{"title":"为社会工作培训开发基于自然语言的人工智能聊天机器人:一个说明性案例研究","authors":"Chitat Chan, Feng Li","doi":"10.1080/17525098.2023.2176901","DOIUrl":null,"url":null,"abstract":"ABSTRACT 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.","PeriodicalId":38938,"journal":{"name":"China Journal of Social Work","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Developing a natural language-based AI-chatbot for social work training: an illustrative case study\",\"authors\":\"Chitat Chan, Feng Li\",\"doi\":\"10.1080/17525098.2023.2176901\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT 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.\",\"PeriodicalId\":38938,\"journal\":{\"name\":\"China Journal of Social Work\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-03-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"China Journal of Social Work\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/17525098.2023.2176901\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Social Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"China Journal of Social Work","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/17525098.2023.2176901","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Social Sciences","Score":null,"Total":0}
Developing a natural language-based AI-chatbot for social work training: an illustrative case study
ABSTRACT 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.