Continuous Authentication for Voice Assistants

Voice has become an increasingly popular User Interaction (UI) channel, mainly contributing to the ongoing trend of wearables, smart vehicles, and home automation systems. Voice assistants such as Siri, Google Now and Cortana, have become our everyday fixtures, especially in scenarios where touch interfaces are inconvenient or even dangerous to use, such as driving or exercising. Nevertheless, the open nature of the voice channel makes voice assistants difficult to secure and exposed to various attacks as demonstrated by security researchers. In this paper, we present VAuth, the first system that provides continuous and usable authentication for voice assistants. We design VAuth to fit in various widely-adopted wearable devices, such as eyeglasses, earphones/buds and necklaces, where it collects the body-surface vibrations of the user and matches it with the speech signal received by the voice assistant's microphone. VAuth guarantees that the voice assistant executes only the commands that originate from the voice of the owner. We have evaluated VAuth with 18 users and 30 voice commands and find it to achieve an almost perfect matching accuracy with less than 0.1% false positive rate, regardless of VAuth's position on the body and the user's language, accent or mobility. VAuth successfully thwarts different practical attacks, such as replayed attacks, mangled voice attacks, or impersonation attacks. It also has low energy and latency overheads and is compatible with most existing voice assistants

Examining the role of consumer motivations to use voice assistants for fashion shopping: The mediating role of awe experience and eWOM

Artificial intelligence-enabled voice assistant services have received notable scholarly attention. Fashion retailers offer AI-based voice assistants to facilitate online shoppers. However, the consumer motivations to use digital voice assistants and their effect on the purchase intentions of online fashion shoppers are unexplored. To bridge this literature gap, this study presents a unique theoretical model grounded in the consumer innovativeness concept, broaden-and-built theory, and stimulus-organism-response model to explore the effect of motivated consumer innovativeness to use digital voice assistants on purchase intention and awe experience of online shoppers. The study used data collected from 538 users of digital voice assistants for online shopping of fashion products. Structural equation modeling analysis revealed that the functional, hedonic, social, and cognitive motivated consumer innovativeness for using voice assistants affects purchase intention and awe experience. Further, the awe experience mediates the relationship between motivated consumer innovativeness and purchase intention; and electronic word-of-mouth mediates the relationship between awe experience and purchase intention. The study theoretically contributes to the extant literature on consumer innovativeness, AI-based voice assistants, and fashion shopping. The findings offer insights to fashion retailers for improved use of voice assistants by online shoppers

Perceived value of AI-based recommendations¿ service: the case of voice assistants

The application of artificial intelligence in services is continuously spreading. In particular, one of the most important recent trends is the development of virtual assistants, more particularly; voice assistants, which provide consumers with various services (e.g. information, music) and with product and service recommendations based on their preferences. There is a need to understand how valuable these recommendations are for consumers. This study contributes to the emerging body of research into consumers’ use of the recommendations that voice assistants make in three key ways: (1) by analysing the roles of the benefits (i.e. convenience, compatibility, personalisation) they derive and costs they expend (i.e. cognitive effort, intrusiveness) in the value creation process related to voice assistants’ recommendations; (2) by evaluating the effect of social presence (the key voice assistant feature) on perceived value of voice assistants’ recommendations, through the benefits and costs associated with voice assistants and (3) by determining how the perceived value of voice assistants’ recommendations affects consumer engagement. An online survey was used to collect data. Partial least squares structural equation modelling (PLS-SEM) was employed to analyse the conceptual model. The core findings of the study are as follows. First, social presence enhances the benefits (especially personalisation) and reduces the costs (except for cognitive effort) associated with voice assistants. Second, personalisation was shown to be the strongest determinant of the perceived value of voice assistants’ recommendations, but their intrusiveness is a potential inhibitor in the way of increasing their value. Third, a positive relationship was observed between the perceived value of voice assistants’ recommendations and consumer engagement with the assistants

The role of trusting beliefs in voice assistants during voice shopping

Artificial intelligence-based voice assistants (VAs) such as Amazon Alexa deliver personalized product recommendations in order to match consumers’ needs. The use of voice assistants for shopping purposes in corporates elements of risk affecting when and how they are considered trusted relationship partners. In this uncertain environment, it is unclear ‘when’ voice assistants are capable of gaining trust and ‘how’ the development of such a trusted relationship affects decisions. This research explores the effect of trusting beliefs towards voice assistants on decision satisfaction through the indirect effect of consideration set size (n.of options), in the context of voice shopping. Findings of an individual-session online experiment (N = 180) show a positive direct effect of trust on customer’s satisfaction and a mediating role of set size, confirming consumers’ bias towards default choices. This study highlights the consequences of trust in AI-enabled voice assistants for decision-making during utilitarian purchases

The Role of Trusting Beliefs in Voice Assistants during Voice Shopping

Artificial intelligence-based voice assistants (VAs) such as Amazon Alexa deliver personalized product recommendations in order to match consumers’ needs. The use of voice assistants for shopping purposes incorporates elements of risk affecting when and how they are considered trusted relationship partners. In this uncertain environment, it is unclear ‘when’ voice assistants are capable of gaining trust and ‘how’ the development of such a trusted relationship affects decisions. This research explores the effect of trusting beliefs towards voice assistants on decision satisfaction through the indirect effect of consideration set size (n. of options), in the context of voice shopping. Findings of an individual-session online experiment (N = 180) show a positive direct effect of trust on customer’s satisfaction and a mediating role of set size, confirming consumers’ bias towards default choices. This study highlights the consequences of trust in AI-enabled voice assistants for decision-making during utilitarian purchases

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

Voice assistants as gatekeepers for consumption? - how information intermediaries shape competition

In December 2020, new regulation of digital markets was proposed by European Commission. It specifically addresses main concerns raised by business behavior of operators of core services in their gatekeeping positions. However, voice assistants (or digital personal assistants, DPAs, e.g. Apple’s Siri, Amazon’s Alexa, Google Assistant) are not included into this regulation. In contrast, the Internal Market and Consumer Protection Committee of European Parliament suggested to include them. This paper argues that (i) voice assistants as gatekeepers for consumption should be listed among core services, (ii) some Digital Market Act’s obligations need to be adopted to fit specifics of voice assistants, (iii) two relevant dimensions of power should be included into rebuttable presumptions used for competition policy and regulation: market power on voice assistants’ market and ecosystem of related markets (cross-market integration criterion), (iv) growth of new gatekeepers should be prevented, among other means by stricter merger control