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The Journal of Management Information Systems (JMIS) is celebrating its fifth decade of publication and is committed to publishing research papers that make significant contributions to the field of information systems. The journal's editors have an inclusive understanding of the field and aim to reflect and shape its growth and evolution. Over the years, JMIS has published papers on various topics, including the economics of IS, strategic deployment of IT, design research, neuroscience in IS research, behavioral cybersecurity, health informatics, and AI-human collaboration. The journal also recognizes its responsibility to support the well-being of society and explores the societal impacts of IT-driven change. The current issue features papers on topics such as the use of body-worn cameras in policing, technological innovation, crowdfunding, chatbots, sentiment analysis, cloud storage and security breaches, cybersecurity risk management, software architecture, and turnover of IT professionals. [Extracted from the article]

Our contemporary life is an intertwined arrangement of 'Life' with digital technologies. Increasingly, we are seeing the prevalence of automation and machines, predominantly through artificial intelligence (AI), as a means to make sense of our worlds, engage with our employers, understand the political system and interact with our social lives as some of the key methods among a wide variety of other interpersonal communication processes. Not only are these often machine-based activities seen through digital communication itself, but also in the surrounding regulatory systems, the growing concerns of digital inequality, the act of datafication, and the infrastructures that enable and inhibit digital communication. These are some of the key themes that emerged from the selected papers in this special issue emerging from the 2020 Association of Internet Researchers (AoIR) conference, entirely held online and themed around 'Life'. In this special issue, we present seven papers from senior and emerging scholars within Asia, Europe, Africa, and North and South America that address and unpack the contemporary moment of communication in our Life. The papers in this special issue discuss chatbots, games, smart lighting, wearables, doorbells, sensors, biometrics, and facial recognition technology - – very much everyday technologies that shape many of our lives. They ground our expectations of AI and highlight the importance of context in internet research. [ABSTRACT FROM AUTHOR]

This discussion article examines the potential integration of Generative Artificial Intelligence (Gen-AI), including advanced Large-Language Models like the popular platform ChatGPT into subject English education. Following the significant public and academic attention in response to these technologies through 2023, this paper considers the transformative potential and challenges posed by Gen-AI in educational settings. Central to the discussion is the exploration of how English teachers can leverage Gen-AI to enrich student learning beyond the obvious domain of writing skills. Instead, the article foregrounds the necessity for students' understanding of Gen-AI as an essential component of digital literacy. While acknowledging ethical concerns such as plagiarism, equity, and access, the paper presents an argument for the productive use of Gen-AI in the classroom to augment reading, viewing, and interpretation lessons. Avoiding an evangelical or dystopian view of AI, this discussion piece explores the time-critical and urgent issue of how, when, and why English can engage with the technology. [ABSTRACT FROM AUTHOR]

The recent popularity of ChatGPT and artificial intelligence chatbots presents both challenges and opportunities for incorporating this modern technology in the classroom. This paper introduces an activity that uses ChatGPT to help students practice their role playing sales skills. The benefits of using this AI chatbot for role play training include allowing students to practice when it's convenient and have the ability to react to a chatbot taking on personas of different buyer types. Survey results demonstrate the effectiveness of this training method for both role play training and general familiarity with ChatGPT. [ABSTRACT FROM AUTHOR]

In Temasek Polytechnic, Singapore, several AI chatbots acting as digital teaching assistants were trialed between July 2021 and August 2022. As these were developed for different purposes, it is important to learn if these AI chatbots help achieve the desired learning outcomes. This paper focuses on lessons learnt from three chatbots designed for different learning experiences: the independent learning of EXCEL, the correction of errors in the application of APA citation style, and the provision of supplementary theoretical support for software usage for Social Media Analytics. The research team studied the students' reaction to these educational chatbots, their motivation to use them, as well as the efficacy of the chatbot features to support specific purposes. This paper offers a design model that describes the three-stage approach for learning with an AI chatbot, with examples elucidating them. These sequential stages are foundational in the chatbot design to provide focused, personalised, student-controlled online learning environment. The application of this model is detailed in a fourth AI chatbot designed for the subject, Airline Management. [ABSTRACT FROM AUTHOR]

This paper examines the venture capital-driven process of making intangible assets in platform start-up firms. By examining the case study of the rise and fall of a venture capital-backed 'unicorn' firm developing a digital health platform, this paper argues that the process of real valorization of capital invested in platform start-up firms involves the making of algorithmic systems and data as intangible assets as well as the experimentation with strategies of exploitation and appropriation, which are inherently linked to the future-oriented financial valorization process of equity shares since unprofitable start-up firms continuously require outside capital to expand operations. While the fetish of 'artificial intelligence' posing the firm's chatbot for self-diagnosis as an intelligent 'doctor in your pocket' plays an important role in financial valorization, it is the failed real valorization process in making profits that ultimately leads to the platform start-up's financial collapse. The conceptual contribution of the paper centres on the contradictory nature of assetization processes which sheds light on how class domination operates in and through venture capital-driven accumulation. [ABSTRACT FROM AUTHOR]

