The Debate Over Artificial Intelligence Essay

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.

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

With today’s technology we haven’t found a way for a computer to think for itself.  This can only happen with the potentialities that will develop over time.  The future may hold great opportunities for this new found world.

Thinking is involved in all conscious mental activity, whether it is acquiring new knowledge, remembering, planning ahead, or day dreaming. Involves manipulating mental representations of info

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,

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.

Intense developmental stages in technology have brought us into a place we never thought we would be in, where instances of computers can function correspondingly to us humans. These machines can perform acts such as playing chess and sorting mail, which are actions that most of us have done before. Both William G. Lycan and John R. Serle assess this topic, using different thought experiments, but both introduce the term Artificial Intelligence. Both philosopher’s objectives are not to argue whether this is possible but how will we distinguish humans from computers.

Searle thought that computers can’t think because they are programmed and lack the biological means to think. John Searle’s argument uses the difference between strong artificial intelligence and weak or cautious artificial intelligence. Strong Artificial intelligence will make it seem that an appropriately programmed computer will be able to seem like it can think and understand. Computers can seem to trick people into thinking

The conditions of the present scenario are as follows: a machine, Siri*, capable of passing the Turing test, is being insulted by a 10 year old boy, whose mother is questioning the appropriateness of punishing him for his behavior. We cannot answer the mother's question without speculating as to what A.M. Turing and John Searle, two 20th century philosophers whose views on artificial intelligence are starkly contrasting, would say about this predicament. Furthermore, we must provide fair and balanced consideration for both theorists’ viewpoints because, ultimately, neither side can be “correct” in this scenario. But before we compare hypothetical opinions, we must establish operant definitions for all parties involved. The characters in

In Minds, Brains, and Programs John Searle objects to Computational Theory of Mind (CTM), particularly that running a program on a computer and manipulating symbols does not mean that the computer has understanding, or more generally a mind. In this paper I will first explain Searle’s Chinese Room, then I will explain CTM and how it relates to the Chinese Room. Following this I will describe how the Chinese Room attacks the CTM. Next I will explain the Systems Reply to the Chinese Room and how the Systems Reply actually undermines Searle’s conclusion in the Chinese Room. Then I will describe Searle’s response to the Systems Reply and how that response undermines the Systems Reply. Lastly, I will evaluate Searle’s reply to the Systems Reply and defend the Systems Reply against the points Searle raises against the Systems Reply.

In today’s society, artificial intelligence appears a daunting and frightening area, however this idea was embraced by Turing. He was a pioneer of imitation, that is, the imitation of the human mind in a machine. The perspectives of Turing with regards to artificial intelligence were new and original, nobody had questioned whether or not a machine can think or likened one to the human mind. It is important to remember that artificial intelligence is only an attempt at recreating the human machine, as Turing put it, which is the mind. In 1942, Turing was quoted saying: “We do not wish to penalise the machine for its inability to shine in beauty competitions, nor to penalise a man for losing in a race against an aeroplane” which demonstrates one of Turing’s key perspectives. Man and machine are going to be different, an attempt at copying the human mind, will not yield a human, but a machine, reinforcing the fact that artificial intelligence is only an attempt to imitate the mind. A paper, written by Turing, outlines an “imitation test,” a test which contrasts the power of the human mind to that of a machine. This test was developed by Turing in order to help the public grasp the concept of an artificial intelligence: it precedes as follows. A participant is asked to take part in two conversations, one of which is with a machine, the other with a human. Now imagine if the participant was unable to decide which was the machine and which was human. Turing

John Searle starts with two claims of programmed computers being able to have a process where they would understand knowledge and the claim of computers understanding how the human mind works. Searle then states that these claims are rather untrue or without reason.

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.

Artificial Intelligence is a topic within the public media that has existed for decades, but is now a concern due to the reality of human advancement and innovation in the field of science and technology. Many people believe that computers will become self-aware or sentient and view humanity as a disposable resource and gain supremacy. Reasoning that research on the technology should halt and not become more advance. Whereas others believe they will help catapult research and the economy forward, supporting the operations and innovations the technology offers. The complicated and divided solutions to the debate aren’t obvious, but there are more benefits to improving artificial intelligence than there is stopping it. Therefore, the negative effects people believe will occur can be resolved.

In the future, we may be able to build a computer that is comparable to the human brain, but not until we truly understand one thing. Lewis Thomas talks about this in his essay, "Computers." He says, "It is in our collective behavior that we are most mysterious. We won't be able to construct machines like ourselves until we've understood this, and we're not even close" (Thomas 473). Thomas wrote this essay in 1974, and although we have made many technological advances