The philosophy of artificial intelligence attempts to answer such questions as:[1] <\/p>\n
These three questions reflect the divergent interests of AI researchers, cognitive scientists and philosophers respectively. The scientific answers to these questions depend on the definition of \"intelligence\" and \"consciousness\" and exactly which \"machines\" are under discussion. <\/p>\n
Important propositions in the philosophy of AI include: <\/p>\n
Is it possible to create a machine that can solve all the problems humans solve using their intelligence? This question defines the scope of what machines will be able to do in the future and guides the direction of AI research. It only concerns the behavior of machines and ignores the issues of interest to psychologists, cognitive scientists and philosophers; to answer this question, it does not matter whether a machine is really thinking (as a person thinks) or is just acting like it is thinking.[7] <\/p>\n
The basic position of most AI researchers is summed up in this statement, which appeared in the proposal for the Dartmouth Conferences of 1956: <\/p>\n
Arguments against the basic premise must show that building a working AI system is impossible, because there is some practical limit to the abilities of computers or that there is some special quality of the human mind that is necessary for thinking and yet cannot be duplicated by a machine (or by the methods of current AI research). Arguments in favor of the basic premise must show that such a system is possible. <\/p>\n
The first step to answering the question is to clearly define \"intelligence.\" <\/p>\n
Alan Turing, in a famous and seminal 1950 paper,[9] reduced the problem of defining intelligence to a simple question about conversation. He suggests that: if a machine can answer any question put to it, using the same words that an ordinary person would, then we may call that machine intelligent. A modern version of his experimental design would use an online chat room, where one of the participants is a real person and one of the participants is a computer program. The program passes the test if no one can tell which of the two participants is human.[2] Turing notes that no one (except philosophers) ever asks the question \"can people think?\" He writes \"instead of arguing continually over this point, it is usual to have a polite convention that everyone thinks.\"[10] Turing's test extends this polite convention to machines: <\/p>\n
One criticism of the Turing test is that it is explicitly anthropomorphic. If our ultimate goal is to create machines that are more intelligent than people, why should we insist that our machines must closely resemble people? Russell and Norvig write that \"aeronautical engineering texts do not define the goal of their field as 'making machines that fly so exactly like pigeons that they can fool other pigeons.'\"[11] <\/p>\n
Recent AI research defines intelligence in terms of intelligent agents. An \"agent\" is something which perceives and acts in an environment. A \"performance measure\" defines what counts as success for the agent.[12] <\/p>\n
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See the original post here: <\/p>\n
Philosophy of artificial intelligence - Wikipedia, the ...<\/a><\/p>\n","protected":false},"excerpt":{"rendered":" The philosophy of artificial intelligence attempts to answer such questions as:[1] These three questions reflect the divergent interests of AI researchers, cognitive scientists and philosophers respectively. The scientific answers to these questions depend on the definition of \"intelligence\" and \"consciousness\" and exactly which \"machines\" are under discussion. Important propositions in the philosophy of AI include: Is it possible to create a machine that can solve all the problems humans solve using their intelligence Continue reading