Health chatbots interview patients and collect health data. This process makes demands on data security and data privacy. To identify how and to what extent security and privacy are considered in current health chatbots. We conducted a scoping review by searching three bibliographic databases (PubMed, ACM Digital Library, IEEExplore) for papers reporting on chatbots in healthcare. We extracted which, how, and where data is stored by health chatbots and identified which external services have access to the data. Out of 1026 retrieved papers, we included 70 studies in the qualitative synthesis. Most papers report on chatbots that collect and process personal health data, usually in the context of mental health coaching applications. The majority did not provide any information regarding security or privacy aspects. We were able to determine limitations in literature and identified concrete challenges, including data access and usage of (third-party) services, data storage, data security methods, use case peculiarities and data privacy, as well as legal requirements. Data privacy and security in health chatbots are still underresearched and related information is underrepresented in scientific literature. By addressing the five key challenges in future, the transfer of theoretical solutions into practice can be facilitated. [ABSTRACT FROM AUTHOR]

Conversational robots (chatbots) are currently an extended Insurtech that is widely used to enable policyholders' communication with insurance firms. This paper analyses customers' acceptance of chatbots in procedures with regard to in-force policies. We analysed a semistructured survey answered by workers of a public Spanish university. Structured questions have been grounded in the well-known technology acceptance model (TAM), which is based on two explanatory variables: perceived usefulness (PU) and perceived ease of use (PEOU). We have also considered two additional explanatory factors: social influence (SI), whose impact on behavioral intention (BI) is mediated by PU, and trust (TRUST), whose influence on BI is supposed to be made throughout PU and PEOU. Likewise, we asked two open questions about the advantages and disadvantages of chatbot use to make procedures linked with in-force insurance contracts. We performed our analysis by using quantitative and qualitative methods. The quantitative analysis tests the suitability of TAM on our data and has been performed by using structural equation modelling with partial least squares (PLS-SEM). Subsequently, to reach a deeper understanding of the reasons that explain the respondents' behavioral intention, we provide a systematic overview of the answers to open questions with the help of the groundwork provided by TAM. We have checked that the basic TAM along with social influence and trust provide a satisfactory explanation for behavioral intention toward bots. Likewise, we have observed a general reluctance toward the use of chatbots. The qualitative analysis showed that arguments explaining resistance come from all explanatory factors considered in the paper. Therefore, mainstream responses have outlined that interaction with chatbots is difficult, and many times, the procedure must be finished with the assistance of a human operator. Likewise, many responses point out as a relevant drawback that they provide a dehumanized service without empathy. Consequently, interactions with chatbots are perceived as cumbersome, ineffective, and a loss of time. Although some people perceive that the faster service provided by chatbots in concrete circumstances is an advantage, other theoretical consequences that may add value, such as temporal flexibility and the possibility of proving better services with the same cost and/or reducing insurance prices because of the reduction of firms' administrative costs, are generally not perceived. Our findings have theoretical and practical implications. We have shown that TAM provides a reliable theoretical model to understand policyhoders' acceptance of chatbot technology in an insurance setting. Perceived usefulness, reliability, social opinion about bot adoption, and usability must be improved to avoid generalized policyholders' reluctance. That resistance is because of issues such as conversational skills, the capability to provide an interaction closer to being human, and users' perception that chatbots actually add value to policyholders. [ABSTRACT FROM AUTHOR]

In view of the emerging spread of AI in computing systems of everyday use, it is becoming apparent that AI and HCI can mutually benefit from each other in fruitful cooperation. Overall, the article provides guidance for dealing with human-AI interaction during the decision-making process and sheds light on how explainable AI can increase users' acceptance of such systems. Explainable AI: The effect of contradictory decisions and explanations on users' acceptance of AI systems. The discussion around the rapid evolution and omnipresence of Artificial Intelligence (AI) is already rich, and AI is expected to be integrated into most aspects of everyday life. [Extracted from the article]

The paper explores how Generative AI intersects with Competition Law, focusing on Foundation Models (FMs) and Large Language Models (LLMs). It examines industry dynamics and identifies key competition issues like entry barriers, tying, leveraging, and acquisitions. It highlights the supply chain's importance and looks at how FMs are integrated into search software, chatbots, and productivity tools, particularly noting entry barriers such as computing power and data collection. It suggests that FMs might require new approaches to market delineation, possibly creating a separate relevant market for data. The paper also discusses various cases pertaining to tying and leveraging and highlights the difficulty in proving tying due to the blurred lines between traditional search engines and AI chatbots. It illustrates how competition assessments for acquisitions may require changes due to data being a highly flexible commodity for the industry. The paper concludes by calling for increased scrutiny and regulation for the industry. [ABSTRACT FROM AUTHOR]

