Chatbots – changing user needs and motivations.

International Journal of Human–Computer Interaction

The growing popularity of chatbots has brought new needs for HCI since it has changed the patterns of human interactions with computers. The conversational aspect of the interaction increases the necessity for chatbots to present social behaviors that are habitual in human-human conversations. In this survey, we argue that chatbots should be enriched with social characteristics that are coherent 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 58 papers from various domains to understand how social characteristics can benefit the 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.

2021

The widespread use of chatbots is a reality and their application in higher education is promising. Understanding higher education users' expectations for the use of chatbots in education is important for the design and development of new solutions. The present investigation documents how higher education users envision the pedagogical uses of chatbots in higher education, and how experts in the domain of education chatbots perceive the potential benefits and challenges related to the use of chatbots in education. A qualitative inquiry was undertaken based on 22 semi-structured interviews with higher-education students and instructors, and experts from the fields of Artificial Intelligence and educational chatbots. Based on our findings, the envisioned pedagogical uses of chatbots can be categorized in terms of chronological integration into the learning process: prospective, ongoing , and retrospective. Under each one of those higher-order categories, specific learning domains can be supported (i.e., cognitive, affective), besides administrative tasks. Benefits and challenges foreseen in the use of pedagogical chatbots are presented and discussed. The findings of this study highlight the manner in which higher-education users envision the use of chatbots in education, with potential implications on the creation of specific pedagogical scenarios, accounting also for the learning context, chatbot technology, and pedagogies that are deemed appropriate in each scenario.

Education Sciences, 2020

This research involved the design of a task-based dialogue system and evaluation of its learning effectiveness. Dialogue training still heavily depends on human communication with instant feedback or correction. However, it is not possible to provide a personal tutor for every English learner. With the rapid development of information technology, digitized learning and voice communication is a possible solution. The goal of this research was to develop an innovative model to refine the task-based dialogue system, including natural language understanding, disassembly intention, and dialogue state tracking. To enable the dialogue system to find the corresponding sentence accurately, the dialogue system was designed with machine learning algorithms to allow users to communicate in a task-based fashion. Past research has pointed out that computer-assisted instruction has achieved remarkable results in language reading, writing, and listening. Therefore, the direction of the discussion i...

Harvard Kennedy School Misinformation Review, 2021

Our study examines Facebook posts containing nine prominent COVID-19 vaccine misinformation topics that circulated on the platform between March 1st, 2020 and March 1st, 2021. We first identify misinformation spreaders and fact checkers, further dividing the latter group into those who repeat misinformation to debunk the false claim and those who share correct information without repeating the misinformation. Our analysis shows that, on Facebook, there are almost as many fact checkers as misinformation spreaders. In particular, fact checkers’ posts that repeat the original misinformation received significantly more comments than posts from misinformation spreaders. However, we found that misinformation spreaders were far more likely to take on central positions in the misinformation URL co-sharing network than fact checkers. This demonstrates the remarkable ability of misinformation spreaders to coordinate communication strategies across topics.

Quality and User Experience, 2020

For chatbots to be broadly adopted by users, it is critical that they are experienced as useful and pleasurable. While there is an emerging body of research concerning user uptake and use of chatbots, there is a lack of theoretically grounded studies detailing what constitutes good or poor chatbot user experiences. In this paper, we present findings from a questionnaire study involving more than 200 chatbot users who reported on episodes of chatbot use that they found particularly satisfactory or frustrating. The user reports were analysed with basis in theory on user experience, with particular concern for pragmatic and hedonic attributes. We found that pragmatic attributes such as efficient assistance (positive) and problems with interpretation (negative) were important elements in user reports of satisfactory and frustrating episodes. Hedonic attributes such as entertainment value (positive) and strange and rude responses (negative) were also frequently mentioned. Older participa...

Information, Communication & Society, 2019

As smart technologies such as artificial intelligence (AI), automation and Internet of Things (IoT) are increasingly embedded into commercial and government services, we are faced with new challenges in digital inclusion to ensure that existing inequalities are not reinforced and new gaps that are created can be addressed. Digital exclusion is often compounded by existing social disadvantage, and new systems run the risk of creating new barriers and harms. Adopting a case study approach, this paper examines the exclusionary practices embedded in the design and implementation of social welfare services in Australia. We examined Centrelink's automated Online Compliance Intervention system ('Robodebt') and the National Disability Insurance Agency's intelligent avatar interface 'Nadia'. The two cases show how the introduction of automated systems can reinforce the punitive policies of an existing service regime at the design stage and how innovative AI systems that have the potential to enhance user participation and inclusion can be hindered at implementation so that digital benefits are left unrealised.

