@article{WienrichCarolusMarkusetal.2023, author = {Wienrich, Carolin and Carolus, Astrid and Markus, Andr{\´e} and Augustin, Yannik and Pfister, Jan and Hotho, Andreas}, title = {Long-term effects of perceived friendship with intelligent voice assistants on usage behavior, user experience, and social perceptions}, series = {Computers}, volume = {12}, journal = {Computers}, number = {4}, issn = {2073-431X}, doi = {10.3390/computers12040077}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-313552}, year = {2023}, abstract = {Social patterns and roles can develop when users talk to intelligent voice assistants (IVAs) daily. The current study investigates whether users assign different roles to devices and how this affects their usage behavior, user experience, and social perceptions. Since social roles take time to establish, we equipped 106 participants with Alexa or Google assistants and some smart home devices and observed their interactions for nine months. We analyzed diverse subjective (questionnaire) and objective data (interaction data). By combining social science and data science analyses, we identified two distinct clusters—users who assigned a friendship role to IVAs over time and users who did not. Interestingly, these clusters exhibited significant differences in their usage behavior, user experience, and social perceptions of the devices. For example, participants who assigned a role to IVAs attributed more friendship to them used them more frequently, reported more enjoyment during interactions, and perceived more empathy for IVAs. In addition, these users had distinct personal requirements, for example, they reported more loneliness. This study provides valuable insights into the role-specific effects and consequences of voice assistants. Recent developments in conversational language models such as ChatGPT suggest that the findings of this study could make an important contribution to the design of dialogic human-AI interactions.}, language = {en} } @article{CarolusWienrich2022, author = {Carolus, Astrid and Wienrich, Carolin}, title = {"Imagine this smart speaker to have a body": An analysis of the external appearances and the characteristics that people associate with voice assistants}, series = {Frontiers in Computer Science}, volume = {4}, journal = {Frontiers in Computer Science}, issn = {2624-9898}, doi = {10.3389/fcomp.2022.981435}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-297175}, year = {2022}, abstract = {Introduction Modern digital devices, such as conversational agents, simulate human-human interactions to an increasing extent. However, their outward appearance remains distinctly technological. While research revealed that mental representations of technology shape users' expectations and experiences, research on technology sending ambiguous cues is rare. Methods To bridge this gap, this study analyzes drawings of the outward appearance participants associate with voice assistants (Amazon Echo or Google Home). Results Human beings and (humanoid) robots were the most frequent associations, which were rated to be rather trustworthy, conscientious, agreeable, and intelligent. Drawings of the Amazon Echos and Google Homes differed marginally, but "human," "robotic," and "other" associations differed with respect to the ascribed humanness, consciousness, intellect, affinity to technology, and innovation ability. Discussion This study aims to further elaborate on the rather unconscious cognitive and emotional processes elicited by technology and discusses the implications of this perspective for developers, users, and researchers.}, language = {en} } @article{WienrichCarolusRothIsigkeitetal.2022, author = {Wienrich, Carolin and Carolus, Astrid and Roth-Isigkeit, David and Hotho, Andreas}, title = {Inhibitors and enablers to explainable AI success: a systematic examination of explanation complexity and individual characteristics}, series = {Multimodal Technologies and Interaction}, volume = {6}, journal = {Multimodal Technologies and Interaction}, number = {12}, issn = {2414-4088}, doi = {10.3390/mti6120106}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-297288}, year = {2022}, abstract = {With the increasing adaptability and complexity of advisory artificial intelligence (AI)-based agents, the topics of explainable AI and human-centered AI are moving close together. Variations in the explanation itself have been widely studied, with some contradictory results. These could be due to users' individual differences, which have rarely been systematically studied regarding their inhibiting or enabling effect on the fulfillment of explanation objectives (such as trust, understanding, or workload). This paper aims to shed light on the significance of human dimensions (gender, age, trust disposition, need for cognition, affinity for technology, self-efficacy, attitudes, and mind attribution) as well as their interplay with different explanation modes (no, simple, or complex explanation). Participants played the game Deal or No Deal while interacting with an AI-based agent. The agent gave advice to the participants on whether they should accept or reject the deals offered to them. As expected, giving an explanation had a positive influence on the explanation objectives. However, the users' individual characteristics particularly reinforced the fulfillment of the objectives. The strongest predictor of objective fulfillment was the degree of attribution of human characteristics. The more human characteristics were attributed, the more trust was placed in the agent, advice was more likely to be accepted and understood, and important needs were satisfied during the interaction. Thus, the current work contributes to a better understanding of the design of explanations of an AI-based agent system that takes into account individual characteristics and meets the demand for both explainable and human-centered agent systems.}, language = {en} } @article{CarolusWienrichToerkeetal.2021, author = {Carolus, Astrid and Wienrich, Carolin and T{\"o}rke, Anna and Friedel, Tobias and Schwietering, Christian and Sperzel, Mareike}, title = {'Alexa, I feel for you!' Observers' empathetic reactions towards a conversational agent}, series = {Frontiers in Computer Science}, volume = {3}, journal = {Frontiers in Computer Science}, doi = {10.3389/fcomp.2021.682982}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-258807}, year = {2021}, abstract = {Conversational agents and smart speakers have grown in popularity offering a variety of options for use, which are available through intuitive speech operation. In contrast to the standard dyad of a single user and a device, voice-controlled operations can be observed by further attendees resulting in new, more social usage scenarios. Referring to the concept of 'media equation' and to research on the idea of 'computers as social actors,' which describes the potential of technology to trigger emotional reactions in users, this paper asks for the capacity of smart speakers to elicit empathy in observers of interactions. In a 2 × 2 online experiment, 140 participants watched a video of a man talking to an Amazon Echo either rudely or neutrally (factor 1), addressing it as 'Alexa' or 'Computer' (factor 2). Controlling for participants' trait empathy, the rude treatment results in participants' significantly higher ratings of empathy with the device, compared to the neutral treatment. The form of address had no significant effect. Results were independent of the participants' gender and usage experience indicating a rather universal effect, which confirms the basic idea of the media equation. Implications for users, developers and researchers were discussed in the light of (future) omnipresent voice-based technology interaction scenarios.