Alexa, Can You Help Me Solve That Problem? – Understanding the Value of Smart Personal Assistants as Tutors for Complex Problem Tasks

In recent decades, the number of students per lecturer at universities has constantly risen. In these learning scenarios, individual lecturer support for helping students actively acquiring new knowledge is hardly possible. However, active student behavior is necessary for successful learning. Smart Personal Assistants such as Amazon’s Alexa or Google’s Home promise to fill this gap by being students’ individual tutors. In order to understand what students expect from Smart Personal Assistants as tutors and how they interact with them, we will carry out an experiment. In this research in progress paper, we present our experiment design, where we observe the individual interaction between students and a Smart Personal Assistant tutor and between students and a human tutor applying the same methods in both cases. Drawing on the concepts of parasocial interaction and trust, we derive hypotheses, present the Smart Personal Assistant development and explain the experiment process in detail

A Proposed Theoretical Model of Discontinuous Usage of Voice-Activated Intelligent Personal Assistants (IPAs)

Based on the contradictory phenomenon of rapid development of Voice-Activated Intelligent Personal Assistants (Voice-Activated IPAs) and discontinuous usage of it, this paper investigates the antecedents of discontinuous usage of Voice-Activated IPAs. We first analyze the topic of Siri usage discussion from Zhihu\u27s Q&A website, and then propose a theoretical model which hypothesized that discontinuous usage of Voice-Activated IPAs are affected by perceived ambiguity, cognitive overload, privacy concern, social embarrassment and lack of integration. It is hypothesized that perceived ambiguity will exert nonlinear impacts on discontinuous usage. Meanwhile, perceived ambiguity is also affected by level of personification in a nonlinear way. Scale development and data collection would be conducted for the future work. It is expected that the results our research could provide theoretical and practical implications for the design of Voice-Activated IPAs

Evaluating the social acceptability of voice based smartwatch search

There has been a recent increase in the number of wearable (e.g. smartwatch, interactive glasses, etc.) devices available. Coupled with this there has been a surge in the number of searches that occur on mobile devices. Given these trends it is inevitable that search will become a part of wearable interaction. Given the form factor and display capabilities of wearables this will probably require a different type of search interaction to what is currently used in mobile search. This paper presents the results of a user study focusing on users’ perceptions of the use of smartwatches for search. We pay particular attention to social acceptability of different search scenarios, focussing on in-put method, device form and information need. Our findings indicate that audience and location heavily influence whether people will perform a voice based search. The results will help search system developers to support search on smartwatches

UGA or TAM: Which Approach Explains Digital Voice Assistant Acceptance Better?

Digital voice assistants (DVAs) have the potential to radically change the communication between companies and their customers in the near future. However, despite enormous cost and convenience reduction advantages for both sides, their acceptance is still limited and even tools for measuring their acceptance are missing. Consequently, in this paper, we investigate whether the Uses and Gratifications Approach (UGA) and/or the Technology Acceptance Model (TAM) is/are better suited for this purpose. We have a closer look on a popular DVA – Google Assistant – and investigate DVA acceptance in a navigation and sightseeing context using a field experiment and a follow-up questionnaire (n=173 participants). The results are promising: Both approaches (UGA and TAM) are valid tools. Pastime, expediency, and enjoyment demonstrate to be important drivers for using DVAs

Why Another Customer Channel? Consumers’ Perceived Benefits and Costs of Voice Commerce

Owing to rapidly increasing adoption rates of voice assistants (VAs), integrating voice commerce as a new customer channel is among the top objectives of businesses’ current voice initiatives. However, customers are reluctant to use their VAs for shopping; a tendency not explained by extant literature. Therefore, this research aims to understand consumers’ perceived benefits and costs when using voice commerce, based on a theoretical framework derived from prior literature and the theory of reasoned action. We evaluated and extended this framework by analyzing 30 semi-structured interviews with smart speaker users. According to our results voice commerce consumers perceive benefits in terms of efficiency, convenience, and enjoyment, and criticize the perceived costs of limited transparency, lack of trust, lack of control, and low technical maturity. The resulting model sheds light on the promoters and inhibitors of voice commerce and provides guidelines that enable practitioners to design and improve voice commerce applications

