Early Explorations of Recommender Systems for Physical Activity and Well-being

TL;DR

This paper explores the unique challenges and design considerations of recommender systems that influence physical activity and well-being through wearables, emphasizing trust, intent, and consequences.

Contribution

It introduces a conceptual framework with three design dimensions to address trust, interpretation, and impact in embodied recommender systems.

Findings

Identifies key limitations of traditional recommender systems in physical contexts.

Proposes design strategies for long-term well-being and behavioral alignment.

Highlights importance of socially responsible personalization.

Abstract

As recommender systems increasingly guide physical actions, often through wearables and coaching tools, new challenges arise around how users interpret, trust, and respond to this advice. This paper introduces a conceptual framework for tangible recommendations that influence users' bodies, routines, and well-being. We describe three design dimensions: trust and interpretation, intent alignment, and consequence awareness. These highlight key limitations in applying conventional recommender logic to embodied settings. Through examples and design reflections, we outline how future systems can support long-term well-being, behavioral alignment, and socially responsible personalization.