# CharacterizationSeeking a PI for a Revolutionary Non-Profit AI App to See Depression

**URL:** <https://onscienceandacademia.org/t/characterizationseeking-a-pi-for-a-revolutionary-non-profit-ai-app-to-see-depression/2424>\
**Category:** Mad Studies Academy\
**Tags:** open-science, psychology, new-academia, new-paper\
**Created:** [June 5, 2025, 1:28pm UTC](https://onscienceandacademia.org/t/characterizationseeking-a-pi-for-a-revolutionary-non-profit-ai-app-to-see-depression/2424 "2025-06-05T13:28:39Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![Diogenix](https://avatars.discourse-cdn.com/v4/letter/d/a88e57/32.png) [@Diogenix](https://onscienceandacademia.org/u/Diogenix)\
**Post date:** [June 5, 2025, 1:28pm UTC](https://onscienceandacademia.org/t/characterizationseeking-a-pi-for-a-revolutionary-non-profit-ai-app-to-see-depression/2424/1 "2025-06-05T13:28:39Z")

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In the spirit of Mad Studies’ mission to redefine science and empowering users, I’m sharing a vision for a non-profit smartphone app that could transform psychiatric care. Research shows **AI can detect depression from facial expressions** (using just 4 minutes of video) **with accuracy effectively surpassing clinicians** , even when only trained off data sets as small as ~200 participants. A free app could make this objective, scalable tool ubiquitous, addressing concerns about stigma, treatment efficacy, and even the definition of mental states themselves. Key features:

- Initial capability: Detects depression via facial expressions, leveraging existing academic models.

- Self-Improving: **Optional user-provided depression scores** (e.g., PHQ-9) **expand the AI platform training database, boosting accuracy with each use.**

- Future expansion: **Incorporate other smart-phone accessible biomarkers** (audio, motion, pupillometry, saccades, etc.) with user consent. **Expand to anxiety, PTSD** , and more.

- Ethical model: **Run as a non-profit, user data stays protected** (including contractual protection with every user) **and user access remains free**. **Monetization through licensing algorithms to healthcare systems** funds growth without compromising privacy.

The mental health crisis is profound – costs exceed all agriculture and education expenditures combined – yet diagnostic remain subjective, placing the field atop a house of cards. This app could democratize objective insight, aligning with Mad Studies’ push for user-driven, transformative approaches.

**As the concept initiator, I’m confident in its potential, but lack the expertise to lead this one. I’m seeking a Principal Investigator or other project lead with associated research or fundraising interests.**

For-profit apps exist, but a non-profit’s trust and scale could outpace them, especially with community-driven data contributions. However, to best incubate the idea and protect from added for-profit pressure, I’m not posting this for arbitrarily large audiences. Please DM or email me eric[at]diogenix dot org.