“Hey Siri, how much do you know about me?”: Intelligent Virtual Assistants and the dilemma between commodity and privacy

Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Marketing IntelligenceArtificial Intelligence has been gaining ground over time, and Intelligent Virtual Assistants (IVAs) are no exception, as people realize that they can be using the time and effort spend on daily tasks, more efficiently, by trusting them to these technological auxiliaries. IVAs are being used by people all over the world to change channels, play songs, turn up the volume, reading text messages and emails, calling someone or even grocery shopping when something’s missing, among many other purposes. However, previous studies show that the concerns with data privacy from using these emerging technologies is growing, since in order to work, these AI assistants need constant access to the devices’ microphones, cameras or even locations. Faced with this dilemma, what weights the most on the scale: The users’ commodity, or their information’s privacy and security? In this research, we used PLS-SEM in order to analyze the barriers and drivers that people take into consideration when having to choose if they would use or not Intelligent Virtual Assistants, and what influences this decision, based on four variables: Familiarity, Trust, Satisfaction and Privacy. Our findings conclude that consumers decidedly value their commodity, having familiarity and satisfaction influencing positively the intentions of use, and having satisfaction being highly influenced by trust. At the same time, it also shows that privacy is an inhibitor to many consumers, affecting negatively the usage perception, as expected

Boundary Regulation Processes and Privacy Concerns With (Non-)Use of Voice-Based Assistants

An exemplar of human-machine communication, voice-based assistants (VBAs) embedded in smartphones and smart speakers simplify everyday tasks while collecting significant data about users and their environment. In recent years, devices using VBAs have continued to add new features and collect more data—in potentially invasive ways. Using Communication Privacy Management theory as a guiding framework, we analyze data from 11 focus groups with 65 US adult VBA users and nonusers. Findings highlight differences in attitudes and concerns toward VBAs broadly and provide insights into how attitudes are influenced by device features. We conclude with considerations for how to address boundary regulation challenges inherent in human-machine interactions

Studying with the Help of Digital Tutors: Design Aspects of Conversational Agents that Influence the Learning Process

Conversational agents such as Apple’s Siri or Amazon’s Alexa are becoming more and more prevalent. Almost every smart device comes equipped with such an agent. While on the one hand they can make menial everyday tasks a lot easier for people, there are also more sophisticated use cases in which conversational agents can be helpful. One of these use cases is tutoring in higher education. Several systems to support both formal and informal learning have been developed. There have been many studies about single characteristics of pedagogical conversational agents and how these influence learning outcomes. But what is still missing, is an overview and guideline for atomic design decisions that need to be taken into account when creating such a system. Based on a review of articles on pedagogical conversational agents, this paper provides an extension of existing classifications of characteristics as to include more fine-grained design aspects

Hey Alexa… examine the variables influencing the use of artificial intelligent in-home voice assistants

Artificial Intelligent (AI) In-home Voice Assistants have seen unprecedented growth. However, we have little understanding on the factors motivating individuals to use such devices. Given the unique characteristics of the technology, in the main hands free, controlled by voice, and the presentation of a voice user interface, the current technology adoption models are not comprehensive enough to explain the adoption of this new technology. Focusing on voice interactions, this research combines the theoretical foundations of U&GT with technology theories to gain a clearer understanding on the motivations for adopting and using in-home voice assistants. This research presents a conceptual model on the use of voice controlled technology and an empirical validation of the model through the use of Structural Equation Modelling with a sample of 724 in-home voice assistant users. The findings illustrate that individuals are motivated by the (1) utilitarian benefits, (2) symbolic benefits and (3) social benefits provided by voice assistants, the results found that hedonic benefits only motivate the use of in-home voice assistants in smaller households. Additionally, the research establishes a moderating role of perceived privacy risks in dampening and negatively influencing the use of in-home voice assistants