Ea Chatbot

[Prisc Chandola]

A chatbot (originally chatterbot)[1] is a software application or web interface that is designed to mimic human conversation through text or voice interactions.[2][3][4] Modern chatbots are typically online and use generative artificial intelligence systems that are capable of maintaining a conversation with a user in natural language and simulating the way a human would behave as a conversational partner. Such chatbots often use deep learning and natural language processing, but simpler chatbots have existed for decades.

Since late 2022, the field has gained widespread attention due to the popularity of OpenAI's ChatGPT,[5][6] followed by alternatives such as Microsoft's Copilot and Google's Gemini.[7] Such examples reflect the recent practice of basing such products upon broad foundational large language models, such as GPT-4 or the Gemini language model, that get fine-tuned so as to target specific tasks or applications (i.e., simulating human conversation, in the case of chatbots). Chatbots can also be designed or customized to further target even more specific situations and/or particular subject-matter domains.[8]

A major area where chatbots have long been used is in customer service and support, with various sorts of virtual assistants.[9] Companies spanning a wide range of industries have begun using the latest generative artificial intelligence technologies to power more advanced developments in such areas.[8]

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.[13]

ELIZA's key method of operation (copied by chatbot designers ever since) involves the recognition of clue words or phrases in the input, and the output of the 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').[13] 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".

Among the most notable early chatbots are ELIZA (1966) and PARRY (1972).[14][15][16][17] More recent notable programs include A.L.I.C.E., Jabberwacky and D.U.D.E (Agence Nationale de la Recherche and CNRS 2006). While ELIZA and PARRY were used exclusively to simulate typed conversation, many chatbots now include other functional features, such as games and web searching abilities. In 1984, a book called The Policeman's Beard is Half Constructed was published, allegedly written by the chatbot Racter (though the program as released would not have been capable of doing so).[18]

From 1978[19] to some time after 1983,[20] the CYRUS project led by Janet Kolodner constructed a chatbot simulating Cyrus Vance (57th United States Secretary of State). It used case-based reasoning, and updated its database daily by parsing wire news from United Press International. The program was unable to process the news items subsequent to the surprise resignation of Cyrus Vance in April 1980, and the team constructed another chatbot simulating his successor, Edmund Muskie.[21][20]

One pertinent field of AI research is natural-language processing. Usually, weak AI fields employ specialized software or programming languages created specifically for the narrow function required. For example, A.L.I.C.E. uses a markup language called AIML,[3] which is specific to its function as a conversational agent, and has since been adopted by various other developers of, so-called, Alicebots. Nevertheless, A.L.I.C.E. is still purely based on pattern matching techniques without any reasoning capabilities, the same technique ELIZA was using back in 1966. This is not strong AI, which would require sapience and logical reasoning abilities.

Jabberwacky learns new responses and context based on real-time user interactions, rather than being driven from a static database. Some more recent chatbots also combine real-time learning with evolutionary algorithms that optimize their ability to communicate based on each conversation held. Still, there is currently no general purpose conversational artificial intelligence, and some software developers focus on the practical aspect, information retrieval.

Chatbot competitions focus on the Turing test or more specific goals. Two such annual contests are the Loebner Prize and The Chatterbox Challenge (the latter has been offline since 2015, however, materials can still be found from web archives).[22]

Since September 2017, this has also been as part of a pilot program on WhatsApp. Airlines KLM and Aeromxico both announced their participation in the testing;[32][33][34][35] both airlines had previously launched customer services on the Facebook Messenger platform.

Many banks, insurers, media companies, e-commerce companies, airlines, hotel chains, retailers, health care providers, government entities, and restaurant chains have used chatbots to answer simple questions, increase customer engagement,[36] for promotion, and to offer additional ways to order from them.[37] Chatbots are also used in market research to collect short survey responses.[38]

Previous generations of chatbots were present on company websites, e.g. Ask Jenn from Alaska Airlines which debuted in 2008[41] or Expedia's virtual customer service agent which launched in 2011.[41][42] The newer generation of chatbots includes IBM Watson-powered "Rocky", introduced in February 2017 by the New York City-based e-commerce company Rare Carat to provide information to prospective diamond buyers.[43][44]

Used by marketers to script sequences of messages, very similar to an autoresponder sequence. Such sequences can be triggered by user opt-in or the use of keywords within user interactions. After a trigger occurs a sequence of messages is delivered until the next anticipated user response. Each user response is used in the decision tree to help the chatbot navigate the response sequences to deliver the correct response message.

Chatbots have great potential to serve as an alternate source for customer service.[48] Many high-tech banking organizations are looking to integrate automated AI-based solutions such as chatbots into their customer service in order to provide faster and cheaper assistance to their clients who are becoming increasingly comfortable with technology. In particular, chatbots can efficiently conduct a dialogue, usually replacing other communication tools such as email, phone, or SMS. In banking, their major application is related to quick customer service answering common requests, as well as transactional support.

Deep learning techniques can be incorporated into chatbot applications to allow them to map conversations between users and customer service agents, especially in social media.[49] Research has shown that methods incorporating deep learning can learn writing styles from a brand and transfer them to another, promoting the brand's image on social media platforms.[49] Chatbots can create new ways of brands and user interactions, which can help improve the brand's performance and allow users to gain "social, information, and economic benefits".[49]

Several studies report significant reduction in the cost of customer services, expected to lead to billions of dollars of economic savings in the next ten years.[50] In 2019, Gartner predicted that by 2021, 15% of all customer service interactions globally will be handled completely by AI.[51] A study by Juniper Research in 2019 estimates retail sales resulting from chatbot-based interactions will reach $112 billion by 2023.[52]

Since 2016, when Facebook allowed businesses to deliver automated customer support, e-commerce guidance, content, and interactive experiences through chatbots, a large variety of chatbots were developed for the Facebook Messenger platform.[53]

The France's third-largest bank by total assets[56] Socit Gnrale launched their chatbot called SoBot in March 2018. While 80% of users of the SoBot expressed their satisfaction after having tested it, Socit Gnrale deputy director Bertrand Cozzarolo stated that it will never replace the expertise provided by a human advisor.[57]

Chatbots are also appearing in the healthcare industry.[60][61] A study suggested that physicians in the United States believed that chatbots would be most beneficial for scheduling doctor appointments, locating health clinics, or providing medication information.[62]

The GPT chatbot ChatGPT is able to answer user queries related to health promotion and disease prevention such as screening and vaccination.[63] Whatsapp has teamed up with the World Health Organization (WHO) to make a chatbot service that answers users' questions on COVID-19.[64]

In 2020, The Indian Government launched a chatbot called MyGov Corona Helpdesk,[65] that worked through Whatsapp and helped people access information about the Coronavirus (COVID-19) pandemic.[66][67]

Certain patient groups are still reluctant to use chatbots. A mixed-methods study showed that people are still hesitant to use chatbots for their healthcare due to poor understanding of the technological complexity, the lack of empathy, and concerns about cyber-security.[68] The analysis showed that while 6% had heard of a health chatbot and 3% had experience of using it, 67% perceived themselves as likely to use one within 12 months. The majority of participants would use a health chatbot for seeking general health information (78%), booking a medical appointment (78%), and looking for local health services (80%). However, a health chatbot was perceived as less suitable for seeking results of medical tests and seeking specialist advice such as sexual health.

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