Serve-AI is the public-interest AI track at Serve IT (Laurie McRobbie Serve IT Nonprofit Clinic) (PIT-UN, a US public-interest technology university network). The goal is practical: help partners adopt generative tools without breaking trust or accessibility.
Licensing (loud)
Serve-AI project materials are CC BY-SA 4.0. Credit Serve-AI / ServeIT Clinic (IU Luddy). Jade is not sole copyright owner of upstream SERVE-AI materials.
- Public page: serveit.luddy.indiana.edu/serve-ai
- Primary IU repo: github.iu.edu/serveit-dev/SERVE-AI (IU login may be required)
- Public accessibility extension: zhao-langxi/serveit-accessibility (CC BY-SA 4.0)
How it connects
Clinic accessibility practice and Madrid outsider-friction notes share one instinct: treat friction as a first-class design input, not a post-launch patch. See ServeIT and the research note.
Long-term adoption (honest framing)
Serve-AI’s public goal is practical help for community organisations over time ... accessibility alongside automation, not a demo-week bolt-on. Growth of AI capability does not automatically mean inclusion: staff still need to review, disclose, override, and maintain AI-touched workflows without a specialist on permanent retainer. That rhyme shows up in Jade’s independent writeups on systems friction and staff-maintainable handoffs. Those notes are reflective portfolio analysis ... not Serve-AI policy documents and not forecasts with invented growth rates.