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Intelligent personal assistants (IPAs), also known as smart speakers, are becoming part of everyday life in more and more households around the world. Phone and household IPAs are integrated in intimate home contexts and require connections to (social) media profiles, user accounts, and domestic appliances. Users can control their household with voice-activated commands in order to make life more convenient and efficient. Yet, IPAs also bring privacy and surveillance concerns about devices "listening in," the "platformization" of home life, and data security. Our exploratory mixed-methods study provides an in-depth and multidimensional account of users' privacy concerns around the emergence of IPAs in Dutch households. We differentiate between surveillance, security, and platform concerns, and our survey results indicate by which factors these are influenced. The focus group analysis highlights the role of conversation, recordability, locatability, control-ability, and assistance affordances. Our findings present a multidimensional and nuanced understanding of privacy concerns around household IPAs. We indicate how smart home technologies raise concerns about privacy, surveillance, device security, everyday behavior, and platform transparency, topics that demand urgent attention before the integration of IPAs will be fully normalized. [ABSTRACT FROM AUTHOR]

This paper reports the findings from an empirical study investigating the effectiveness of using intelligent voice assistants, Amazon Alexa in our case, to deliver a phishing training to users. Because intelligent voice assistants can hardly utilize visual cues but provide for convenient interaction with users, we developed an interaction-based phishing training focused on the principles of persuasion with examples on how to look for them in phishing emails. To test the effectiveness of this training, we conducted a between-subject study where 120 participants were randomly assigned in three groups: no training, interaction-based training with Alexa, and a facts-and-advice training and assessed a vignette of 28 emails. The results show that the participants in the interaction-based group statistically outperformed the others when detecting phishing emails that employed the following persuasion principles (and/or combinations of): authority, authority/scarcity, commitment, commitment/liking, and scarcity/liking. The paper discusses the implication of this result for future phishing training and anti-phishing efforts. [ABSTRACT FROM AUTHOR]

The increase in irrigated crop areas, especially in countries such as Spain and Italy, has led to an increase in technological solutions for monitoring the irrigation. Furthermore, the centre pivot irrigation systems used in these crops have facilitated the daily work of farmers in recent years, however, the monitoring of these systems and the reporting of problems in their operation has become a key aspect during the growing season. For this reason, different monitoring solutions have been proposed from the area of Precision Agriculture and Information and Communication Technologies (ICTs). Nevertheless, it is necessary that these solutions take into account the digital divide their potential users may suffer and be low-cost solutions in order to be attractive to the end-users. This paper presents several low-cost solutions using novel user interfaces and wireless communication technologies for the monitoring of this type of irrigation systems. This paper presents the results obtained after the deployment of the proposed systems on a real environment and the main conclusions drawn after their use in irrigated maize crops. • LoRaWAN and GPS allow affordable monitoring systems for centre pivot irrigation. • Chatbots and voice assistants help to avoid the digital divide. • Edge Computing Devices and LPWANs enable new AMR solutions for water meters. [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]

'Anthropomorphism' is a popular term in the literature on human-technology engagements, in general, and child-technology engagements, in particular. But what does it really mean to 'anthropomorphize' something in today's world? This conceptual review article, addressed to researchers interested in anthropomorphism and adjacent areas, reviews contemporary anthropomorphism research, and it offers a critical perspective on how anthropomorphism research relates to today's children who grow up amid increasingly intelligent and omnipresent technologies, particularly digital voice assistants (e.g., Alexa, Google Assistant, Siri). First, the article reviews a comprehensive body of quantitative as well as qualitative anthropomorphism research and considers it within three different research perspectives: descriptive, normative and explanatory. Following a brief excursus on philosophical pragmatism, the article then discusses each research perspective from a pragmatistic viewpoint, with a special emphasis on child-technology and child-voice-assistant engagements, and it also challenges some popular notions in the literature. These notions include descriptive 'as if' parallels (e.g., child behaves 'as if' Alexa was a friend), or normative assumptions that human-human engagements are generally superior to human-technology engagements. Instead, the article reviews different examples from the literature suggesting the nature of anthropomorphism may change as humans' experiential understandings of humanness change, and this may particularly apply to today's children as their social cognition develops in interaction with technological entities which are increasingly characterized by unprecedented combinations of human and non-human qualities. [ABSTRACT FROM AUTHOR]

