"I'm Not Able to Be There for You": Emotional Labour, Responsibility, and AI in Peer Support

2026-04-15

AI Summary

This study addresses the blurred boundaries of responsibility in peer support within digital environments, which lead to the excessive individualization of emotional labor and a lack of organizational support and accountability mechanisms. Through qualitative interviews and human-centered design methods, the research explores peer supporters’ motivations and perceptions of responsibility, revealing that their expectations of AI center on redistributing responsibility rather than enhancing empathic capabilities. Challenging the dominant efficiency-driven logic of AI intervention, this work proposes a responsibility-oriented design framework that reconfigures the role of AI in mental health support from a sociotechnical systems perspective, advocating for an AI-supported ecosystem grounded in shared responsibility.

Technology Category

• Humans and AI: Emotional Intelligence
• Philosophy and Ethics of AI: AI & Jobs/Labor
• Intelligent Robots: Embodied AI

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Economics, Online Markets and Human Computation: Fairness and ethical considerations in crowd work and in human-in-the-loop AI systems
• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization

Abstract

Peer support is increasingly positioned as a scalable response to gaps in mental health care, particularly in digitally mediated settings, yet what counts as peer support and how responsibility is distributed remain unevenly defined in practice. Drawing on interviews with peer supporters, we show how lived experience, moral commitment, and self-identification shape participation while blurring expectations around scope, authority, and accountability. Institutional ambiguity concentrates emotional labour, boundary-setting, and escalation of responsibility at the individual level, often without consistent organisational scaffolding. Participants evaluated AI not primarily through empathy or technical capability, but through how technologies redistribute risk, labour, and accountability within already fragile support roles. Building on these findings, we outline design futures for an AI-supported peer support ecosystem that foregrounds responsibility as a central design concern rather than treating AI as a mechanism of scale.

Problem

• peer support
• emotional labour
• responsibility
• AI
• mental health care

Innovation

• emotional labour
• responsibility
• AI ethics
• peer support
• accountability