This paper develops a critical perspective on the use of conversational agents (CAs) with children at home. Drawing on interviews with eleven parents of pre-school children living in Norway, we illustrate the ways in which parents resisted the values epitomised by CAs. We problematise CAs' attributes in light of parents' ontological perceptions of what it means to be human and outline how their attitudes correspond to Bourdieu's [1998a. Acts of Resistance. New York: New Press] concept of acts of resistance. For example, parents saw artificial conversation designed for profit as a potential threat to users' autonomy and the instant gratification of CAs as a threat to children's development. Parents' antecedent beliefs map onto the ontological tensions between human and non-human attributes and challenge the neoliberal discourse by demanding freedom and equality for users rather than productivity and economic gain. Parents' comments reflect the belief that artificial conversation with a machine inappropriately and ineffectively mimics a nuanced and intimate human-to-human experience in service of profit motives. [ABSTRACT FROM AUTHOR]

The paper presents a novel method for processing information with a spatial component or querying geospatial databases. It proposes an interactive toponym disambiguation method tailored especially for dialogue systems and chatbots. The method exploits the interactive nature of dialogues to resolve ambiguity by using dialogue clarification techniques, i.e., asking users for additional information to perform disambiguation. The paper evaluates different questioning strategies and methods for selecting suitable toponym features to formulate disambiguation questions. A novel Equi-population partitioning method for selecting suitable toponym features in questions is presented as an approach outperforming other compared methods. [ABSTRACT FROM AUTHOR]

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]

There is considerable uncertainty about the role that Artificial Intelligence (AI) might play in Environmental Impact Assessment (EIA), including into research. AI large language model (LLM) chatbots have the potential to increase the efficiency of EIA research, but their outputs can create concerns. This paper investigates the potential time savings achievable using LLM chatbots to undertake a critical review of literature focussing on the use of AI in EIA. Using a combination of ChatGPT and Elicit, literature was reviewed to identify 12 key issues associated with the use of AI in EIA and this paper was prepared in three and a half days from initial conception. A protocol is developed to assist researchers in fact checking evidence delivered through Elicit (or other machine learning tools) which serves as a novel outcome of this research. Using comments from three peer reviewers allowed some more objective reflection on the credibility of the LLM chatbot-derived output, on the appropriateness of the time savings, and on the future research needed on the application of LLM chatbots in this context. [ABSTRACT FROM AUTHOR]

Chatbots can bring innovation in online assistance and communication with customers. Due to the growth of e-commerce, fashion brands have been adopting chatbots to provide personalised consumer experiences. Research in the area of chatbots for fashion e-commerce has addressed technological advancements and consumer behaviour, but little has been done on analysing chatbot features through a holistic point of view. The aim of this paper is to offer an interdisciplinary review through a comprehensive categorisation of recent studies on the theme and inform future research in the area. To achieve that, a theme-based literature review was carried out through the analysis of specialised research. The collected work was categorised addressing both computational and non-computational perspectives. The findings show that Deep Learning, recommendation systems, audio recognition and integration of chatbots with other fashion applications are a few design opportunities to be applied in both research and practice. [ABSTRACT FROM AUTHOR]

Nowadays, new technologies are taking place for enabling conversational interactions between users and bots. Creating conversational interfaces (CI) paves the way for new design challenges. Designers need to use appropriate design specifications for creating a logically sound dialogue endowed with proper visual cues in the case of chatbots that captures the entire user experience. To do it they need the help of domain experts. Experts in mobility, environment, energy, e-health, weather, etc., are the only ones who well-know the specific domain in which the bot will act. Current tools used to design interactive flows of dialogue entail deep programming skills their users need to know. Starting from this consideration, the paper proposes a design environment that offers experts the possibility to design a flow of dialogue without getting lost in technicalities. By using visual language, the expert can specify intents, actions, entities and parameters at the base of the flow of dialogue on which the bot will be created. Then, our engine automatically translates into a bot compliant with the Google DialogFlow technology. Finally, the paper present a preliminary analysis of the system carried out to test its features and how these are reflected in its ease of use. [ABSTRACT FROM AUTHOR]

A popular chatbot can generate natural and human-like responses, and the crucial technology is the ability to understand and appreciate the emotions and demands expressed from the perspective of the user. However, some empathetic dialogue generation models only specialise in commonsense and neglect emotion, which can only get a one-sided understanding of the user's situation and makes the model unable to express emotion better. In this paper, we propose a novel affective feature knowledge interactive model named AFKI, to enhance response generation performance, which enriches conversation history to obtain emotional interactive context by leveraging fine-grained emotional features and commonsense knowledge. Furthermore, we utilise an emotional interactive context encoder to learn higher-level affective interaction information and distill the emotional state feature to guide the empathetic response generation. The emotional features are to well capture the subtle differences of the user's emotional expression, and the commonsense knowledge improves the representation of affective information on generated responses. Extensive experiments on the empathetic conversation task demonstrate that our model generates multiple responses with higher emotion accuracy and stronger empathetic ability compared with baseline model approaches for empathetic response generation. [ABSTRACT FROM AUTHOR]

