Chatbots are increasingly becoming important gateways to digital services and information—taken up within domains such as customer service, health, education, and work support. However, there is only limited knowledge concerning the impact of chatbots at the individual, group, and societal level. Furthermore, a number of challenges remain to be resolved before the potential of chatbots can be fully realized. In response, chatbots have emerged as a substantial research area in recent years. To help advance knowledge in this emerging research area, we propose a research agenda in the form of future directions and challenges to be addressed by chatbot research. This proposal consolidates years of discussions at the CONVERSATIONS workshop series on chatbot research. Following a deliberative research analysis process among the workshop participants, we explore future directions within six topics of interest: (a) users and implications, (b) user experience and design, (c) frameworks and platforms, (d) chatbots for collaboration, (e) democratizing chatbots, and (f) ethics and privacy. For each of these topics, we provide a brief overview of the state of the art, discuss key research challenges, and suggest promising directions for future research. The six topics are detailed with a 5-year perspective in mind and are to be considered items of an interdisciplinary research agenda produced collaboratively by avid researchers in the field.

Chatbots are increasingly used in a commercial context to make product- or service-related recommendations. By doing so, they collect personal information of the user, similar to other online services. While privacy concerns in an online (website-) context are widely studied, research in the context of chatbot-interaction is lacking. This study investigates the extent to which chatbots with human-like cues influence perceptions of anthropomorphism (i.e., attribution of human like characteristics), privacy concerns, and consequently, information disclosure, attitudes and recommendation adherence. Findings show that a human-like chatbot leads to more information disclosure, and recommendation adherence mediated by higher perceived anthropomorphism and subsequently, lower privacy concerns in comparison to a machine-like chatbot. This result does not hold in comparison to a website; human-like chatbot and website were perceived as equally high in anthropomorphism. The results show the importance of both mediating concepts in regards to attitudinal and behavioral outcomes when interacting with chatbots.

Chatbots are increasingly used in a commercial context to make product-or service-related recommendations. By doing so, they collect personal information of the user, similar to other online services. While privacy concerns in an online (website-) context are widely studied, research in the context of chatbot-interaction is lacking. This study investigates the extent to which chatbots with human-like cues influence perceptions of anthropomorphism (i.e., attribution of human-like characteristics), privacy concerns, and consequently, information disclosure, attitudes and recommendation adherence. Findings show that a human-like chatbot leads to more information disclosure, and recommendation adherence mediated by higher perceived anthropomorphism and subsequently, lower privacy concerns in comparison to a machine-like chatbot. This result does not hold in comparison to a website; human-like chatbot and website were perceived as equally high in anthropomorphism. The results show the importance of both mediating concepts in regards to attitudinal and behavioral outcomes when interacting with chatbots.

Online users are increasingly exposed to chatbots as one form of AI-enabled media technologies, employed for persuasive purposes, e.g., making product/service recommendations. However, the persuasive potential of chatbots has not yet been fully explored. Using an online experiment (N = 242), we investigate the extent to which communicating with a stand-alone chatbot influences affective and behavioral responses compared to interactive Web sites. Several underlying mechanisms are studied, showing that enjoyment is the key mechanism explaining the positive effect of chatbots (vs. Web sites) on recommendation adherence and attitudes. Contrary to expectations, perceived anthropomorphism seems not to be particularly relevant in this comparison.The communication between online users and organizations is increasingly shifting toward interactions with technology driven by artificial intelligence (AI; Sundar, 2020). Among the most prevalent instances of technology with which users are confronted are AI-based chatbots. Defined as "software that accepts natural language as input and generates natural language as output, engaging in a conversation" (Griol et al., 2013, p. 706), chatbots can be found on social media (e.g., Facebook, Twitter) and messaging apps (e.g., Skype, Facebook Messenger); they can be an alternative to (branded) Web sites (e.g., A.s.r., 2019). These stand-alone chatbots are often used for making product or service recommendations (e.g., shopping, financial/health-related CONTACT Carolin Ischen

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