The use of IoT products is increasingly becoming part of the everyday life of citizens in the EU. With the consumer IoT sector braced for rapid growth, the European Commission is concerned that it will be concentrated in a small number of companies. The Commission is particularly wary that Big Tech may leverage their large shares on the voice assistants market to harm developing competitors and consumers. The preliminary report of its inquiry into the consumer IoT sector published in June 2021 shows that many respondents share the Commission's competition concerns. If, after analyzing the results of the inquiry, the Commission turns up evidence of anti-competitive practices by tech giants, it could initiate investigations against those companies to ensure compliance with EU rules on abuse of dominant position. Nevertheless, some experts doubt whether a crackdown on Big Tech would lead to a more competitive and innovative IoT market. [ABSTRACT FROM AUTHOR]

Background: Artificial intelligence has provided new opportunities for human interactions with technology for the practice of medicine. Among the recent artificial intelligence innovations, personal voice assistants have been broadly adopted. This highlights their potential for health care-related applications such as behavioral counseling to promote healthy lifestyle habits and emotional well-being. However, the use of voice-based applications for behavioral therapy has not been previously evaluated. Objective: This study aimed to conduct a formative user evaluation of Lumen, a virtual voice-based coach developed as an Alexa skill that delivers evidence-based, problem-solving treatment for patients with mild to moderate depression and/or anxiety. Methods: A total of 26 participants completed 2 therapy sessions--an introductory (session 1) and a problem-solving (session 2)--with Lumen. Following each session with Lumen, participants completed user experience, task-related workload, and work alliance surveys. They also participated in semistructured interviews addressing the benefits, challenges and barriers to Lumen use, and design recommendations. We evaluated the differences in user experience, task load, and work alliance between sessions using 2-tailed paired t tests. Interview transcripts were coded using an inductive thematic analysis to characterize the participants' perspectives regarding Lumen use. Results: Participants found Lumen to provide high pragmatic usability and favorable user experience, with marginal task load during interactions for both Lumen sessions. However, participants experienced a higher temporal workload during the problem-solving session, suggesting a feeling of being rushed during their communicative interactions. On the basis of the qualitative analysis, the following themes were identified: Lumen's on-demand accessibility and the delivery of a complex problem-solving treatment task with a simplistic structure for achieving therapy goals; themes related to Lumen improvements included streamlining and improved personalization of conversations, slower pacing of conversations, and providing additional context during therapy sessions. Conclusions: On the basis of an in-depth formative evaluation, we found that Lumen supported the ability to conduct cognitively plausible interactions for the delivery of behavioral therapy. Several design suggestions identified from the study including reducing temporal and cognitive load during conversational interactions, developing more natural conversations, and expanding privacy and security features were incorporated in the revised version of Lumen. Although further research is needed, the promising findings from this study highlight the potential for using Lumen to deliver personalized and accessible mental health care, filling a gap in traditional mental health services. [ABSTRACT FROM AUTHOR]

