PS-12Healthcare & Well-being
MindBridge
AI-Assisted Student Mental Well-Being Support and Escalation
SDG 3SDG 4
The challenge
Students experiencing sustained stress, isolation or emotional difficulty may not know when or how to seek support, while institutions need a way to provide low-friction resources without turning normal emotions into diagnoses. Build a privacy-first well-being support system that uses voluntary check-ins or journaling signals to identify broad support needs, recommend appropriate self-help or campus resources and escalate only according to clearly defined safety rules. The design must be transparent that it is not a therapist or diagnostic tool and must minimise collection of sensitive data.
What a working submission needs
Develop a prototype with consent-based check-ins, a simple well-being trend view, explainable support categories, curated resource recommendations and a user-controlled escalation pathway.
Demonstrate privacy settings and safe handling of high-risk language using synthetic scenarios.
Stretch goals
multilingual interaction, appointment/resource availability or anonymous institutional trend analytics with strong aggregation.
Optional. A working core counts for more than feature count.Suggested stack
Web/mobile application, AI/ML models, a mapping or dashboard interface, and open APIs as appropriate to the problem.
Scope and responsibility
Healthcare, safety and public-sector challenges are decision-support tools, not autonomous clinical, legal, emergency-command or enforcement systems. Name your prototype’s limitations in the demo. Judging weighs a working core, justified use of AI, technical quality, real-world impact and responsible design above feature count.
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