"I'm Not Able to Be There for You": Emotional Labour, Responsibility, and AI in Peer Support
Kellie Yu Hui Sim, Kenny Tsu Wei Choo
TLDR
Examines emotional labor and responsibility in digital peer support, showing how AI is judged by its impact on risk and accountability.
Key contributions
- Identifies how lived experience and moral commitment blur expectations for peer supporters.
- Highlights how institutional ambiguity concentrates emotional labor and responsibility on individuals.
- Reveals that peer supporters evaluate AI based on its redistribution of risk, labor, and accountability.
- Proposes design futures for AI-supported peer support that prioritize responsibility over mere scalability.
Why it matters
This research is crucial for understanding the complex human factors in digital mental health support. It shifts the conversation from AI's technical capabilities to its ethical implications, particularly regarding responsibility and labor distribution. This reframing is vital for designing more equitable and sustainable AI-supported peer support.
Original 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.
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