To meet expectations of stakeholders in Education 4.0, the inclination towards acceptance, testing, and implementation of Voice Assistants has increased at a faster pace in western universities. This study has been done to understand the present level of performance and capability of voice assistants in answering the basic queries of users from Indian Higher education sector. Three voice assistants namely Amazon Alexa, Microsoft Cortana, and Google Assistant have been considered for a survey in which 100 students participated and tested the performance of these three voice assistants by asking basic questions related to admission and examination. A set of total 14 questions has been selected to be asked by user in both the categories. Category 1 related to Admissions contained 7 little complex questions while category 2 related to Examination had 7 direct and simpler questions. Responses of the users were noted down and after careful analysis, the explanations have been deduced about performance of these voice assistants in factors considered: understanding of voice and language of user, understanding of basic meaning of the question, request to repeat the question, whether the answer was given by voice assistants and quality of the answer received. As per the results, various observations have been noted that may further help Artificial Intelligence developers and programmers to understand the success and failure of voice assistants and accordingly bring improvements in their performance level. This study also helps in knowing about huge applications, contributions and benefits these voice assistants offer to the stakeholders. Once the improvements are incorporated by the developers, marketing professionals can boost the absorption and use of voice assistants in massive higher education sector of India by convincing the important stakeholders that also paves a way to tap into more undiscovered possibilities about use of Artificial Intelligence in higher education system at global level. [ABSTRACT FROM AUTHOR]

Recently emerging synthetic acoustically gender-ambiguous voices could contribute to dissolving the still prevailing genderism. Yet, are we indeed perceiving these voices as "unassignable"? Or are we trying to assimilate them into existing genders? To investigate the perceived ambiguity, we conducted an explorative 3 (male, female, ambiguous voice) × 3 (male, female, ambiguous topic) experiment (N = 343). We found that, although participants perceived the gender-ambiguous voice as ambiguous, they used a profoundly wide range of the scale, indicating tendencies toward a gender. We uncovered a mild dissolve of gender roles. Neither the listener's gender nor the personal gender stereotypes impacted the perception. However, the perceived topic gender indicated the perceived voice gender, and younger people tended to perceive a more male-like gender. [ABSTRACT FROM AUTHOR]

Digital assistants increasingly infiltrate the world of children. The way they function reminds us somewhat of playmates, nannies and tutors. So far, educators have only marginally dealt with this new media phenomenon, yet the use of smart speakers by young people offers many opportunities as well as challenges. These are elaborated in this article and classified in terms of media education. Firstly, we will address a definition of smart speakers and digital speech assistants, and then examine their use by means of usage data. We will then concentrate on examining the extent to which these smart technologies play a role in the environments of young people. What forms of advertising are there? What data do digital assistants collect? And finally, how can parents, educators and companies ensure that smart technologies are used in a child-friendly manner that complies with data protection regulations? Our aim is to nudge the phenomenon of smart speakers and speech assistants into the media-pedagogical focus. Dealing with the specific characteristics of smart speakers requires a high degree of (child) user competence. As we will show in the conclusion, there are further pedagogically beneficial approaches from the point of view of promoting advertising literacy.

Data annotation for human activity recognition is a well-known challenge for researchers. In particular, annotation in daily life settings relies on self-reporting tools with unknown accuracy. Speech is a promising interface for activity labeling. In this work, we compare the accuracy of two commercially available tools for annotation: voice diaries and connected buttons. We retrofit the water meters of thirty homes in the USA for infrastructure-mediated sensing. Participants are split into equal groups and receive one of the self-reporting tools. The balanced accuracy metric is transferred from the field of machine learning to the evaluation of the annotation performance. Our results show that connected buttons perform significantly better than the voice diary, with 92% median accuracy and 65% median reporting rate. Using questionnaire answers, we highlight that annotation performance is impacted by habit formation and sentiments toward the annotation tool. The use case for data annotation is to disaggregate water meter data into human activities beyond the point of use. We show that it is feasible with a machine-learning model and the corrected annotations. Finally, we formulate recommendations for the design of studies and intelligent environments around the key ideas of proportionality and immediacy. • Self-reporting of human activities enables to train machine learning algorithms. • Speech is not the best interface to report chores in daily life settings. • Internet-connected buttons prove better with 92% accuracy and 65% reporting rate. • Human activities can be inferred from smart water meter data. [ABSTRACT FROM AUTHOR]

