PROJECT TOPIC: Design and implementation of general knowledge chatbot using natural language processing

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1.1 Background of the Study In 1950, Alan Turing’s famous article “Computing Machinery and Intelligence” was published (Turing, Alan (1950), which proposed what is now called the Turing test as a criterion of intelligence. This criterion depends on the ability of a computer program to impersonate a human in a real-time written conversation with a human judge, sufficiently well that the judge is unable to distinguish reliably—on the basis of the conversational content alone—between the program and a real human. The notoriety of Turing’s proposed test stimulated great interest in Joseph Weizenbaum’s program ELIZA, published in 1966, which seemed to be able to fool users into believing that they were conversing with a real human. However Weizenbaum himself did not claim that ELIZA was genuinely intelligent, and the Introduction to his paper presented it more as a debunking exercise: [In] artificial intelligence … machines are made to behave in wondrous ways, often sufficient to dazzle even the most experienced observer. But once a particular program is unmasked, once its inner workings are explained … its magic crumbles away; it stands revealed as a mere collection of procedures … The observer says to himself “I could have written that”. With that thought he moves the program in question from the shelf marked “intelligent”, to that reserved for curios … The object of this paper is to cause just such a re-evaluation of the program about to be “explained”. Few programs ever needed it more (Weizenbaum, Joseph January 1966). ELIZA’s key method of operation (copied by chatbot designers ever since) involves the recognition of cue words or phrases in the input, and the output of corresponding pre-prepared or pre-programmed responses that can move the conversation forward in an apparently meaningful way (e.g. by responding to any input that contains the word ‘MOTHER’ with ‘TELL ME MORE ABOUT YOUR FAMILY’) (Weizenbaum, Joseph January 1966). Thus an illusion of understanding is generated, even though the processing involved has been merely superficial. ELIZA showed that such an illusion is surprisingly easy to generate, because human judges are so ready to give the benefit of the doubt when conversational responses are capable of being interpreted as “intelligent”. Interface designers have come to appreciate that humans’ readiness to interpret computer output as genuinely conversational—even when it is actually based on rather simple pattern-matching—can be exploited for useful purposes. Most people prefer to engage with programs that are human-like, and this gives chatbot-style techniques a potentially useful role in interactive systems that need to elicit information from users, as long as that information is relatively straightforward and falls into predictable categories. Thus, for example, online help systems can usefully employ chatbot techniques to identify the area of help that users require, potentially providing a “friendlier” interface than a more formal search or menu system. This sort of usage holds the prospect of moving chatbot technology from Weizenbaum’s “shelf … reserved for curios” to that marked “genuinely useful computational methods”.

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