John Searle’s Chinese Room argument is a thought experiment in which Searle tries to refute the Turing Test and Strong AI. It involves a person, a room, 2 slots labeled A and B, and 3 pieces of paper. The Chinese Room argument was aimed at the position called “Strong AI” (Cole), also known as Representational Theory of the Mind, and against the Turing Test created by Alan Turing. The problem with the Chinese Room argument is that it misses the point entirely – Searle compares a CPU or computer to a person, a non-conscious object with a conscious agent (Cole). The argument also gets extrapolating the functions of the brain from a greater whole to a smaller part of the brain wrong – as a whole you may know things, but certain areas of the brain will always know more than we consciously do. Because of these issues, Searle fails to properly damage the “Strong AI” theory.
The Representational Theory
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Syntax by itself is neither constitutive of nor sufficient for minds. 4. Therefore, programs are neither constitutive of nor sufficient for minds. (Searle, 1993)
The Chinese Room argument was also made specifically for the position of what he calls “Strong AI”. Strong AI is the Representational Theory of the Mind and the view that sufficiently programmed computers or systems have the ability to understand natural language and seriously have other mental faculties similar to the people that their behavior mimic. With this view, a computer or artificial intelligence could actually play a game intelligently, make clever moves, and understand a natural language (Cole).
According to the Stanford Encyclopedia of Philosophy, Searle’s Chinese Room Argument damages Strong AI according to this logic structure: If Strong AI is true, then there is a program for Chinese that if a computing system runs that program, the system therefore comes to understand Chinese. Someone could run a program for Chinese without learning to understand Chinese. Therefore, Strong AI is false
The author Tex G. Hall is explaining Native American team sports mascots are racist. He is testifying for many other people as well. He makes a very sensible are you and uses the motion and great facts facts. The way his argument is structured is very engaging. He first off thanks many people for bringing this controversy to everyone 's attention.
AI or artificial intelligence is not a modern concept, but rather a field of research that dates back to the mid-twentieth century. More recently though, privately owned Open AI has created a chatbot that uses artificial intelligence to respond to human formed questions. Gaining a public interest, Chat GPT satisfactorily passed a UPENN Wharton Business Exam, ranking notable scores in the English section, but unsatisfactory levels in the math section. When tasked with comparing the principles of the transcendentalists with Christopher Mccandless from Into the Wild, GPT produces an unsatisfactory essay. Although Chat GPT compares the transcendentalist lifestyle of Christopher Mccandless and the Transcendentalists logically, many of the arguments
He suggests humans have more controlling over machines. He supports his thought by referring to computers in chess that “the computer has no intuition at all, it analyzes the game using brute force [and] inspects the pieces currently on the board, then calculates all options” (Thompson 343). He points out that the way computer thinks is “fundamentally unhuman” and it is the player who runs the program and decides which moves to take (Thompson 343). After all, computers are just tools that we use to optimize accuracy and
He argues that machines can simply match an input with an output, but this does not indicate that there is any understanding (4). This can be further explained as Searle illustrates the simulation of a person being given Chinese characters to view with no knowledge whatsoever of the language. The person is given another set of Chinese writing with instructions in English that help respond to the first batch of writing and for these responses to be returned. Although the responses written by the person are synonymous to what a native Chinese speaker would deem to be correct, this does not mean the person understands Chinese, but merely the instructions in English directed the person allows them to generate viable responses. Searle continues with stating that understanding requires intentionality and machines may have calculating capacities, but may not have their own intrinsic intention that reflect mental states (11).
In agreement, the intelligence of our brain is flattening into artificial intelligence and we are heavily rely on it. As pancake, we are becoming less and less dense of our dense cultural inheritance while spreading a search wide
In his article, Searle discusses two statements. The first is that intentionality in humans is caused by features of the brain, so certain processes in the brain are satisfactory for intentionality. The other statement he discusses is that a computer program can never have intentionality. Searle states that ‘strong AI’ demands that any programmed computer displays intentionality similar to human’s.
In Google’s eyes “the human brain is just an outdated computer that needs a faster processor and a bigger hard drive” and Carr is afraid that we will become machinelike as if
What this means is the things that are being continuously made are changing our critical thinking skills. Thompson central claim is that computers are not as smart as humans, but once you have been using them over a certain amount of time you seem to get better at working them and that’s what really makes you more efficient in using them. The point that I don’t agree with Carr on is “Their thoughts and actions fell scripped, as if they're following the steps of an algorithm (p.328.)” I don’t agree with Carr’s argument here because he’s emphasizing that human thoughts are being scripted and we don’t think about things critically, but not all of our thinking
Mirabelli uses example to show the inaccuracies of this claim. The first example Mirabelli presents is the skill it takes to memorize an entire menu. A waiter must memorize the entire menu, as well as have a full understanding of the menu. Mirabelli provides the reader with an example of what happens when the waiter does not have a full understanding of the menu. “Harvey then told me that a customer had asked him about the sauce, and since he could not explain what it was, the customer did not order it” (Mirabelli 150).
Douglas employs notable examples to support his claims and rightfully proves why AI is not as risky as seen by the public. David Parnas’ “The Real Risks of Artificial Intelligence” focuses on the unseen negative aspects of Artificial Intelligence. He argues that AI programs can be untrustworthy and even in some cases, destructive due to the programming approach that programmers take. While Parnas is negative about the concept of Artificial Intelligence, Eldridge see Artificial Intelligence in a brighter light. Both authors present their arguments differently in terms of tone, level of diction, examples and organization.
This article fits with my research because it talks about the positive outcome artificial intelligence can have in the educational field. It is fairly simple to read and was helpful by proving the positive impact. It address the pros and cons about the educational AI that could be used to help students with courses they are having difficulties
In Alan Turing’s paper Computing Machinery and Intelligence, he proposes a thought experiment that would eventually be tested, and even later be beaten. He describes an experiment where a man and a woman are in two different rooms and an outside observer has to guess at the sexes of the participants. He then suggests that one of the participants be replaced with a computer. Once humanity is unable to tell the difference and will guess that the computer is human at the same rate that it will guess that it is a machine will answer Turing’s thesis of, “Can machines think?’ (434).
The Turing test has become the most widely accepted test of artificial intelligence and the most influential. There are also considerable arguments that the Turing test is not enough to confirm intelligence. Legg and Hutter (2007) cite Block (1981) and Searle (1980) as arguing that a machine may appear intelligent by using a very large set of
Artificial Intelligence is the field within computer science to explain some aspects of the human thinking. It includes aspects of intelligence to interact with the environment through sensory means and the ability to make decisions in unforeseen circumstances without human intervention. The beginnings of modern AI can be traced to classical philosophers' attempts to describe human thinking as a symbolic system. MIT cognitive scientist Marvin Minsky and others who attended the conference
I do not believe the field has been developed to its potential in any regard, and feel that considerable progress can be made to improve the interactive experience that users have with an artificial intelligence application. This genuine intrigue combined with my curiosity for the subject matter and the limitless potential of the field are the reason why I wish to pursue a greater depth of knowledge in artificial