• People with visual impairments face difficulties accessing cultural, historical, and practical information because the world relies heavily on visual cues. • Museums provide opportunities for exploration and learning, but often overlook accessibility issues. They can be part of the solution for the blind. • Using inclusive audio descriptions and spatialized sounds during remote museum navigation can help blind people develop a cognitive map of the museum layout and increase engagement and immersion. • The research goes beyond helping with navigation. It also positively impacts social learning, engagement, and a deeper appreciation of cultural heritage among blind people. • Co-designed, humor-infused, and culturally sensitive voice assistants have the potential to enrich the lives of people with visual impairments and improve their access to cultural heritage. People with visual imparments (PWVI) encounter challenges in accessing cultural, historical, and practical information in a predominantly visual world, limiting their participation in various activities, including visits to museums.Museums, as important centers for exploration and learning, often overlook these accessibility issues.This abstract presents the iMuse Model, an innovative approach to create accessible and inclusive museum environments for them.The iMuse Model centers around the co-design of a prototype voice assistant integrated into Google Home, aimed at enabling remote navigation for PWVI within the Basilica Cistern museum in Turkey.This model consists of a two-layer study.The first layer involves collaboration with PWVI and their sight loss instructors to develop a five level framework tailored to their unique needs and challenges.The second layer focuses on testing this design with 30 people with visual impairments, employing various methodologies, including the Wizard of Oz technique.Our prototype provides inclusive audio descriptions that encompass sensory, emotional, historical, and structural elements, along with spatialized sounds from the museum environment, improving spatial understanding and cognitive map development.Notably, we have developed two versions of the voice assistant: one with a humorous interaction and one with a non-humorous approach. Users expressed a preference for the humorous version, leading to increased interaction, enjoyment, and social learning, as supported by both qualitative and quantitative results.In conclusion, the iMuse Model highlights the potential of co-designed, humor-infused, and culturally sensitive voice assistants.Our model not only aid PWVI in navigating unfamiliar spaces but also enhance their social learning, engagement, and appreciation of cultural heritage within museum environments. [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI) is supposed to perform tasks autonomously, make competent decisions, and interact socially with people. From a psychological perspective, AI can thus be expected to impact users' three Basic Psychological Needs (BPNs), namely (i) autonomy, (ii) competence, and (iii) relatedness to others. While research highlights the fulfillment of these needs as central to human motivation and well-being, their role in the acceptance of AI applications has hitherto received little consideration. Addressing this research gap, our study examined the influence of BPN Satisfaction on Intention to Use (ITU) an AI assistant for personal banking. In a 2×2 factorial online experiment, 282 participants (154 males, 126 females, two non-binary participants) watched a video of an AI finance coach with a female or male synthetic voice that exhibited either high or low agency (i.e., capacity for self-control). In combination, these factors resulted either in AI assistants conforming to traditional gender stereotypes (e.g., low-agency female) or in non-conforming conditions (e.g., high-agency female). Although the experimental manipulations had no significant influence on participants' relatedness and competence satisfaction, a strong effect on autonomy satisfaction was found. As further analyses revealed, this effect was attributable only to male participants, who felt their autonomy need significantly more satisfied by the low-agency female assistant, consistent with stereotypical images of women, than by the high-agency female assistant. A significant indirect effects model showed that the greater autonomy satisfaction that men, unlike women, experienced from the low-agency female assistant led to higher ITU. The findings are discussed in terms of their practical relevance and the risk of reproducing traditional gender stereotypes through technology design. [ABSTRACT FROM AUTHOR]

Copyright of Transfer: Zeitschrift für Kommunikation & Markenmanagement is the property of Deutsche Werbewissenschaftliche Gesellschaft 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.)

Copyright of Transfer: Zeitschrift für Kommunikation & Markenmanagement is the property of Deutsche Werbewissenschaftliche Gesellschaft 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.)