AbstractThis column considers challenges and opportunities AI generative chatbots pose to proprietary library databases. It briefly reviews evolution from paper library indices to Web-based databases then reasons why current chatbots pose greater challenges to database relevancy than when Web engines first emerged. Library databases and free chatbots are compared in terms of identifying information needs, and locating, evaluating, and using information. Q/A with EBSCO are collected on challenges and opportunities chatbots provide them. Discussion centering around questions intended for database vendors ensues, along with a conclusion on potential information literacy benefits if library databases adopt chatbot search platforms. [ABSTRACT FROM AUTHOR]

Conversations between people are where, among other things, stressors are amplified and attenuated, conflicts are entrenched and resolved, and goals are advanced and thwarted. What happens in dyads' back-and-forth exchanges to produce such consequential and varied outcomes? Although numerous theories in communication and in social psychology address this question, empirical tests of these theories often operationalize conversational behavior using either discrete messages or overall features of the conversation. Dynamic systems theories and methods provide opportunities to examine the interdependency, self-stabilization, and self-organization processes that manifest in conversations over time. The dynamic dyadic systems perspective exemplified by the articles in this special issue (a) focuses inquiry on the turn-to-turn, asynchronous exchange of messages between two partners, (b) emphasizes behavioral patterns within and the structural and temporal organization of conversations, and (c) adapts techniques used in analysis of intensive longitudinal data to identify and operationalize those dynamic patterns. As an introduction to the special issue, this paper describes a dynamic dyadic systems perspective on conversation and discusses directions for future research, such as applications to human-computer interaction, family communication patterns, health care interventions, and group deliberation. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) poses new challenges and opportunities for hospitality and tourism (H&T) education. This study explores how ChatGPT, a chatbot powered by a generative pre-trained transformer model, can affect H&T curriculum design and delivery. Using secondary data from academic articles, news reports, and official documents, the paper applies curriculum theory and stakeholder theory to examine the competencies, expectations, and interests of H&T students, educators, and industry practitioners regarding ChatGPT. This study reveals that ChatGPT can enhance learning outcomes and experiences, improve educational equity and efficiency, and raise ethical, technical, and pedagogical issues for H&T education. This research note also offers insights and recommendations for H&T educators to integrate ChatGPT into their teaching practices and prepare students for research work and careers that incorporate generative AI. Moreover, the study contributes to the literature on H&T education by examining the role and impact of ChatGPT as an innovative and emerging technology. [ABSTRACT FROM AUTHOR]

AbstractThe paper aims to discuss ChatGPT and its role in academic libraries. It identifies the key areas where ChatGPT can be implemented in libraries to improve various services and the overall work experience of academics, along with the risk factors associated with ChatGPT. Research finds that ChatGPT can be aided with many library services such as collection development management, virtual reference services, digital information service and library discovery, research writing and publishing, research performance analysis and bibliometric services. It can be helpful for libraries to meet patron requirements, streamline the research process, and increase the efficiency of the library and staff. It reduces the workload of library staff to a certain extent rather than replacing the human librarians as various threats are associated with the ChatGPT, such as incorrect query responses, data protection, misuse, privacy, security, inaccessibility, limited technology comprehension and other ethical issues. It also discusses the limitations and challenges libraries may face while implementing the technology to impart various services. The importance of this study lies in the fact that it acknowledges the reality of ChatGPT and its limitations and how the library will be ready to cope with and deal with the technology in the future. [ABSTRACT FROM AUTHOR]

In today's time, the research mainly focuses on designing a Chat-bot which responds to a user's query in the most efficient manner. However, state-of-the-art works on chat-bot design are unable to emotionally connect with the user and follow-up to a conversation. In this paper, a socially and emotionally active intelligent assistant, AMIBO is proposed. It detects and recognizes the face, perceives emotion via speech and vision capabilities, provides empathetic and intelligent responses. In order to enhance the experience of AMIBO, navigation and information delivery system have been integrated in the bot. The analysis of the feature vector (on 450 subjects) is done for all the initially taken 75 distances and 15 angles reduced to 26 distances and 11 angles feature vector. An encouraging accuracy of 99% was achieved on CK+ dataset and 97% on KDEF dataset. [ABSTRACT FROM AUTHOR]

Analysing failure in innovation processes enhances a better understanding of success, as it might enlighten preconditions for the optimal implementation of initiatives, encompassing institutional logics, market conditions and contexts. This paper aims to identify the main non-successful innovations by Spanish news media over the last decade and to analyse their causes. It is based on interviews with 9 experts, who identified the early implementation of paywalls and chatbots as the most paradigmatic cases among a panel of 20 individuals. This work highlights the immaturity of markets, social contexts, and technological tools as obstacles, and argues that innovation requires a degree of trial and error. This study should be understood as a tentative approach to failure and its causes, which aims to encourage further empirical research. [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]

