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Mayara Costa Figueiredo, Elizabeth Ankrah, Jacquelyn E. Powell, Daniel A. Epstein, Yunan Chen

2023Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies15 citationsDOIOpen Access PDF

Abstract

Recently, there has been a proliferation of personal health applications describing to use Artificial Intelligence (AI) to assist health consumers in making health decisions based on their data and algorithmic outputs. However, it is still unclear how such descriptions influence individuals' perceptions of such apps and their recommendations. We therefore investigate how current AI descriptions influence individuals' attitudes towards algorithmic recommendations in fertility self-tracking through a simulated study using three versions of a fertility app. We found that participants preferred AI descriptions with explanation, which they perceived as more accurate and trustworthy. Nevertheless, they were unwilling to rely on these apps for high-stakes goals because of the potential consequences of a failure. We then discuss the importance of health goals for AI acceptance, how literacy and assumptions influence perceptions of AI descriptions and explanations, and the limitations of transparency in the context of algorithmic decision-making for personal health.

Topics & Concepts

Transparency (behavior)TrustworthinessPerceptionContext (archaeology)Computer scienceHealth literacyPsychologyData scienceArtificial intelligenceApplied psychologyInternet privacyHealth carePolitical scienceComputer securityLawPaleontologyBiologyNeuroscienceMobile Health and mHealth ApplicationsInnovative Human-Technology InteractionDigital Mental Health Interventions