Social robots, conversational agents, voice assistants, and other embodied AI are increasingly a feature of everyday life. What connects these various types of intelligent agents is their ability to interact with people through voice. Voice is becoming an essential modality of embodiment, communication, and interaction between computer-based agents and end-users. This survey presents a meta-synthesis on agent voice in the design and experience of agents from a human-centered perspective: voice-based human-agent interaction (vHAI). Findings emphasize the social role of voice in HAI as well as circumscribe a relationship between agent voice and body, corresponding to human models of social psychology and cognition. Additionally, changes in perceptions of and reactions to agent voice over time reveals a generational shift coinciding with the commercial proliferation of mobile voice assistants. The main contributions of this work are a vHAI classification framework for voice across various agent forms, contexts, and user groups, a critical analysis grounded in key theories, and an identification of future directions for the oncoming wave of vocal machines. [ABSTRACT FROM AUTHOR]

New technologies like voice assistants such as Siri, Alexa, and the Google Assistant give the impression that the lines between humans and machines are blurring as machines gradually take up social roles once occupied by humans. To counter that anxiety, this essay argues that these technologies are becoming more like characters, adapting to the templates we initially constructed for fictional beings whose space voice assistants occupy instead. It provides a textual reading of the Japanese voice assistant Hikari Azuma as advertised by the company Vinclu's website in order to demonstrate how Hikari functions as a kyara , a character without story, whose development depends on the user. The essay proposes that we have to adjust our conceptual understanding of characters as distinct from human beings and technology. Instead, the essay concludes that we should perceive current technologies like voice assistants as technologies operating on a spectrum in which some machines will look more like characters and others more like software-in-action with no humanlikeness at all. [ABSTRACT FROM AUTHOR]

As children increasingly interact with digital voice assistants, it is important to know whether they treat these devices as reliable information sources. Two studies investigated children's trust in and recall of statements made by a novel voice assistant and a human informant. In Study I, children ages 4-5 (Mage = 5.05; 20 boys, 20 girls) and 7-8 (Mage = 7.98; 18 boys, 22 girls) from predominately White, upper middle-class families heard each informant respond to questions from multiple categories. With increasing age, children showed greater trust in the voice assistant for factual information and greater trust in the human for personal information about the experimenter identified as her friend. Endorsement of each informant's statements also predicted later recall. In Study 2, children ages 4-5 (Mage = 5.00; 20 boys, 20 girls) and 7-8 (Mage = 8.03; 19 boys, 21 girls) from predominately White, upper middle-class families chose whether to seek out information from a voice assistant or human informant. With increasing age, children showed an increasing preference to seek factual information from the voice assistant and an increasing preference to seek personal information from the human. Additionally, children's preferences were not related to attributions of epistemic capacities to each informant nor the presence of a voice assistant in children's homes. These results suggest that children's trust in voice assistants varies with age and depends on the type of information involved. [ABSTRACT FROM AUTHOR]

Copyright of HMD: Praxis der Wirtschaftsinformatik is the property of Springer Nature 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.)

Artificial Intelligence (AI) is supposed to perform tasks autonomously, make competent decisions, and interact socially with people. From a psychological perspective, AI can thus be expected to impact users’ three Basic Psychological Needs (BPNs), namely (i) autonomy, (ii) competence, and (iii) relatedness to others. While research highlights the fulfillment of these needs as central to human motivation and well-being, their role in the acceptance of AI applications has hitherto received little consideration. Addressing this research gap, our study examined the influence of BPN Satisfaction on Intention to Use (ITU) an AI assistant for personal banking. In a 2×2 factorial online experiment, 282 participants (154 males, 126 females, two non-binary participants) watched a video of an AI finance coach with a female or male synthetic voice that exhibited either high or low agency (i.e., capacity for self-control). In combination, these factors resulted either in AI assistants conforming to traditional gender stereotypes (e.g., low-agency female) or in non-conforming conditions (e.g., high-agency female). Although the experimental manipulations had no significant influence on participants’ relatedness and competence satisfaction, a strong effect on autonomy satisfaction was found. As further analyses revealed, this effect was attributable only to male participants, who felt their autonomy need significantly more satisfied by the low-agency female assistant, consistent with stereotypical images of women, than by the high-agency female assistant. A significant indirect effects model showed that the greater autonomy satisfaction that men, unlike women, experienced from the low-agency female assistant led to higher ITU. The findings are discussed in terms of their practical relevance and the risk of reproducing traditional gender stereotypes through technology design.

