Chatbot
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.
For the bot-creation software, see ChatBot. For bots on Internet Relay Chat, see IRC bot.
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]
As chatbots work by predicting responses rather than knowing the meaning of their responses, this means they can produce coherent-sounding but inaccurate or fabricated content, referred to as ‘hallucinations’. When humans use and apply chatbot content contaminated with hallucinations, this results in ‘botshit’.[10] Given the increasing adoption and use of chatbots for generating content, there are concerns that this technology will significantly reduce the cost it takes humans to generate, spread and consume botshit.[11]
Development[edit]
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]
Chatbots may use artificial neural networks as a language model. For example, generative pre-trained transformers (GPT), which use the transformer architecture, have become common to build sophisticated chatbots. The "pre-training" in its name refers to the initial training process on a large text corpus, which provides a solid foundation for the model to perform well on downstream tasks with limited amounts of task-specific data. An example of a GPT chatbot is ChatGPT.[23] Despite criticism of its accuracy and tendency to “hallucinate”—that is, to confidently output false information and even cite non-existent sources—ChatGPT has gained attention for its detailed responses and historical knowledge. Another example is BioGPT, developed by Microsoft, which focuses on answering biomedical questions.[24][25] In November 2023, Amazon announced a new chatbot, called Q, for people to use at work.[26]
DBpedia created a chatbot during the GSoC of 2017.[27][28][29] It can communicate through Facebook Messenger (see Master of Code Global article).
The creation and implementation of chatbots is still a developing area, heavily related to artificial intelligence and machine learning, so the provided solutions, while possessing obvious advantages, have some important limitations in terms of functionalities and use cases. However, this is changing over time.
The most common limitations are listed below:[94]
In 2023, US-based National Eating Disorders Association replaced its human helpline staff with a chatbot but had to take it offline after users reported receiving harmful advice from it.[96][97][98]
Chatbots and jobs[edit]
Chatbots are increasingly present in businesses and often are used to automate tasks that do not require skill-based talents. With customer service taking place via messaging apps as well as phone calls, there are growing numbers of use-cases where chatbot deployment gives organizations a clear return on investment. Call center workers may be particularly at risk from AI-driven chatbots.[99]
Chatbot jobs
Chatbot developers create, debug, and maintain applications that automate customer services or other communication processes. Their duties include reviewing and simplifying code when needed. They may also help companies implement bots in their operations.
A study by Forrester (June 2017) predicted that 25% of all jobs would be impacted by AI technologies by 2019.[100]
Prompt Engineering, the task of designing and refining prompts (inputs) leading to desired AI-generated responses has gained significant demand and popularity in recent years, with the advent of sophisticated models, notably OpenAI’s GPT series (which still contain notable flaws and limitations, as previously outlined).
