Minds, Brain And Programs By John R. Searle

Through this, Searle argues that if a human and machine receive the same input and then respond by the same output, how are they any different from one another? When given the same purpose, humans and machines have the same response, therefore machines may have a mind. Gilbert Ryle created The computational theory of mind that claims “Computers behave in seemingly rational ways; their inner program causes them to behave in this way and therefore mental states are just like computational states”. He continues on by saying that “If logic can be used to command, and these commands can be coded into logic, then these commands can be coded in terms of 1s and 0s, therefore giving modern computers logic. Through this, how is one to tell if robots don’t have minds if they use logic just like humans do. When the purpose of humans and machines are the same, they may process differently in order to complete that purpose, although they may have the same output. Because humans and machines receive the same input and return the same output, they both have minds in addition to functions and processes in order to do that.

Artificial Inelegance topic has captivated the minds of researches and common people alike. The use of AI comes into being as to try to understand our own brain and create a thinking machine. To begin the topic, one must explain of john Searles arguments against what he calls StrongAI. Searles creates a distinction between Strong Ai and Weak AI. While he has no issue with Weak Ai which is the idea of computers that assist us in crunching numbers based on our inputs

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

The most prominent example of the concept of a machine being intelligent in the manner of this so

The principle of a strong AI is that an appropriately programmed computer is actually thinking, as opposed to simulating thought. © Principle is equivalent(c?) to accepting the Turing Test as the definition of thought. Which Searle would not be surprised to see that a machine still hasn’t passed. Searle’s argument is straightforward. Searle’s premise on the “Chinese Room” is that someone who understands English sitting in a room with a set of rules that tells this person how to respond to questions written in Chinese in such a way as to pass the Turing test. To Searle this person in the room doesn’t “understand” (e) Chinese. Understanding, being that real comprehension or thought isn’t existent. So to Searle, any machine that can be passed by systems, which behave in purely formal ways (eP), can be explained in purely formal ways ©, just like the Chinese Room, so it is not an adequate test. Main idea to Searle is that person answering Chinese questions is not engaged in “intentional” behavior with theses questions, and is not “thinking about”(eP? Merely reacting to a mix of emotions/past experience) the answers. Thus, the test is

Even with the correct programming a computer cannot freely think for itself, with its own conscious thought. John Searle is a philosopher of mind and language at UC Berkeley. Searle’s Chinese Room Argument is against the premise of Strong AI. He argues that even though a computer may have the ability to compute the use of syntax (Weak AI), a computer could not be able to understand the meaning behind the words it is communicating. Semantics convey both intentional and un-intentional content in communication. Though a computer could be programmed to recognize which words would convey the correct meaning of a symbol. This,

John Searle 1980(in Cooney, 2000), provides a thought experiment, commonly referred to as the Chinese room argument (CRA), to show that computers, programmed to simulate human cognition, are incapable of understanding language. The CRA requires us to consider a scenario where Searle, who is illiterate in Chinese, finds himself locked in a room with a book containing Chinese characters. Additionally, he has another book which has a set of instructions written in English (which he understands), that allows him to match and manipulate the Chinese characters so that he can provide appropriate written responses (in Chinese) to incoming questions, which are also written in Chinese. Moreover, Searle has a pile of blank paper with which he uses to jot down his answers. Subsequently, Searle becomes so proficient in providing responses that the quality of his answers matches that of a native Chinese speaker. Thus, Searle in the CR functions as a computer would, where he is the system while the books are the program and the blank paper acts as storage.

Due to the fact that Searle is inside the room and does not actually understand Chinese, he claims the Chinese Room cannot be cognitively. Therefor, the Chinese Room would be functionally equivalent but not cognitively equivalent to the native Chinese speakers and furthermore, if the Chinese Room can imitate understanding without truly having it, then both Strong AI and Functionalism would have to be invalid. Functionalism’s imperative is to show that functional equivalence must always equal cognitive equivalence, so if one could show functional equivalence did not equal cognitive equivalence then Functionalism would be invalid. Additionally, if a computer or some other system could imitate intelligence without retaining understanding, then strong AI would be invalid as well. Strong AI is the view that if a machine can successfully imitate human intelligence in a way that it becomes functionally and cognitively equivalent to a mind, then the computer itself is a mind. Strong AI and its advocates respond to Searle’s claims by applying the Systems Reply. The Systems Reply states that despite the fact that Searle does not understand Chinese in the Chinese Room, the system as a whole does in fact understand Chinese. Just because Searle, or the

“Can Computers Have True Artificial Intelligence?” BBC, 3 Apr. 2012, www.bbc.com/news/technology-17547694. Accessed by 23 May 2017.

John Searle formulated the Chinese Room Argument in the early 80’s as an attempt to prove that computers are not cognitive operating systems. In short though the immergence of artificial and computational systems has rapidly increased the infinite possibility of knowledge, Searle uses the Chinese room argument to shown that computers are not cognitively independent.

Is John Searle’s Chinese room argument a decisive objection to functionalism? Why or why not? Introduction Development within artificial intelligence (AI) has produced machines or computers that can imitate human-like understanding and intelligence. Programs have been produced to allow AI a form of seemingly natural interaction. Due to such movement in technology can we use the notion of functionalism to suggest that these AI can understand, think and be intelligent?

John Searle is an American philosopher who was known for creating the thought experiment, the Chinese room for challenging the idea of strong AI and functionalism. Searle’s work, Minds, Brains and Programs introduces the Chinese room and refutes some objections to the points he brings up.

* Developments in computer science would lead to parallels being drawn between human thought and the computational functionality of computers, opening entirely new areas of psychological thought. Allen Newell and Herbert Simon spent years developing the concept of artificial intelligence (AI) and later worked with cognitive psychologists regarding the implications of AI. The effective result was more of a framework conceptualization of mental functions with

In his paper “Computing Machinery and Intelligence,” Alan Turing sets out to answer the question of whether machines can think in the same humans can by conceptualizing the question in concrete terms. In simple terms, Turing redefines the question by posing whether a machine can replicate the cognition of a human being. Yet, some may object to the notion that Turing’s new question effectively captures the nature of machines’ capacity for thought or consciousness, such as John Searle. In his Chinese room thought experiment, Searle outlines a scenario that implies machines’ apparent replication of human cognition does not yield conscious understanding. While Searle’s Chinese thought experiment demonstrates how a Turing test is not sufficient to establish that a machine can possess consciousness or thought, this argument does not prove that machines are absolutely incapable of consciousness or thought. Rather, given the ongoing uncertainty of the debate regarding the intelligence of machines, there can be no means to confirm or disconfirm the conscious experience of machines as well as the consciousness of humans by extension of that principle.

Substantial studying has been made on the subject and Turing’s overly optimistic point of view, yet, we experience difficulty when trying to combine idea of advancement in technology and what makes us humans: the capability of thinking. Conventionally, we have firmly grasp to the idea that the act of thinking is the official stamp of authenticity which differentiate humans from the rest of beings, and so while trying to decide if a computer can think or not, we are closely scrutinizing the foundation of our nature as beings to its core. But before we dive into the subject matter of why I disagree with Turing, we must inquire about what exactly is thinking. Some have tried to define thinking as having conscious thoughts; but thinking and consciousness are not terminologies that are mutually exchangeable. While thinking is a state of consciousness, consciousness is not thinking. Even as we process information necessary for reasoning, much of our brain activity and processing takes