Algorithmic care and health equity: affective labor in assistive platforms for visual disability communities

Introduction Digital assistive technologies are transforming social inclusion for visually impaired individuals, yet their public health implications remain contested. This study aims to examine how interface cues and platform algorithms shape affective labor in assistive technologies, and what implications this has for health equity. Focusing on the transnational platform “Be My Eyes,” we analyzed how technology-mediated caregiving reshapes social support networks and impacts health equity through affective labor. Methods The study employed digital ethnography. Semi-structured interviews were conducted with 11 volunteers who heavily utilized Be My Eyes. In addition, the respondents’ help diaries were analysed. Results Four interlinked themes emerged. (1) Feeling rules: interface cues (urgency banners, countdowns, re-matching scripts, default anonymity, notification cadence) specify when to step in, how fast to act, and what tone to use; (2) Surface acting: volunteers manage voice, wording, and pacing to keep calls steady under time pressure; (3) Deep acting: stance shifts from “savior” to collaborator, using shared metaphors and pacing to co-construct meaning; and (4) Emotional dissonance: speed cues, metrics, and modality limits (e.g., tactile gaps) can pull felt emotion and displayed composure apart. Conclusion Our findings critique “algorithmic altruism,” wherein empathy is rendered computable via metrics such as response speed and closure, and highlight hidden public health risks, such as emotional exhaustion in volunteers. We identify scope-bounded design levers—tempo flexibility for openings/closings, minimal opt-in identity cues to allow warmth without losing anonymity, and light relational continuity—to support responsiveness and emotional integrity. We also mark boundary conditions (task type, modality demands, cultural fit). This study urges a shift toward sensory-diverse, equity-oriented design and policy protections for affective labor, advancing health equity by centering disabled agency rather than perpetuating market-driven disparities. These insights complement Sustainable Development Goals (SDG 3 and SDG 10) by specifying interface-level mechanisms through which technologies can bridge, rather than widen, inequalities.