Voice assistants embodied in smart speakers (e.g., Amazon Echo, Google Home) enable voice-based interaction that does not necessarily rely on expertise with mobile or desktop computing. Hence, these voice assistants offer new opportunities to different populations, including individuals who are not interested or able to use traditional computing devices such as computers and smartphones. To understand how older adults who use technology infrequently perceive and use these voice assistants, we conducted a 3-week field deployment of the Amazon Echo Dot in the homes of seven older adults. While some types of usage dropped over the 3-week period (e.g., playing music), we observed consistent usage for finding online information. Given that much of this information was health-related, this finding emphasizes the need to revisit concerns about credibility of information with this new interaction medium. Although features to support memory (e.g., setting timers, reminders) were initially perceived as useful, the actual usage was unexpectedly low due to reliability concerns. We discuss how these findings apply to other user groups along with design implications and recommendations for future work on voice-user interfaces.
more »
« less
Use of Intelligent Voice Assistants by Older Adults with Low Technology Use
Voice assistants embodied in smart speakers (e.g., Amazon Echo, Google Home) enable conversational interaction that does not necessarily rely on expertise with mobile or desktop computing. Hence, these voice assistants offer new opportunities to different populations, including individuals who are not interested or able to use traditional computing devices such as computers and smartphones. To understand how older adults who use technology infrequently perceive and use these voice assistants, we conducted a three-week field deployment of the Amazon Echo Dot in the homes of seven older adults. Participants described increased confidence using digital technology and found the conversational voice interfaces easy to use. While some types of usage dropped over the three-week period (e.g., playing music), we observed consistent usage for finding online information. Given that much of this information was health-related, this finding emphasizes the need to revisit concerns about credibility of information with this new interaction medium. Although features to support memory (e.g., setting timers, reminders) were initially perceived as useful, the actual usage was unexpectedly low due to reliability concerns. We discuss how these findings apply to other user groups along with design implications and recommendations for future work on voice user interfaces.
more »
« less
- Award ID(s):
- 1816145
- NSF-PAR ID:
- 10157638
- Date Published:
- Journal Name:
- ACM transactions on computerhuman interaction
- ISSN:
- 1073-0516
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Healthcare applications on Voice Personal Assistant System (e.g., Amazon Alexa), have shown a great promise to deliver personalized health services via a conversational interface. However, concerns are also raised about privacy, safety, and service quality. In this paper, we propose VerHealth, to systematically assess health-related applications on Alexa for how well they comply with existing privacy and safety policies. VerHealth contains a static module and a dynamic module based on machine learning that can trigger and detect violation behaviors hidden deep in the interaction threads. We use VerHealth to analyze 813 health-related applications on Alexa by sending over 855,000 probing questions and analyzing 863,000 responses. We also consult with three medical school students (domain experts) to confirm and assess the potential violations. We show that violations are quite common, e.g., 86.36% of them miss disclaimers when providing medical information; 30.23% of them store user physical or mental health data without approval. Domain experts believe that the applications' medical suggestions are often factually-correct but are of poor relevance, and applications should have asked more questions before providing suggestions for over half of the cases. Finally, we use our results to discuss possible directions for improvements.more » « less
-
null (Ed.)Critical for the early diagnosis of genetic disorders, a Family Health History (FHx) can be collected in several ways including electronic FHx tools, which aid easy editing and sharing by linking with other information management portals. The user acceptance of such systems is critical, especially among older adults experiencing motor and cognitive issues. This study investigated two types of FHx interfaces, standard and Virtual Conversational Agent (VCA), using 30 young (between 18 and 30) and 24 older participants (over 60). Workload, usability and performance data were collected. Even though participants required less time to complete three of five tasks on the standard interface, the VCA interface performed better in terms of subjective workload and usability. Additionally, 67% of the older adults preferred the VCA interface since it provided context-based guidance during the data collection process. The results from this study have implications for the use of virtual assistants in FHx and other areas of data collection.more » « less
-
null (Ed.)Smart speakers such as Amazon Echo present promising opportunities for exploring voice interaction in the domain of in-home exercise tracking. In this work, we examine if and how voice interaction complements and augments a mobile app in promoting consistent exercise. We designed and developed TandemTrack, which combines a mobile app and an Alexa skill to support exercise regimen, data capture, feedback, and reminder. We then conducted a four-week between-subjects study deploying TandemTrack to 22 participants who were instructed to follow a short daily exercise regimen: one group used only the mobile app and the other group used both the app and the skill. We collected rich data on individuals' exercise adherence and performance, and their use of voice and visual interactions, while examining how TandemTrack as a whole influenced their exercise experience. Reflecting on these data, we discuss the benefits and challenges of incorporating voice interaction to assist daily exercise, and implications for designing effective multimodal systems to support self-tracking and promote consistent exercise.more » « less
-
Guizzardi, G. ; Gailly, F. ; Suzana, P. (Ed.)Conversational devices such as Amazon Echo and Google Home represent more than a way to tap into the behavioral surplus of consumers. They provide an opportunity to address societal problems by examining data streams produced by these devices. In this paper, we describe usage patterns and problems related to the use of Amazon Echo devices at home by one specific demographic: the elderly. We rely on a pilot project to collect usage data over multiple months based on deployment of these devices in the homes of eight elderly individuals who either live alone or with a spouse. The paper describes methods used to ensure confidentiality, data collection and analysis procedures, and our findings. We find that the use of conversational devices remains restricted to single commands instead of conversations, making yourself understood remains a problem, sustained use remains a challenge, and the interaction rarely goes beyond simple commands. We interpret the results, and point to the potential for such devices in the lives of the elderly, specifically for health-related problems. The paper also describes lessons learned for capture and analysis of data from such conversational devices.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- The DOI is not currently available.
