# Personalizing Personal Health Interfaces: Co-Design with Generative AI

arXiv: https://arxiv.org/abs/2609.15046 · HTML: https://mlsanity.com/paper/2609.15046/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 17 of its 94 references that are in the map.
- First posted on arXiv 14 Sep 2026.

## Builds on (most cited first, 17 of 17)

- [The Metacognitive Demands and Opportunities of Generative AI](https://mlsanity.com/paper/2312.10893/) (2023)
- [Luminate: Structured Generation and Exploration of Design Space with Large Language Models for Human-AI Co-Creation](https://mlsanity.com/paper/2310.12953/) (2023)
- [Design Principles for Generative AI Applications](https://mlsanity.com/paper/2401.14484/) (2024)
- [The Effects of Generative AI on Design Fixation and Divergent Thinking](https://mlsanity.com/paper/2403.11164/) (2024)
- [Generative and Malleable User Interfaces with Generative and Evolving Task-Driven Data Model](https://mlsanity.com/paper/2503.04084/) (2025)
- [GenQuery: Supporting Expressive Visual Search with Generative Models](https://mlsanity.com/paper/2310.01287/) (2023)
- [The GenUI Study: Exploring the Design of Generative UI Tools to Support UX Practitioners and Beyond](https://mlsanity.com/paper/2501.13145/) (2025)
- ["In my defense, only three hours on Instagram": Designing Toward Digital Self-Awareness and Wellbeing](https://mlsanity.com/paper/2509.21860/) (2025)
- [StoryEnsemble: Enabling Dynamic Exploration & Iteration in the Design Process with AI and Forward-Backward Propagation](https://mlsanity.com/paper/2508.03182/) (2025)
- [Causal Stories from Sensor Traces: Auditing Epistemic Overreach in LLM-Generated Personal Sensing Explanations](https://mlsanity.com/paper/2605.08590/) (2026)
- [Exploring the Personal Informatics Analysis Gap: "There's a Lot of Bacon"](https://mlsanity.com/paper/2108.03761/) (2021)
- [IntentFlow: Investigating Fluid Dynamics of Intent Communication in Generative AI](https://mlsanity.com/paper/2507.22134/) (2025)
- [Designing Beyond Language: Sociotechnical Barriers in AI Health Technologies for Limited English Proficiency](https://mlsanity.com/paper/2511.07277/) (2025)
- [Designing KRIYA: An AI Companion for Wellbeing Self-Reflection](https://mlsanity.com/paper/2601.14589/) (2026)
- [Generative Experiences for Digital Mental Health Interventions: Evidence from a Randomized Study](https://mlsanity.com/paper/2604.07558/) (2026)
- [Rethinking the UI of GenUI: A Tale of Two Designs](https://mlsanity.com/paper/2606.13843/) (2026)
- [Maru: Information Architecture as a Shared Language for Generating Aligned and Persistent User Interfaces](https://mlsanity.com/paper/2608.25565/) (2026)

## Abstract (arXiv)

Personal health interfaces present wellbeing data through standardized dashboards that rarely fit how people interpret or act on it. Personalizing them to what people would like to see for themselves often requires design and technical expertise, a barrier that generative AI may potentially lower. Therefore, we ask what designs emerge and how it enables and constrains the design process. We conducted a co-design study where 14 participants redesigned Google and Apple Health interfaces using Figma Make. Participants reimagined interfaces that supported personal context, future planning, and interactive experiences, yet conversational AI designs converged around chat-window conventions. AI helped materialize loosely articulated ideas, but model defaults and generation latency shaped iteration. The process more readily operationalized interpretability and accountability than privacy, trust, and emotional safety. Generative co-design let participants create interfaces directly, blurring the boundary between intentions and model defaults. We discuss implications for preserving agency and flexible user-directed interfaces.