainly shows a distinction between a human mind and strong AI. However, it seems that the depths of human understanding can also be a weakness to how it compares to strong AI and the way that knowledge and understanding is derived.
Perry, John, Michael Bratman, and John Martin Fischer. "Minds, Brains, and
Programs. “Introduction to Philosophy. New York: Oxford UP, 2013. 298-311. Print.
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.
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.
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.
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.
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.
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.
I'll first talk about how Searle was lead to question the claim of computers being things that could actually think and were considered to have a strong sense intelligence based on the assumptions made by Alan Turing. He developed a test called the "Turing test" or, in other words, the "Imitation Game". The "Turing test" was a test that used a person (interrogator) who asked two subjects (a human and a computer) a series of questions that aided the integrator in determining which of the subjects was actually a human. (A.M. Turing, 1950, pg.) The assumptions based on the test included: If something has the ability to have thought then it is considered a thinker. The other assumption in question is that not only humans have the capability of having a mind, but other things including objects could also have a mind which makes them a thinking thing. These assumptions made Searle question on how the assumptions could be accurate, so in order to try to find a way to argue that the assumptions are not valid, so he created his experiment called the "Chinese Room Experiment". With this experiment, Searle was able to provide arguments that go against the claim proposed from the "Turing test" which I will discuss
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.
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...
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 ...
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.
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...