cool. i like what you've done here with a virtual panel that can answer questions ... i have similar ideas for kabuki syndrome (currently: https://www.thekabukipapers.org). talk? marstall at gmail.
Thats the main thing. I think that Ai-native governance by domain experts is how AI reaches its full potential. Not in theory but in terms of the value it delivers to populations via outcomes.
AI-native Governance is like irrigation for the outcomes populations want to achieve, starts with intents; executed on by programs that use protocols as guardrails. This is a gross oversimplification of the process but based what i see from your work you will get the abstract.
Examples -
dietmanager.com - RDN governance
crohns.ai - AGA (MD/GI) governance
<city>.us.codify.city - City council Governance
https://san-francisco.ca.us.codify.city/
https://new-york.ny.us.codify.city/
http://chicago.il.us.codify.city/
Each codify.* is a PDA [Public Domain Agent] - that gets delegated intents per request and has to manage its own "deal" - its also managed democratically via ontology and downline policies set by the experts in said field and has feedback loop to verify/optimize policy outcomes.
This concept applies to everything IMO, and I cannot say I fully understand it but im absolutely obsessed with the exploration of the idea; again - in practice not theory. I have real outcomes in healthcare, education and housing.
The jobs to harvest the corpus needed to create each agent is not scaling well.
Note: crohns.ai: 3,948 gastroenterologists, dietmanager.com: 1,752 RDNs