Because technologies are frequently used for sexual gratification it seems plausible that artificial communication partners, such as voice assistants, could be used to fulfill sexual needs. While the idea of sexualized interaction with voice assistants has been portrayed in movies (e.g., "Her"), there is a lack of empirical research on the effect of the ontological class (human versus artificial) on the voice's potential to evoke interest in a sexualized interaction and its perception in terms of sexual attractiveness. The Sexual Interaction Illusion Model (SIIM), which emphasizes influences on sensations evoked by artificial interaction partners, furthermore suggests that there may be contextual influences, especially sexual arousal, that may be crucial for the question of engaging in a sexualized interaction with an artificial entity. To empirically investigate whether the ontological class of the speaker (computer-mediated human in comparison to voice assistants) and the level of sexual arousal affects the heterosexual males' interest in hearing more flirtatious messages and the perception of the communication partner's sexual attractiveness, an online experiment with between subject design was conducted. Two hundred and fifty seven respondents were confronted with at least four, and voluntarily six messages from either a computer-mediated human or a flirtatious voice assistant, in interaction with being previously primed sexually or neutrally. The results demonstrated that the effect of sexual arousal was not prevailing on the interest in further messages and the attractiveness perception of the interaction partners, while the ontological class did so. Here, the voice assistant evoked more interest in further messages and the technology itself, while the computer mediated human was perceived to be more sexually attractive and flirtatious, and evoked more social presence. The communication partners social presence was shown to be the predictor with most explanatory power for the interaction partners perceived sexual attractiveness, regardless of whether it was human or artificial. The results underline differences between artificial and human interaction partners, but also underline that especially social presence and the feeling that the user is addressed (in terms of flirtatiousness) is crucial in digitalized intimacy regardless of the ontological class. [ABSTRACT FROM AUTHOR]

In recent years, Artificial Intelligence (AI) has shown significant progress and its potential is growing. An application area of AI is Natural Language Processing (NLP). Voice assistants incorporate AI by using cloud computing and can communicate with the users in natural language. Voice assistants are easy to use and thus there are millions of devices that incorporates them in households nowadays. Most common devices with voice assistants are smart speakers and they have just started to be used in schools and universities. The purpose of this paper is to study how voice assistants and smart speakers are used in everyday life and whether there is potential in order for them to be used for educational purposes.

During the digital transformation, artificial intelligence technologies are actively developed and implemented in the organization’s management processes. This trend also applies to human resource management. The purpose of this article is to substantiate the benefits of using artificial intelligence tools in human resource management for organizations. Current state of human resource management has been analysed in the article, its main problems have been defined. The opportunities offered by artificial intelligence technologies offer in the field of human resources as well as the problems companies face in their implementation have been considered. Practical examples of the use of artificial intelligence tools such as chatbots, mood analysis technologies, voice assistants, facial recognition system in the field of human resource management have been given.

The emergence, development, problems, prospects and statistics of the use of voice assistants in interactive marketing communications have been considered. The use of voice assistants as an interface of interaction with electronic equipment is a new, dynamically developing trend, covering all spheres of human activity. The relevance of the studied problem lies in the fact that the integration of advertising in voice assistants in the near future will affect all types of business in one way to another and become an integral part of a successful advertising campaign: these are the most effective interactive marketing communications of the future. The author’s recommendations on the use of voice assistants in interactive marketing communications have been given.

