Volume 22, Issue 1 - Special Issue: Conversational Agents; Guest Editors: Thomas Ludwig, Philip Weber, Alexander Maedche and Andreas Riener

3D printers are no longer found only in industry, universities or makerspaces but now are increasingly used in domestic settings. Personal fabrication will increase in the coming years, and 3D printing will play an important role in this process. Due to technology and price development, 3D printers are becoming established among casual users at home. However, there are still many hurdles in the use of 3D printers that interfere with their appropriation in everyday life. In this paper, we investigate how chatbots can overcome these hurdles and support onboarding to 3D printing. Furthermore, we explore how chatbots can be used as a human–machine interface and facilitate interaction with 3D printers for both novice and expert users. In a research-through-design approach, we have created a fully functional chatbot that introduces users to 3D printing and helps them perform typical tasks when operating 3D printers.

We present a conversational social robot behaviour design that draws from psychotherapy research to support individual self-reflection and wellbeing, without requiring the robot to parse or otherwise understand what the user is saying. This simplicity focused approached enabled us to intersect the well-being aims with privacy and simplicity, while achieving high robustness. We implemented a fully autonomous and standalone (not network enabled) prototype and conducted a proof-of-concept study as an initial step to test the feasibility of our behaviour design: whether people would successfully engage with our simple behaviour and could interact meaningfully with it. We deployed our robot unsupervised for 48 h into the homes of 14 participants. All participants engaged with self-reflection with the robot without reporting any interaction challenges or technical issues. This supports the feasibility of our specific behaviour design, as well as the general viability of our non-parsing simplicity approach to conversation, which we believe to be an exciting avenue for further exploration. Our results thus pave the way for further exploring how conversational behaviour designs like ours may support people living with loneliness.

In recent years, emerging approaches to chatbot-guided food coaching and dietary management, while innovative and promising in nature, have often lacked long-term studies. Therefore, with this work, we pursued a participatory approach within a design case study to the co-design and development of a nutrition chatbot for elderly people. Overall, 15 participants were directly involved in the study, of which 12 participated in the initial co-design phase, seven in the first real-world evaluation study over four weeks, and three in the second evaluation study over seven weeks. We contribute to the fields of Human-Computer Interaction by showing how the long-term use of such a chatbot in the area of nutrition looks like, which design implications arise for the development of nutrition chatbots, and how a participatory design approach can be realized to design, evaluate and develop nutrition chatbots.

New work has been a topic for a few years now and the COVID-19 pandemic has brought this trend more into focus, i.e., working remotely became more popular. However, besides various advantages, there is the risk of loneliness in employees, which can negatively affect their work performance and mental health. Research in different domains suggests that social robots could reduce loneliness. Since we were interested in whether and how such findings are transferable to the office context, we developed and tested a concept for a social office robot. More specifically, we first conducted a cultural probes study with white-collar workers to gain information about workplace loneliness and its drivers. Second, we explored design possibilities for a social office robot in a focus group. Based on the results, we created a concrete concept, Luca, which we finally evaluated and optimized with the help of interviews with participants from various industries. The present work contributes to HRI research and practice, e.g., by providing design recommendations for the implementation of a social office robot. Future research could investigate the effectiveness of a social office robot intervention in field studies. Next to implications for research and practice, potential limitations are discussed.

With the increasing proliferation of security-critical voice-based services such as voice banking, user authentication on smart speakers is becoming a vital requirement. Prior research on verifying the speaker’s identity has been taken a technical perspective predominantly, while respective user-centered research is scarce. To investigate authentication methods for smart speakers from a user’s perspective, we conducted a multi-method experiment. In a comprehensive online survey ( n = 696) and a comparative lab study ( n = 18) with an advanced functional prototype we studied 6 authentication methods (spoken PIN, biometrics, app with button/voice confirmation, card reader, sound authentication) regarding their perceived security and ease of use. While token-based authentication approaches (in particular an authenticator app on a smartphone) typically are perceived as more secure, they are found inferior when it comes to the ease of use. The currently most frequently used authentication method for smart speakers, the spoken PIN method, seems to represent a compromise between security and ease of use. The sophisticated sound authentication was appreciated for its ease of use, however, was rated worst regarding the perceived security.

Voice assistants have become embedded in people’s private spaces and domestic lives where they gather enormous amounts of personal information which is why they evoke serious privacy concerns. The paper reports the findings from a mixed-method study with 65 digital natives, their attitudes to privacy and actual and intended behaviour in privacy-sensitive situations and contexts. It also presents their recommendations to governments or organisations with regard to protecting their data. The results show that the majority are concerned about privacy but are willing to disclose personal data if the benefits outweigh the risks. The prevailing attitude is one characterised by uncertainty about what happens with their data, powerlessness about controlling their use, mistrust in big tech companies and uneasiness about the lack of transparency. Few take steps to self-manage their privacy, but rely on the government to take measures at the political and regulatory level. The respondents, however, show scant awareness of existing or planned legislation such as the GDPR and the Digital Services Act, respectively. A few participants are anxious to defend the analogue world and limit digitalization in general which in their opinion only opens the gate to surveillance and misuse.