Computer Supported Cooperative Work (CSCW)

Organizations’ hiring processes are increasingly shaped by various digital tools and e-recruitment systems. However, there is little understanding of the recruiters’ needs for and expectations towards new systems. This paper investigates recruitment chatbots as an emergent form of e-recruitment, offering a low-threshold channel for recruiter-applicant interaction. The rapid spread of chatbots and the casual nature of their user interfaces raise questions about the perceived benefits, risks, and suitable roles in this sensitive application area. To this end, we conducted 13 semi-structured interviews, including 11 interviews with people who are utilizing recruitment chatbots and two people from companies that are developing recruitment chatbots. The findings provide a qualitative account of their expectations and motivations, early experiences, and perceived opportunities regarding the current and future use of chatbots in recruitment. While chatbots answer the need for attracting ne...

Education and Information Technologies

Chatbots hold the promise of revolutionizing education by engaging learners, personalizing learning activities, supporting educators, and developing deep insight into learners’ behavior. However, there is a lack of studies that analyze the recent evidence-based chatbot-learner interaction design techniques applied in education. This study presents a systematic review of 36 papers to understand, compare, and reflect on recent attempts to utilize chatbots in education using seven dimensions: educational field, platform, design principles, the role of chatbots, interaction styles, evidence, and limitations. The results show that the chatbots were mainly designed on a web platform to teach computer science, language, general education, and a few other fields such as engineering and mathematics. Further, more than half of the chatbots were used as teaching agents, while more than a third were peer agents. Most of the chatbots used a predetermined conversational path, and more than a quar...

Asian CHI Symposium 2021, 2021

Advances in conversational interfaces have facilitated the widespread use of chatbots in assisting humans in their daily lives such as in retail services, healthcare, and education. With the use of Natural Language Processing techniques (NLP), chatbots can leverage on storytelling strategies to engage children in meaningful conversations to narrate and share their stories. In this paper, we compared two existing conversational storytelling agents, Orsen and EREN, by analyzing the dialog logs to examine children's engagement when sharing their stories with these agents. Taking three dimensions-language production, flow maintenance, and affect; into consideration, results show that the ability of EREN to recognize emotions expressed in the child's input text can encourage the children to be more open to sharing their stories. Even though the agent cannot generate affect-rich responses, its ability to recognize the emotions made children feel thankful and appreciative of the agent for listening. CCS CONCEPTS • Human-centered computing → Collaborative and social computing.

Information, 2020

In this study, we examined the activities of automated social media accounts or bots that tweet or retweet referencing #COVID-19 and #COVID19. From a total sample of over 50 million tweets, we used a mixed method to extract more than 185,000 messages posted by 127 bots. Our findings show that the majority of these bots tweet, retweet and mention mainstream media outlets, promote health protection and telemedicine, and disseminate breaking news on the number of casualties and deaths caused by COVID-19. We argue that some of these bots are motivated by financial incentives, while other bots actively support the survivalist movement by emphasizing the need to prepare for the pandemic and learn survival skills. We only found a few bots that showed some suspicious activity probably due to the fact that our dataset was limited to two hashtags often used by official health bodies and academic communities.

CHI Conference on Human Factors in Computing Systems

Applied Sciences, 2021

Despite recent Artificial Intelligence (AI) advances in narrow task areas such as face recognition and natural language processing, the emergence of general machine intelligence continues to be elusive. Such an AI must overcome several challenges, one of which is the ability to be aware of, and appropriately handle, context. In this article, we argue that context needs to be rigorously treated as a first-class citizen in AI research and discourse for achieving true general machine intelligence. Unfortunately, context is only loosely defined, if at all, within AI research. This article aims to synthesize the myriad pragmatic ways in which context has been used, or implicitly assumed, as a core concept in multiple AI sub-areas, such as representation learning and commonsense reasoning. While not all definitions are equivalent, we systematically identify a set of seven features associated with context in these sub-areas. We argue that such features are necessary for a sufficiently rich...

Lecture Notes in Computer Science, 2023

Organizations are increasingly implementing chatbots to address customers' inquiries, but customers still have unsatisfactory encounters with them. In order to successfully deploy customer service chatbots, it is important for organizations and designers to understand how to best introduce them to customers. Arguably, how a chatbot introduces itself as well as its services might influence customers' perceptions about the chatbot. Therefore, a framework was developed to annotate the social cues in chatbot introductions. In order to validate our framework, we conducted a content analysis of introductions of customer service chatbots (n = 89). The results showed that the framework turned out to be a reliable identification instrument. Moreover, the most prevalent social cue in chatbot introductions was a humanlike avatar, whereas communication cues, indicating the chatbot's functionalities, hardly occurred. The paper ends with implications for the design of chatbot introductions and possibilities for future research.