This paper presents a conversation strategy for interactive recommendations using a chatbot. Chatbots have recently been attracting attention for their use as a flexible user interface. To develop an effective chatbot, it is important to determine what kind of questions to ask, what information should be provided, and how to process a user's responses for a given task. In this paper, we target a chatbot that uses a graphical user interface (GUI) and focus on the task of recommending an item that suits a user's preference. We propose a conversation strategy where a chatbot combines questions about a user's preferences and recommendations while soliciting user's feedback to them. The balance between the questions and recommendations is controlled by changing the parameter values. In addition, we propose a simulation model to evaluate the performance of interactive recommendation under different parameter values. The simulation results with a prototype dataset are presented and discussed. [ABSTRACT FROM AUTHOR]

The introduction of the AI-powered chatbot ChatGPT by OpenAI has sparked much interest and debate among academic researchers. Commentators from different scientific disciplines have raised many concerns and issues, especially related to the ethics of using these tools in scientific writing and publications. In addition, there has been discussions about whether ChatGPT is trustworthy, effective, and useful in increasing researchers' productivity. Therefore, in this paper, we evaluate ChatGPT's performance on tasks related to bibliometric analysis, by comparing the output provided by the chatbot with a recently conducted bibliometric study on the same topic. The findings show that there are large discrepancies and ChatGPT's trustworthiness is low in this particular area. Therefore, researchers should exercise caution when using ChatGPT as a tool in bibliometric studies. [ABSTRACT FROM AUTHOR]

Chatbots' growing popularity has brought new challenges to HCI, having changed the patterns of human interactions with computers. The increasing need to approximate conversational interaction styles raises expectations for chatbots to present social behaviors that are habitual in human–human communication. In this survey, we argue that chatbots should be enriched with social characteristics that cohere with users' expectations, ultimately avoiding frustration and dissatisfaction. We bring together the literature on disembodied, text-based chatbots to derive a conceptual model of social characteristics for chatbots. We analyzed 56 papers from various domains to understand how social characteristics can benefit human–chatbot interactions and identify the challenges and strategies to designing them. Additionally, we discussed how characteristics may influence one another. Our results provide relevant opportunities to both researchers and designers to advance human–chatbot interactions. [ABSTRACT FROM AUTHOR]

Today, with the rapid advancement of technology, Artificial Intelligence (AI)-powered chatbots have become omnipresent across sectors like e-commerce, travel, hospitality, banking, EdTech, etc.; but they still haven't been predominantly adopted by academic libraries. This paper reports on a qualitative study aimed to explore the perceived risks and challenges behind the adoption of chatbots in libraries and how chatbots could help deliver superior experience to all library users as well as stakeholders. We conducted interviews with multiple stakeholders of academic libraries: the library staff, doctoral students and the faculty, to understand their perspectives on the adoption of Chatbots. We used CAQDAS NVIVO 12 content analysis software to analyse the interview transcripts. Our findings suggest that the majority of the stakeholders we interviewed favour the adoption of chatbots, as they believe that integrating chatbot technology with an existing library information system could deliver diverse services, which in turn would help in research and scholarly communication. However, 'perceived risk' with respect to employing chatbots among stakeholders was high. Also, the stakeholders raised some serious concerns with respect to privacy intrusion by chatbots, and with respect to chatbots' comprehension of task complexity, which are issues that must be addressed by chatbot developers while designing them, specifically for libraries. [ABSTRACT FROM AUTHOR]

Chatbots are virtual conversation agents that offer innovative features to connect with customers and thus offer a promising avenue to engage customers. Currently many private and nationalized banks are deploying chatbots for connecting and communicating with customers. This technology is expected to dominate the banking sector in the future by improving customer service. However, the success of banking chatbots will be effective when customers are satisfied with the chatbots and engage in using them. To probe in to the question, this study investigates the antecedents and consequences of customer brand engagement in using banking chatbots, with the lens of diffusion of innovation theory. The antecedents include interactivity, time convenience, compatibility, complexity, observability, and trialability. The consequences are satisfaction with the brand experience and customer brand usage intention. The theorized model has been validated with 470 Indian banking chatbot customers usable responses. The results suggest that trialability, compatibility, and interactivity positively influence customer brand engagement through a chatbot, thereby influencing satisfaction with the brand experience and customer brand usage intention. The paper presents theoretical and managerial implications which enable banks to strengthen customer engagement, satisfaction and brand usage intention through chatbots. [ABSTRACT FROM AUTHOR]

In this paper, I examine the historiographical capabilities of ChatGPT, a state-of-the-art artificial intelligence (AI) chatbot released on 30 November 2022, by OpenAI corporation. I begin by outlining a concise history of AI, highlighting the key innovations that have culminated in the development of advanced applications such as ChatGPT. Subsequently, I present an analysis of my interactions with the chatbot between February and May 2023, focusing on a long 'interview' conducted on the theory and methodology of historical science. My preliminary findings suggest that while ChatGPT holds significant potential for aiding historians in their research, the prospect of AI-driven history production remains distant and unlikely to materialize soon. [ABSTRACT FROM AUTHOR]