}, language = {en} } @article{WienrichCarolus2021, author = {Wienrich, Carolin and Carolus, Astrid}, title = {Development of an Instrument to Measure Conceptualizations and Competencies About Conversational Agents on the Example of Smart Speakers}, series = {Frontiers in Computer Science}, volume = {3}, journal = {Frontiers in Computer Science}, doi = {10.3389/fcomp.2021.685277}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-260198}, year = {2021}, abstract = {The concept of digital literacy has been introduced as a new cultural technique, which is regarded as essential for successful participation in a (future) digitized world. Regarding the increasing importance of AI, literacy concepts need to be extended to account for AI-related specifics. The easy handling of the systems results in increased usage, contrasting limited conceptualizations (e.g., imagination of future importance) and competencies (e.g., knowledge about functional principles). In reference to voice-based conversational agents as a concrete application of AI, the present paper aims for the development of a measurement to assess the conceptualizations and competencies about conversational agents. In a first step, a theoretical framework of "AI literacy" is transferred to the context of conversational agent literacy. Second, the "conversational agent literacy scale" (short CALS) is developed, constituting the first attempt to measure interindividual differences in the "(il) literate" usage of conversational agents. 29 items were derived, of which 170 participants answered. An explanatory factor analysis identified five factors leading to five subscales to assess CAL: storage and transfer of the smart speaker's data input; smart speaker's functional principles; smart speaker's intelligent functions, learning abilities; smart speaker's reach and potential; smart speaker's technological (surrounding) infrastructure. Preliminary insights into construct validity and reliability of CALS showed satisfying results. Third, using the newly developed instrument, a student sample's CAL was assessed, revealing intermediated values. Remarkably, owning a smart speaker did not lead to higher CAL scores, confirming our basic assumption that usage of systems does not guarantee enlightened conceptualizations and competencies. In sum, the paper contributes to the first insights into the operationalization and understanding of CAL as a specific subdomain of AI-related competencies.}, language = {en} } @article{WienrichReitelbachCarolus2021, author = {Wienrich, Carolin and Reitelbach, Clemens and Carolus, Astrid}, title = {The Trustworthiness of Voice Assistants in the Context of Healthcare Investigating the Effect of Perceived Expertise on the Trustworthiness of Voice Assistants, Providers, Data Receivers, and Automatic Speech Recognition}, series = {Frontiers in Computer Science}, volume = {3}, journal = {Frontiers in Computer Science}, doi = {10.3389/fcomp.2021.685250}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-260209}, year = {2021}, abstract = {As an emerging market for voice assistants (VA), the healthcare sector imposes increasing requirements on the users' trust in the technological system. To encourage patients to reveal sensitive data requires patients to trust in the technological counterpart. In an experimental laboratory study, participants were presented a VA, which was introduced as either a "specialist" or a "generalist" tool for sexual health. In both conditions, the VA asked the exact same health-related questions. Afterwards, participants assessed the trustworthiness of the tool and further source layers (provider, platform provider, automatic speech recognition in general, data receiver) and reported individual characteristics (disposition to trust and disclose sexual information). Results revealed that perceiving the VA as a specialist resulted in higher trustworthiness of the VA and of the provider, the platform provider and automatic speech recognition in general. Furthermore, the provider's trustworthiness affected the perceived trustworthiness of the VA. Presenting both a theoretical line of reasoning and empirical data, the study points out the importance of the users' perspective on the assistant. In sum, this paper argues for further analyses of trustworthiness in voice-based systems and its effects on the usage behavior as well as the impact on responsible design of future technology.}, language = {en} } @article{SchwabHennighausenAdleretal.2018, author = {Schwab, Frank and Hennighausen, Christine and Adler, Dorothea C. and Carolus, Astrid}, title = {Television Is Still "Easy" and Print Is Still "Tough"? More Than 30 Years of Research on the Amount of Invested Mental Effort}, series = {Frontiers in Psychology}, volume = {9}, journal = {Frontiers in Psychology}, number = {1098}, issn = {1664-1078}, doi = {10.3389/fpsyg.2018.01098}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-189965}, year = {2018}, abstract = {We provide a literature overview of 30 years of research on the amount of invested mental effort (AIME, Salomon, 1984), illuminating relevant literature in this field. Since the introduction of AIME, this concept appears to have vanished. To obtain a clearer picture of where the theory of AIME has diffused, we conducted a literature search focusing on the period 1985-2015. We examined scientific articles (N = 244) that cite Salomon (1984) and content-analyzed their keywords. Based on these keywords, we identified seven content clusters: affect and motivation, application fields, cognition and learning, education and teaching, media technology, learning with media technology, and methods. We present selected works of each content cluster and describe in which research field the articles had been published. Results indicate that AIME was most commonly (but not exclusively) referred to in the area of educational psychology indicating its importance regarding learning and education, thereby investigating print and TV, as well as new media. From a methodological perspective, research applied various research methods (e.g., longitudinal studies, experimental designs, theoretical analysis) and samples (e.g., children, college students, low income families). From these findings, the importance of AIME for further research is discussed.}, language = {en} }