As part of this work, some dialogue systems and voice assistants have been studied. Based on their comparison, the basic requirements for creating chat bots were formulated. The well-known open source automatic speech recognition systems were studied and on the basis of comparison the most suitable for integration into the prototype of the chat-bot were selected. The results of the testing of the chat-bot prototype were presented. It is a stand-alone mobile application that works without an Internet connection and allows a dialogue on the day-today topics. The differences between regular and corporate chat-bots were highlighted, and the requirements to corporate chat-bots were collected. Other possible implementation options were briefly considered, for example, for people with speech-impaired voice.

Because technologies are frequently used for sexual gratification it seems plausible that artificial communication partners, such as voice assistants, could be used to fulfill sexual needs. While the idea of sexualized interaction with voice assistants has been portrayed in movies (e.g., “Her”), there is a lack of empirical research on the effect of the ontological class (human versus artificial) on the voice’s potential to evoke interest in a sexualized interaction and its perception in terms of sexual attractiveness. The Sexual Interaction Illusion Model (SIIM), which emphasizes influences on sensations evoked by artificial interaction partners, furthermore suggests that there may be contextual influences, especially sexual arousal, that may be crucial for the question of engaging in a sexualized interaction with an artificial entity. To empirically investigate whether the ontological class of the speaker (computer-mediated human in comparison to voice assistants) and the level of sexual arousal affects the heterosexual males’ interest in hearing more flirtatious messages and the perception of the communication partner’s sexual attractiveness, an online experiment with between subject design was conducted. Two hundred and fifty seven respondents were confronted with at least four, and voluntarily six messages from either a computer-mediated human or a flirtatious voice assistant, in interaction with being previously primed sexually or neutrally. The results demonstrated that the effect of sexual arousal was not prevailing on the interest in further messages and the attractiveness perception of the interaction partners, while the ontological class did so. Here, the voice assistant evoked more interest in further messages and the technology itself, while the computer mediated human was perceived to be more sexually attractive and flirtatious, and evoked more social presence. The communication partners social presence was shown to be the predictor with most explanatory power for the interaction partners perceived sexual attractiveness, regardless of whether it was human or artificial. The results underline differences between artificial and human interaction partners, but also underline that especially social presence and the feeling that the user is addressed (in terms of flirtatiousness) is crucial in digitalized intimacy regardless of the ontological class.

In this paper, we present the results of our long-term study on use of a voice assistant (Amazon Alexa via Amazon Echo Dot) in nine families with children and no previous experience with this technology. The study was conducted over the course of 5 weeks during which the families could interact with the device freely. Three house visits were made to collect empirical data from the adult participants in form of questionnaires. Additionally, conversational data from log files of the voice assistant were obtained. These data were annotated and analyzed with a focus on communication breakdowns during human-assistant interaction. We investigate user behavior for both adults and children in such situations, its reasons and consequences for user satisfaction. This article provides qualitative analysis of three particularly interesting breakdown cases, as well as statistical analysis along several hypotheses and research questions combining empirical and conversational data. Described cases of communication breakdown illustrate findings from existing literature on the topic. The statistical analysis paints a mixed picture, however, it helped us identify further avenues for research, some of which can be explored with our data set in the future. We found a significant negative effect of the number of abandoned failed requests on user satisfaction, contrary to the number of successfully repaired requests that had no influence on user satisfaction. We discovered that users are more inclined to use reformulation as repair strategy when they do not perceive the emergence of miscommunication as their fault. We could not identify a significant effect of internal reasons for the choice of other strategies, so we suggest that situational clues such as the immediate response of the voice assistant are more important for the choice of repair strategy. Our results also hint that users distinguish between repair strategies differently, as the self-perceived frequency of repetitions and abortions of requests were found to be positive predictors for the use of reformulation-based strategies. With regards to the long-term aspect of the study, use of repetition as a repair strategy by both children and adults significantly decreased with time, no other changes were found for other strategies. Additionally, no significant impact of age on the choice of repair strategy was found, as well as no interaction effect between age and time.