A chatbot (also known as a talkbot, chatterbot, Bot, IM bot, interactive agent, or Artificial Conversational Entity) is a computer program or an artificial intelligence which conducts a conversation via auditory or textual methods. Such programs are often designed to convincingly simulate how a human would behave as a conversational partner, thereby passing the Turing test. Chatbots are typically used in dialog systems for various practical purposes including customer service or information acquisition. Some chatterbots use sophisticated natural language processing systems, but many simpler systems scan for keywords within the input, then pull a reply with the most matching keywords, or the most similar wording pattern, from a database.
The term “ChatterBot” was originally coined by Michael Mauldin (creator of the first Verbot, Julia) in 1994 to describe these conversational programs. Today, most chatbots are either accessed via virtual assistants such as Google Assistant and Amazon Alexa, via messaging apps such as Facebook Messenger or WeChat, or via individual organizations’ apps and websites. Chatbots can be classified into usage categories such as conversational commerce (e-commerce via chat), analytics, communication, customer support, design, developer tools, education, entertainment, finance, food, games, health, HR, marketing, news, personal, productivity, shopping, social, sports, travel and utilities.
There are two types of chatbots Rule based bots and AI bots.
In a rule-based approach, a bot answers questions based on some rules on which it is trained on. The rules defined can be very simple to very complex. The creation of these bots are relatively straightforward using some rule-based approach, but the bot is not efficient in answering questions, whose pattern does not match with the rules on which the bot is trained.
AI is the technology that allows the bot to learn from the interactions it has with the end users. Behind this learnings there are analytics platforms, and integrations with APIs, among other things, that feed the AI and provide resources so that that the chatbot is able to provide the user with correct answers.
Depending on the purpose with which the chatbot was created, its functionality will be determined. Below you can read some of the most come uses for Chatbots:
a) Virtual Assistants:
Businesses use chatbots for a variety of cases, such as customer service. Simply put, an artificial intelligence service can be used to answer simple questions, help users book services, get more information about a specific topic, buy a product, etc. Having a chatbot help expedite this types of tasks, allows for human agents to focus on more relevant problems.
b) Automation of manual processes:
The use of intelligent algorithms, for example, can now automate the process of collecting data from various reports and perform an analysis to determine the profitability of a particular business path.
c) Analysis of unstructured data:
It is estimated that 80% of the digital data is not structured. Organizing and tracking these data has the potential of leading to a better understanding of the users and making predictions based on tendencies.
In 1950, Alan Turing’s famous article “Computing Machinery and Intelligence” was published, 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:
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.
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’). 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”.