Electronic Markets

Chatbots as prominent form of conversational agents are increasingly implemented as a user interface for digital customer-firm interactions on digital platforms and electronic markets, but they often fail to deliver suitable responses to user requests. In turn, individuals are left dissatisfied and turn away from chatbots, which harms successful chatbot implementation and ultimately firm’s service performance. Based on the stereotype content model, this paper explores the impact of two universally usable failure recovery messages as a strategy to preserve users’ post-recovery satisfaction and chatbot re-use intentions. Results of three experiments show that chatbot recovery messages have a positive effect on recovery responses, mediated by different elicited social cognitions. In particular, a solution-oriented message elicits stronger competence evaluations, whereas an empathy-seeking message leads to stronger warmth evaluations. The preference for one of these message types over t...

Behaviour & Information Technology, 2020

Digital personal assistants (DPAs) have recently grown in popularity because they are both a commercially available new technology and reasonably affordable to the average household. This opens opportunities for new ways to assist people in everyday activities in their homes through voice-interaction. Physical activity has significant health benefits, and yet globally, 1 in 4 adults are not active enough. To address this, we investigate the persuasive potential of DPAs in increasing people's physical activity at home. We conducted a study with 48 participants to understand the effect of applying three of Fogg's persuasive principles to the design of a DPA exercise programme: Suggestion, Virtual Reward, and Praise. Our findings show that DPAs have the potential, within their current technical and reactive capabilities, to persuade people to increase their physical activity at home, using Suggestion to encourage physical effort, Virtual Reward to encourage endurance, and Praise to create reassurance for beginners. Based on this, we offer three alternate perspectives for developing persuasive DPAs. We also discuss limitations of the study and suggest future research directions around using persuasion with DPAs.

Applied Computing and Informatics

PurposeThis research work aims to arise from developing new communication channels for customer service in micro, small and medium enterprises (MSMEs), such as chatbots. In particular, the results of the usability testing of three chatbots implemented in MSMEs are presented.Design/methodology/approachThe methodology employed includes participants, chatbot development platform, research methodology, software development methodology and usability test to contextualize the study's results.FindingsBased on the results obtained from the System Usability Scale (SUS) and considering the accuracy of the chatbot's responses, it is concluded that the level of satisfaction in using chatbots is high; therefore, if the chatbot is well integrated with the communication systems/channels of the MSMEs, the client receives an excellent, fast and efficient service.Originality/valueThe paper analyzes chatbots for customer service and presents the usability testing results of three chatbots impl...

JMIR Human Factors

Background Chatbots are computer programs that present a conversation-like interface through which people can access information and services. The COVID-19 pandemic has driven a substantial increase in the use of chatbots to support and complement traditional health care systems. However, despite the uptake in their use, evidence to support the development and deployment of chatbots in public health remains limited. Recent reviews have focused on the use of chatbots during the COVID-19 pandemic and the use of conversational agents in health care more generally. This paper complements this research and addresses a gap in the literature by assessing the breadth and scope of research evidence for the use of chatbots across the domain of public health. Objective This scoping review had 3 main objectives: (1) to identify the application domains in public health in which there is the most evidence for the development and use of chatbots; (2) to identify the types of chatbots that are bein...

Electronics

Artificial intelligence (AI) conversational agents (CA) or chatbots represent one of the technologies that can provide automated customer service for companies, a trend encountered in recent years. Chatbot use is beneficial for companies when associated with positive customer experience. The purpose of this paper is to analyze the overall customer experience with customer service chatbots in order to identify the main influencing factors for customer experience with customer service chatbots and to identify the resulting dimensions of customer experience (such as perceptions/attitudes and feelings and also responses and behaviors). The analysis uses the systematic literature review (SLR) method and includes a sample of 40 publications that present empirical studies. The results illustrate that the main influencing factors of customer experience with chatbots are grouped in three categories: chatbot-related, customer-related, and context-related factors, where the chatbot-related fac...

SHS Web of Conferences, 2021

Research background: The first notable early chatbots were created in the sixties, but the growing use of artificial intelligence (AI) has powered them significantly. Studies show that basically chatbots are created and used for purposes by government and business, mostly in consumer service and marketing. The new Proposal of the Artificial intelligence act aims to promote the uptake of AI and address the risks associated with certain uses of such technology. However, the act contains only minimum transparency obligation for some specific AL systems such as chatbots. Purpose of the article: In light of this issue, the article aims to discuss how existing European Union (EU) consumer law is equipped to deal with situations in which the use of chatbots can pose the risks of manipulation, aggressive commercial practices, intrusion into privacy, exploitation of a consumer’s vulnerabilities and algorithmic decision making based on biased or discriminatory results. Methods: The article wi...