Developing a natural language-based AI-chatbot for social work training

An illustrative case study

Bibliographic Data

ID12914352
AuthorsChitat Chan (0000-0003-4674-9597, Hong Kong Baptist University, corresponding author), Feng Li (0000-0002-6589-6392, Inspur (China))
Year2023
Volume16
Issue2
Pages121-136
Publication date2023-03-05
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueChina Journal of Social Work (JOURNAL)
Journal identifiersISSN: 1752-5098 • E-ISSN: 1752-5101
PublisherTaylor & Francis (PUBLISHER • GB)
DOI10.1080/17525098.2023.2176901
OpenAlexW4323316263
LanguageEN
Citations received11
References cited29

A chatbot is a computer program designed to simulate conversation with human users. In social services, many chatbots are retrieval based: they analyse users’ intents and retrieve preset answers based on decision tree logic. A major limitation of these earlier chatbots was that their conversations were rigid, unnatural, and sounded like a multiple-choice questionnaire. Recent achievements in large-scale generative pretrained transformers (LGPTs) (e.g. GPT-3, Yuan 1.0) have offered new possibilities for chatbot development. Such technology provides a high-quality natural language experience, requires much less resource input than earlier chatbot technologies, and is much more accessible to the public. However, the use of LGPT-based cfhatbots in social work, particularly in a Chinese context, is uncommon or even absent. Using an illustrative case study, this article illustrates the initial development of an LGPT-based chatbot to support social work training in a Chinese context and discusses the possibilities for further development

Chatbot · Context (archaeology · Conversation · Data science · Knowledge management · Natural language · Natural language understanding · World Wide Web · AI in Service Interactions · Communication · Computer Science · Digital Mental Health Interventions · Psychology · Technology Use by Older Adults · Artificial Intelligence

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