A library's website is the virtual front door for many of our users. Libraries offer online assistance in several ways, including a variety of options to request help. Live chat and email services are not new, but the recent development of chatbots provides opportunities to rethink and enhance online support. While some chatbots or virtual assistants generate automatic and custom responses to user input, this paper explores the implementation of a rules-based chatbot, where all responses have been input and configured by library staff. Details are provided to describe the process before, during, and after the initial implementation with data and observations from the pilot in mid-2023. [ABSTRACT FROM AUTHOR]

In this paper, we present a multimodal dialogue system combining a neural response generation mechanism, a reranking mechanism, and a rule-based avatar control mechanism. Our system was submitted to the open track at the Fifth Dialogue System Live Competition and won second place. Remarkably, our system received the best human evaluation performance for visual information control (i.e. speaking style of avatar) in the preliminary round. The assessment of the competition evaluators revealed that our system generates natural utterances appropriate to the conversational context and topic with an appealing speaking style. Through the analysis, we found that our devices, such as post-processing on speech recognition results and the final response selection method, are effective, but we also found room for improvement, such as speech recognition errors and challenges in the reranking module. [ABSTRACT FROM AUTHOR]

Copyright of Service Industries Journal is the property of Routledge and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, we look at a specific issue with practical Turing tests, namely the right of the machine to remain silent during interrogation. In particular, we consider the possibility of a machine passing the Turing test simply by not saying anything. We include a number of transcripts from practical Turing tests in which silence has actually occurred on the part of a hidden entity. Each of the transcripts considered here resulted in a judge being unable to make the ‘right identification’, i.e., they could not say for certain which hidden entity was the machine. [ABSTRACT FROM PUBLISHER]

This study explores the trends of chatbots in education studies by conducting a literature review to analyze relevant papers published in the Social Science Citation Index (SSCI) journals by searching the Web of Science (WoS) database. From the analysis results, it was found that the United States, Taiwan and Hong Kong are the top three contributing countries or regions. In addition, most studies adopted quantitative methods in their research design, such as ANOVA (Analysis of variance), descriptive statistics, t test, and correlation analysis. ANCOVA (Analysis of covariance) was the most frequently adopted approach for comparing the performances or perceptions of different groups of students. From the analysis results, the greatest proportion of studies adopted guided learning, followed by no learning activities. It was determined that the studies related to chatbots in education are still in an early stage since there are few empirical studies investigating the use of effective learning designs or learning strategies with chatbots. This implies much room for conducting relevant research to drive innovative teaching in terms of improving the learning process and learning outcomes. Finally, we highlight the research gaps and suggest several directions for future research based on the findings in the present study. [ABSTRACT FROM AUTHOR]

This document is a correction notice for a set of articles published in the journal Public Management Review. The articles were written for a special issue titled "Implementing AI in the Public Sector" and were mistakenly published in regular issues. The correction provides the correct order of the articles and updates the references in the introduction for clarity. The complete set of papers can be found on the journal's collection page. [Extracted from the article]

This document is a revised set of recommendations from the World Association of Medical Editors (WAME) regarding the use of chatbots and generative artificial intelligence (AI) in scholarly publications. The recommendations aim to inform editors, authors, and reviewers about the use of chatbots in papers and address concerns about authenticity, plagiarism, and biases in chatbot-generated content. The document emphasizes the need for transparency, proper attribution of sources, and the responsibility of authors and editors in ensuring the accuracy and integrity of chatbot-generated material. It also highlights the importance of providing editors with appropriate tools to detect AI-generated content. [Extracted from the article]

Firms are beginning to use chatbots to collect information from users (e.g., online reviews), a task traditionally done through forms. We used two experiments to investigate how collecting reviews using chatbots in place of forms might impact user experience and, in turn, alter the nature of the reviews submitted by users. Study 1 compares chatbots to web forms, finding that chatbots may improve perceived efficiency but otherwise have no discernible effect on satisfaction and usage intention. At the same time, chatbot usage results in shorter, lower-quality reviews. While structured templates enhance form-based reviews, introducing structure to chatbot interactions does not positively impact satisfaction and usage intent, potentially making the process less efficient. Nonetheless, a structured chatbot approach yields longer reviews and mitigates declines in quality. Adding structure to a chatbot takes the chat out of the chatbot, turning the interaction from casual conversation to a formal process, as demonstrated in Study 2. Hence, while this structured approach for chatbots improves review quality without harming satisfaction and usage intent, it may not be the most effective method for enhancing the reviewer experience. Our research shows that the chatbot and structure pulled users towards contradicting genre rules (the social structures that guide technology use) and triggered users to subconsciously enact distinctly different thought patterns as they composed reviews. [ABSTRACT FROM AUTHOR]

