Users often mindlessly treat machines such as voice assistants (VAs) like social beings, speaking politely despite VAs functioning as commandable tools that do not require polite expressions. In fact, unnecessary words can even impair interactions, causing frustration. This contrast between social and functional interactions is especially relevant in family homes with children, where VAs are often integrated long-term. Since children are still learning social communication rules, they might adopt negatively connotated communication patterns with the VA, such as a lack of politeness, commanding phrasing, or verbal abuse. Over 2.5 years, 128 parents therefore completed six online surveys about their own and their children’s communication behaviour towards and relationship with their VA, as well as their own social perception of and satisfaction with the VA. Multilevel analyses revealed that parents considered themselves to be more polite to the VA than their children. Perceived relationship closeness between children and VA positively predicted children’s commanding, politeness, and verbal abuse tendencies towards the VA over time, whereas for the parents, relationship closeness only influenced politeness. The findings highlight the potential impact of social perceptions on long-term communication with VAs and tackle the concern of VA’s negative impact on human-human communication.

Despite the rising prevalence of intelligent voice assistants in people's homes, it remains opaque to most users how they function. With the overall goal to foster informed usage and responsible handling of personal data, the user's understanding increasingly moves into the focus of research. Particularly in the context of black box technologies such as voice assistants, individuals build intuitive mental models (also called folk theories) which can act as a guide for how they understand and interact with such systems. To shed light on individuals' mental models regarding intelligent voice assistants, we applied a visual elicitation method during a citizen science workshop: 26 participants were asked to visualize how they imagine a voice assistant to function. The resulting drawings were categorized based on their theorization complexity level. While basic awareness of the overall functionality (user input -- something happens -- voice assistant output) was found in every drawing, 13 participants revealed mental models on how the input is received (e.g., audio recording and speech processing), six on how the information is then processed (e.g., database requests and data categorization), and five on how the output is generated (e.g., speech synthesis). Overall, the results underline the need to address individuals' gaps in understanding of intelligent technology that is already in widespread use.

Intelligent voice assistants such as Alexa and Google Home enable individuals who would otherwise be excluded to access the Internet. For instance, older adults have difficulties operating certain interfaces such as a computer or smartphone because of physical or mental constraints. Due to their intuitive, speech-based control in dialogue form, voice assistants hold the potential to assist older adults and promote their independence. However, for a successful adoption, the technology needs to be accepted and trusted by the target group. With the aim to explore older adults' attitudes towards intelligent voice assistants, semi-structured interviews were conducted with 19 adults between 65 and 86 years. The interviews included a wizard-of-oz interaction with a voice assistant and a vignette describing a scenario in which the voice assistant appears to be eavesdropping. On the one hand, the interviewees evaluated the voice assistant as useful, easy to comprehend, and pleasant. On the other hand, they voiced general data protection concerns, fears of being overheard and observed as well as a strong aversion to unprompted recommendations and advertisement. Most strikingly, fears of being patronized or manipulated by the voice assistant were mentioned frequently, which was justified by a strong need to maintain independence -- particularly with advancing age.

It has long been observed that people treat technical entities like computers as social actors. Numerous studies have been conducted on media equation theory, which describes users' social reactions toward devices to be unconscious. These users consider this inappropriate when thought about consciously. However, both long-term trends as well as the reactions of children have been neglected - although children might indeed differ in their reactions, as they are especially prone to the tendency to humanize and anthropomorphize. This study examined the social behavior of 20 children aged six to twelve toward a voice assistant during a five-week field study. In the course of three sessions, interviews were conducted to assess the children's tendency to socially react to the devices and to what extent they perceive such reactions as appropriate. Additionally, the tendency to anthropomorphize was assessed together with qualitative data to gain insight into cues that would trigger anthropomorphization. Results indicate that age and duration have an effect on the tendency to anthropomorphize. However, age and duration have only a partial effect on social reactions and the evaluation of their appropriateness. Furthermore, natural speech appeared to be a rather strong cue in triggering tendencies to anthropomorphize in the children.