Who Gets to Interpret the Workout? User Tensions with AI-Generated Fitness Feedback
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arXiv
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| Format: | Preprint |
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2026
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| _version_ | 1866910167360077824 |
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| author | Shalawadi, Sujay Wester, Joel Cox, Samuel Rhys van Berkel, Niels |
| author_facet | Shalawadi, Sujay Wester, Joel Cox, Samuel Rhys van Berkel, Niels |
| contents | Fitness tracking platforms increasingly integrate generative AI to interpret activity data, such as Strava's Athlete Intelligence. These integrations raise questions about how athletes engage with AI-supported fitness self-tracking. We analyzed 297 Reddit threads and 5,692 comments from r/Strava following the company's launch of AI features to examine user reactions to AI-generated fitness feedback. Our findings revealed four recurring tensions: (1) numerical evaluation versus contextual understanding; (2) isolated session summaries versus ongoing training narratives; (3) a fixed AI tone versus diverse emotional states; and (4) a single AI voice versus different athletic types. Across these tensions, users resisted AI feedback that constrained interpretations of their own lived experiences. These findings shed light on the implicit challenges of integrating AI into self-tracking platforms. We conclude with implications for the design of AI-supported self-tracking systems that preserve interpretive openness and user agency. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_23830 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Who Gets to Interpret the Workout? User Tensions with AI-Generated Fitness Feedback Shalawadi, Sujay Wester, Joel Cox, Samuel Rhys van Berkel, Niels Human-Computer Interaction Fitness tracking platforms increasingly integrate generative AI to interpret activity data, such as Strava's Athlete Intelligence. These integrations raise questions about how athletes engage with AI-supported fitness self-tracking. We analyzed 297 Reddit threads and 5,692 comments from r/Strava following the company's launch of AI features to examine user reactions to AI-generated fitness feedback. Our findings revealed four recurring tensions: (1) numerical evaluation versus contextual understanding; (2) isolated session summaries versus ongoing training narratives; (3) a fixed AI tone versus diverse emotional states; and (4) a single AI voice versus different athletic types. Across these tensions, users resisted AI feedback that constrained interpretations of their own lived experiences. These findings shed light on the implicit challenges of integrating AI into self-tracking platforms. We conclude with implications for the design of AI-supported self-tracking systems that preserve interpretive openness and user agency. |
| title | Who Gets to Interpret the Workout? User Tensions with AI-Generated Fitness Feedback |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2604.23830 |