Introduction: People with disabilities or special needs can benefit from AI-based conversational agents (i.e., chatbots) that are used for competence training and well-being management. Assessing the quality of interactions with these chatbots is key to being able to reduce dissatisfaction with them and to understanding their potential long-term benefit. This in turn will help to increase adherence to their use, thereby improving the quality of life of the large population of end-users that they are able to serve. Methods: Following Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) methodology, we systematically reviewed the literature on methods of assessing the perceived quality of interactions with chatbots using the from Scopus and the Web of Science electronic databases. Using the Boolean operators (AND/OR) the keywords chatbot*, conversational agent*, special needs, disability were combined. Results: Revealed that only 15 of 192 papers on this topic included people with disabilities or special needs in their assessments. The results also highlighted the lack of a shared theoretical framework for assessing the perceived quality of interactions with chatbots. Conclusion: Systematic procedures based on reliable and valid methodologies continue to be needed in this field. The current lack of reliable tools and systematic methods to assess chatbots for people with disabilities and special needs is concerning, and ultimately, it may also lead to unreliable systems entering the market with disruptive consequences for people. Chatbots applied in rehabilitation are mainly tested in terms of clinical effectiveness and validity with a minimal focus on measuring the quality of the interaction The usability and interactive properties of chatbots applied in rehabilitation are not comparable as each tool is measured in different way The lack of a common framework to assess chatbots exposes people with disability and special needs to the risk of using unreliable tools [ABSTRACT FROM AUTHOR]

Chatbots and other artificial-intelligence applications that mimic human conversation or writing have rapidly become some of the most popular tech applications of all time. Expert analysis and media coverage of the risks and benefits of AI have paid scant attention to how chatbots might affect public health at a time when depression, suicide, anxiety, and mental illness are epidemic in the United States, particularly among children and young adults. Many experts have pointed to a correlation between declining mental health and increasing online engagement. Generative AI's potential to transform education, the job market, and social interactions could come at the expense of humanity's own mental faculties, creativity, and social skills. Chatbots—which are prone to errors and fabrications—could also make it more difficult for humans to tell fact from fiction. But to the extent that mental health experts and the healthcare industry are interested in AI, it's mostly viewed as a promising tool for identifying and treating mental health issues, rather than a potential threat to mental health. [ABSTRACT FROM AUTHOR]

Since ChatGPT's release in November 2022, artificial intelligence has come into the spotlight. Inspiring both fascination and fear, chatbots have stirred debates among researchers, developers, and policy makers. The concerns range from concrete and tangible ones—which include replication of existing biases and discrimination at scale, harvesting personal data, and spreading misinformation—to more existential fears that their development will lead to machines with human-like cognitive abilities. Understanding how chatbots work and the human labor and data involved can better help evaluate the validity of concerns surrounding these systems, which although innovative, are hardly the stuff of science fiction. [ABSTRACT FROM AUTHOR]

ChatGPT has revolutionized the travel industry. This study employs the stimulus-organism-response (SOR) model to develop and validate a conceptual model for ChatGPT acceptance. Social influence and perceived value emerge as key determinants of user cognitive appraisals of ChatGPT's expertise, trustworthiness, and emotional connections through parasocial interaction. These factors subsequently influence traveler acceptance of ChatGPT for travel-related services. Findings reveal that social influence is the most potent predictor of ChatGPT acceptance, while perceived trust directly impacts user acceptance during the cognitive process. These insights advance research on parasocial interaction, while providing valuable guidance for implementing ChatGPT in tourism services. [ABSTRACT FROM AUTHOR]

This paper presents some important issues on misidentification of human interlocutors in text-based communication during practical Turing tests. The study here presents transcripts in which human judges succumbed totheconfederate effect, misidentifying hidden human foils for machines. An attempt is made to assess the reasons for this. The practical Turing tests in question were held on 23 June 2012 at Bletchley Park, England. A selection of actual full transcripts from the tests is shown and an analysis is given in each case. As a result of these tests, conclusions are drawn with regard to the sort of strategies which can perhaps lead to erroneous conclusions when one is involved as an interrogator. Such results also serve to indicate conversational directions to avoid for those machine designers who wish to create a conversational entity that performs well on the Turing test. [ABSTRACT FROM AUTHOR]

Background: Utilizing artificial intelligence (AI) in chatbots, especially for chronic diseases, has become increasingly prevalent. These AI-powered chatbots serve as crucial tools for enhancing patient communication, addressing the rising prevalence of chronic conditions, and meeting the growing demand for supportive healthcare applications. However, there is a notable gap in comprehensive reviews evaluating the impact of AI-powered chatbot interventions in healthcare within academic literature. This study aimed to assess user satisfaction, intervention efficacy, and the specific characteristics and AI architectures of chatbot systems designed for chronic diseases. Method: A thorough exploration of the existing literature was undertaken by employing diverse databases such as PubMed MEDLINE, CINAHL, EMBASE, PsycINFO, AC M Digital Library and Scopus. The studies incorporated in this analysis encompassed primary research that employed chatbots or other forms of AI architecture in the context of preventing, treating or rehabilitating chronic diseases. The assessment of bias risk was conducted using Risk of 2.0 Tools. Results: Seven hundred and eighty-four results were obtained, and subsequently, eight studies were found to align with the inclusion criteria. The intervention methods encompassed health education (n = 3), behaviour change theory (n = 1), stress and coping (n = 1), cognitive behavioural therapy (n = 2) and self-care behaviour (n = 1). The research provided valuable insights into the effectiveness and user-friendliness of AI-powered chatbots in handling various chronic conditions. Overall, users showed favourable acceptance of these chatbots for self-managing chronic illnesses. Conclusions: The reviewed studies suggest promising acceptance of AI-powered chatbots for self-managing chronic conditions. However, limited evidence on their efficacy due to insufficient technical documentation calls for future studies to provide detailed descriptions and prioritize patient safety. These chatbots employ natural language processing and multimodal interaction. Subsequent research should focus on evidence-based evaluations, facilitating comparisons across diverse chronic health conditions. [ABSTRACT FROM AUTHOR]

