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This paper describes the human information behaviours of long-time users of voice assistants or chatbot software that focuses on voice interaction to retrieve information, and which operate on technologies that use artificial intelligence to understand and act upon the information requests of the user through a conversational interface. The paper reports on a case study based on 10 interviews with adult participants who have used voice assistants in their homes for at least six months. Interviews were semi-structured and focused on connecting to the users' and their family's experiences of using voice assistants in their daily lives. Insights from our findings focus on two areas, how the humanness of voice assistants and their perceived personality affect information retrieval, and secondly, the difficulties in transitioning from text-based information seeking to speech-based interactions. This paper makes a case for expanding human information behaviour studies to include interactive conversational information retrieval devices such as voice assistants. [ABSTRACT FROM AUTHOR]

This paper reviews different types of conversational agents used in health care for chronic conditions, examining their underlying communication technology, evaluation measures, and AI methods. A systematic search was performed in February 2021 on PubMed Medline, EMBASE, PsycINFO, CINAHL, Web of Science, and ACM Digital Library. Studies were included if they focused on consumers, caregivers, or healthcare professionals in the prevention, treatment, or rehabilitation of chronic diseases, involved conversational agents, and tested the system with human users. The search retrieved 1087 articles. Twenty-six studies met the inclusion criteria. Out of 26 conversational agents (CAs), 16 were chatbots, seven were embodied conversational agents (ECA), one was a conversational agent in a robot, and another was a relational agent. One agent was not specified. Based on this review, the overall acceptance of CAs by users for the self-management of their chronic conditions is promising. Users' feedback shows helpfulness, satisfaction, and ease of use in more than half of included studies. Although many users in the studies appear to feel more comfortable with CAs, there is still a lack of reliable and comparable evidence to determine the efficacy of AI-enabled CAs for chronic health conditions due to the insufficient reporting of technical implementation details. [ABSTRACT FROM AUTHOR]

This paper explores the potential of using chatbots to improve the academic research experience for university students with a literature-based discussion reflecting on a prototype being developed at the University of Technology Sydney (UTS). The paper proposes that information professionals need to adapt emerging technologies such as chatbots to innovate, improve and support library services. Designing a positive experience for the user is essential to ensure that such technological solutions are sustainable. In this exploratory paper, we argue that it is important that librarians engage with the conversational design of the library chatbot in collaboration with the technology developers in order to make it useful, friendly, trustworthy, and customisable for university students. [ABSTRACT FROM AUTHOR]