Views on Computationalism: Clark vs. Searle
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.”
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: p1. The brain is constructed like a computer, since both contain parts which enable them to function. p2. The brain, like a computer, uses symbols to make calculations and perform functions. p3. The brain contains mindware similarly as a computer contains software.
c. Therefore, computers are capable of being intelligent beings.
I find, however, that Clark’s conclusion is false, and that the following considerations provide a convincing argument for the premises leading to this conclusion, starting with premise one: “the brain is constructed like a computer, since both contain parts which enable them to function.” This statement is plausible, yet questionable. Yes, the mind contains tissue, veins, and nerves etc. which enable it to function, the same way that a computer contains wires, chips, and gigabytes etc. which it needs to function. However, can it be possible to compare the two when humans devised these parts and the computer itself so that it can function? If both “machines”, as Clark believes, were constructed by the same being this comparison might be more credible. Clark might argue that humans were made just as computers were made so therefore it could be appropriate to categorize them together. I feel that this response would fail because it is uncertain where exactly humans were made and how, unless one relies on faith, whereas computers are constructed by humans in warehouses or factories.
My second argument against Clark’s claims applies to premise two: “the brain, like a computer, uses symbols to make calculations and perform functions.” Before I state what I find is wrong with this claim, I should explain the example Clark uses to support this premise, which is from the work of Jerry Fodor:
The general point behind the homunculi-head introduces consideration to the possibility of brain functions being done by parts which could not together be conscious. Functionalism requires only similar machine instructions which serve out a set of outputs given a set of inputs. Block’s counter arguments shows such an account of
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.
...ted through a first principle, consciousness. Furthermore, what is true of the sense-datum of seeing my brain is true of seeing or sensing any material object, namely that the material object appears to us as the content of the sense-datum. Here is the crux of my third objection to the materialists who propound the doctrine of mind-brain identity, that they make a fundamental mistake at the beginning of their investigation. They take the material as their Archimedian point and so build a philosophy of consciousness on a dangerously fragile basis. They try to explain what is thoroughly grounded and certain in terms of what is assumed, and subject to doubt. It is surely closer to reality to commence with mental events as foundational and to worry next whether they coexist with a physical world for it is within mental events that material bodies make their appearance.
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.
Kandel, E. R., J. H. Schwarz, and T. M. Jessel. Principles of Neural Science. 3rd ed. Elsevier. New York: 1991.
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
...e, it is clear that the mind and brain are not the same thing. If they were, then the two would not have any contradicting qualities. The mind is not divisible, but the brain is. Therefore, the two have a characteristic that is different, which makes them not identical.
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.
When most people think of artificial intelligence they might think of a scene from I, Robot or from 2001: A Space Odyssey. They might think of robots that highly resemble humans start a revolution against humanity and suddenly, because of man’s creation, man is no longer the pinnacle of earth’s hierarchy of creatures. For this reason, it might scare people when I say that we already utilize artificial intelligence in every day society. While it might not be robots fighting to win their freedom to live, or a defense system that decides humanity is the greatest threat to the world, artificial intelligence already plays a big role in how business is conducted today.
R. L. Paul, M. M. (1972). The Species of the Brain Research, 1-19. pp. 113-117. S. A. Clark, T. A.
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.