Chatbots are increasingly able to talk as humans. Disclosing the identity of chatbots can negatively impact the user trust, but withholding is considered illegal. Disclosing is an inevitable trend, and it is crucial to study different disclosure types. However, most research focuses on comparing disclosure versus non-disclosure. This article investigates the impact of interaction between disclosing and service contact types on service satisfaction. Specifically, pre-dialogue (vs. post-dialogue) disclosure appears more satisfying for high-contact services, whereas post-dialogue disclosure is better suited to low-contact services. Trust is the mediating mechanism of these effects. These findings can help service providers devise marketing strategies. [ABSTRACT FROM AUTHOR]

Various research and development efforts are currently underway to address these new challenges, including "dialogue robot competition" at IROS 2022 and "dialogue system live competition". In recent years, as seen in smart speakers such as Google Home and Amazon Alexa, there has been remarkable progress in spoken dialogue systems technology to converse with users with human-like utterances. The second paper 'Building a hospitable and reliable dialogue system for android robots: a scenario-based approach with large language models' introduces a dialogue system that seamlessly integrates a scenario-based approach with a powerful large language model. [Extracted from the article]

In this article we consider transcripts that originated from a practical series of Turing's Imitation Game that was held on 6 and 7 June 2014 at the Royal Society London. In all cases the tests involved a three-participant simultaneous comparison by an interrogator of two hidden entities, one being a human and the other a machine. Each of the transcripts considered here resulted in a human interrogator being fooled such that they could not make the ‘right identification’, that is, they could not say for certain which was the machine and which was the human. The transcripts presented all involve one machine only, namely ‘Eugene Goostman’, the result being that the machine became the first to pass the Turing test, as set out by Alan Turing, on unrestricted conversation. This is the first time that results from the Royal Society tests have been disclosed and discussed in a paper. [ABSTRACT FROM PUBLISHER]

Driven by the need to provide continuous, timely, and efficient customer service, firms are constantly experimenting with emerging technological solutions. In recent times firms have shown an increased interest in designing and implementing artificial intelligence (AI)-based interactional technologies, such as conversational AI agents and chatbots, that obviate the need for having human service agents for the provision of customer service. However, the business impact of conversational AI is contingent on customers using and adequately engaging with these tools. This engagement depends, in turn, on conversational AI's similarity, or likeness to the human beings it is intended to replace. Businesses therefore need to understand what human-like characteristics and competencies should be embedded in customer-facing conversational AI agents to facilitate smooth user interaction. This focus on "human-likeness" for facilitating user engagement in the case of conversational AI agents is in sharp contrast to most prior information systems (IS) user engagement research, which is predicated on the "instrumental value" of information technology (IT). Grounding our work in the individual human competency and media naturalness literatures, we theorize the key role of human-like interactional competencies in conversational AI agents—specifically, cognitive, relational, and emotional competencies—in facilitating user engagement. We also hypothesize the mediating role of user trust in these relationships. Following a sequential mixed methods approach, we use a quantitative two-wave, survey-based study to test our model. We then examine the results in light of findings from qualitative follow-up interviews with a sampled set of conversational AI users. Together, the results offer a nuanced understanding of desirable human-like competencies in conversational AI agents and the salient role of user trust in fostering user engagement with them. We also discuss the implications of our study for research and practice. [ABSTRACT FROM AUTHOR]

Around the recent turn of the millennium, one of the most promising discourses in performance studies seemed to be about the performative dimension of the chatterbot-what might also be termed its transdimensional potential. A chatterbot is a computer program which simulates human response by words typed and viewed on a computer screen and exhibits symptoms of human cognition. The stimulating chance to contemplate ‘embodied’ vs. ‘disembodied’ performance in the light of new media and to question performance as a solely human activity has been rather neglected, however, as we unquestioningly embrace entertaining internet applications. The paper aims to critically analyse the performativity of chatterbot in relation to key theories of performance theory and to introduce the reader to the transdimensional performance potential of the human-chatterbot conversation by exploring strategies such as bringing chatterbot-generated content on the stage. [ABSTRACT FROM AUTHOR]