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Building a Companion: Analysis of Normative Guidance from a Social Robotics Developer
ABSTRACT
Background:
In media coverage and social commentary, perspectives on actual and potential AI-enabled companions for older adults range from enthusiasm, to caution about social effects, to concern about the harms of over-engagement by vulnerable users. This paper explores how these evolving ideas and values about AI use in later life are interpreted within the professional culture of a social robotics lab.
Objective:
Through study of the lab’s code of ethics and other guidance documents, the objective was to understand these developers’ perspectives on decision points in building a companion robot for people aging in place.
Methods:
The authors used narrative analysis of grey-literature documents produced by and for the team developing a semi-embodied companion robot for people aging in place alone. The analysis also applied concepts from AI ethics and from human-centered approaches to AI design for older adults.
Results:
Guidance documents preserved insights into ethical challenges that arose during product development and iteratively articulated guiding principles for this lab that were informed by team-level decisions about the companion robot’s character and behavior. Guidance documents interpreted principles of AI ethics within a human-centered, design-oriented approach emphasizing support for the user’s goals and relationships, prevention of overdependence on the robot, and authenticity in how the robot presents itself.
Conclusions:
Based on this narrative analysis, this paper offers six lessons for aging-focused researchers and professionals involved in development, evaluation, or implementation of AI-enabled companions for older adults: human-centered design informed by users’ experiences; time-limited engagement; differentiation of companion robots from surveillance devices; the need for ethical guidance for everyday work; public sharing of ethical insights from practice to support consensus-building, and integration of insights from AI design and development processes into principles and practices of AI ethics. Clinical Trial: Not applicable.
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.