In the Middle, Not on Top: AI-Mediated Communication for Patient-Provider Care Relationships
Summary
This article proposes a "middle, not top" approach for integrating AI into patient-provider care, where AI mediates communication without overriding human judgment.
Through studies of CLEAR, an asynchronous messaging system, it demonstrates how this configuration effectively addresses real-world constraints such as time pressure and varying health literacy levels.
The research highlights that AI's mediator affordances, including availability and neutrality, help redistribute interpretive work and reduce relational friction.
Ultimately, the paper frames AI mediation as a crucial relational infrastructure, emphasizing critical design tensions concerning power dynamics and privacy.
Technical Impact
The paper introduces a novel architectural paradigm where AI acts as a "mediator" rather than a central decision-maker, facilitating human-to-human communication.
This redefines AI's role, influencing system designs that prioritize trust and human-centered approaches, moving away from fully autonomous AI in sensitive domains like healthcare.
The concept of "mediator affordances" provided by AI, such as redistributing interpretive work and reducing relational friction, offers new insights for UX/UI design.
Specifically, leveraging AI in asynchronous messaging systems provides guidelines for designing interfaces that address practical challenges like time constraints and health literacy disparities, enhancing user experience and accessibility.
The article points out that AI's mediating role creates design tensions around power structures and privacy.
This necessitates developers to incorporate robust ethical and privacy-by-design principles when building AI systems, ensuring transparency, user control, and responsible data handling from the outset.