| Sumario: | Purpose Voice operated virtual personal assistants - or smart speakers - like Amazon's Echo or Apple's HomePod have shown high rates of diffusion in private households in Europe and North America: Since Amazon launched the first smart speaker in the USA in 2015, 38.5% of the total US population have adopted such devices in 2020 (Petrock, 2020). Given this trend, the use of smart speakers is also becoming interesting for gerontechnology. Benefits of smart speakers for older users seem obvious: The devices can be operated despite visual impairments or limitation in mobility and smart speakers can be operated without a visual interface (see e.g. O'Brien et al., 2019; Nimrod & Edan, 2021). Companies like Amazon have started offering specific services such as "Alexa together', that aim at supporting older persons living independently by offering multiple features like fall detection alerts and activity responses (Amazon, 2022). A recurring critique on technologies for older persons particularly within aging research is the deficit-oriented design approach. As Vines et al. (2015) point out, the mainstream public discourse on technology and aging has been dominated by images, which view aging as a societal problem and connect to more deficit-oriented images of older persons. Thus, aging processes are primarily associated with multiple declines (Peine et al., 2014) and characteristics such as frailty, immobility and passivity are stereotypically ascribed to all older persons (see e.g. Katz, 2015). Against this background, the objective of this presentation is to identify smart speaker applications for older persons and to analyze the features offered to users focusing on images of aging. Method Due to the lack of a standardized procedure for the evaluation of smart speaker skills (Chung et al., 2018), we applied a method called feature analysis (Hasinoff & Bivens, 2021). A feature analysis consists of four steps: (1) identification of a problem and apps addressing this problem, (2) identification of features offered by apps, (3) categorization of how the features address the problem, and (4) using speculative design to imaging alternative apps (ibd.). We concentrated on the first three parts. To identify apps, we searched Amazon's skill store for the terms "elderly", "senior", "older person", and abbreviations and included skills that explicitly target older users. To extract information, we developed a template that included aspects like name, description, features, user rating, etc. Results and Discussion The search revealed 67 skills targeting older persons. The dominant category was "Health and fitness" encompassing the most skills (26), followed by "Education and Reference" with 18 skills. Considering the features, we found multiple applications that advertise events at assisted living facilities and within the community. Other features of skills provide information on various aspects of ageing, informed relatives about health and in emergencies, physical and mental exercises, reminders to take medication, podcasts, affirmations, and health monitoring. We found that most skills emphasize rather deficit-oriented images of aging and address certain shortcomings or enforce more convenience for users. Therefore, their intended usage mostly rearranges actions to compensate or to feel relief. A new critical perspective to understand the implications of smart speaker use in old age, could try to examine how this skill replaces a prior practice to remember.
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