There is a small but rapidly expanding literature on chatbot design, the user experience of chatbots, and the outcomes of chatbot use. They differ from searching the web because the responses are often conversational, and they provide a single answer with no need for assessment and filtering of many possible answers. User input is usually in text or speech form, while the output generated by the chatbot can be written, spoken, or visual. They can be stand-alone interventions or integrated into mobile apps, websites, texting, smart technologies, and virtual reality sites. Hybrid chatbots can use elements of both approaches. They vary in their complexity from rule-based chatbots that ask users to select from a list of prewritten queries and return an answer from a pool of predetermined responses to artificial intelligence–driven models that use natural language processing to understand user queries, inputted using free text, and generate original responses. A task-orientated chatbot is designed to provide options to solve a specific problem, for example, offering customers a menu of services, whereas a conversation-orientated chatbot is designed to generate a relationship that may continue over time. Ĭhatbots have been classified as “task (transaction) orientated” or “conversation-orientated”. A similar, but slower, rise in chatbot use in education and health has also been documented particularly within mental health care where chatbots provide cognitive behavioral therapy and support self-help for stress, anxiety, and difficulty sleeping. Chatbots are increasingly used in service and retail sectors where they offer reduced reliance on human agents, 24/7 availability, and the ability to respond to large numbers of questions quickly. A chatbot (or conversational agent) is a computer program that is designed to simulate conversation with human users.
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