Young people's perceptions and recommendations for conversational generative artificial intelligence in youth mental health

2026-04-16 · Source: cs.AI updates on arXiv.org · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Human-Computer Interaction · Depth: Expert, quick

Summary

A study explored young people's perceptions and recommendations for conversational generative AI (genAI) chatbots in youth mental health. Researchers examined the Mental health Intelligence Agent (Mia), a genAI chatbot initially designed for Australian youth service professionals. Through co-design and online workshops with 32 young participants, the study gathered insights into their attitudes and needs. Four key themes emerged: "Humanising AI without dehumanising care," "I need to know what's under the hood," "Right tool, right place, right time?," and "Making it mine on safe ground." This work provides critical implications for integrating genAI chatbots into youth mental health services and informs the ethical design, development, implementation, and governance of such tools for consumers.

Key takeaway

For AI Product Managers developing mental health applications, understanding youth perspectives is crucial. You should prioritize co-design with young users to ensure genAI chatbots are perceived as helpful, transparent, and safe. Focus on features that humanize AI interactions without diminishing the value of human care, and provide clear information about the AI's capabilities and limitations to build trust and ensure appropriate use.

Key insights

Young people desire transparent, humanized, and customizable genAI chatbots for mental health support.

Principles

• AI in mental health must complement, not replace, human care.
• Transparency in AI functionality builds user trust.
• Contextual appropriateness is key for AI tool deployment.

Method

The study used co-design and online workshops with 32 young people to explore perceptions of genAI chatbots and develop recommendations for reconceptualizing Mia for consumers.

In practice

• Integrate user co-design into AI development.
• Prioritize explainability in AI mental health tools.
• Offer personalization options for chatbot interactions.

Topics

• Conversational AI
• Youth Mental Health
• GenAI Chatbots
• Co-design
• Human-Computer Interaction

Best for: AI Product Manager, AI Scientist, Research Scientist, AI Ethicist

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Editorial summary, takeaway, and curation by AIssential. Original article published by cs.AI updates on arXiv.org.