I’m working on Sovereign Mohawk (Sov-MOHAWK) , a platform designed to let hospitals train oncology AI models globally without moving patient data. I have integrated a Post-Quantum Cryptography stack and a 55.5% Byzantine resilience threshold, but I’m looking for specific community feedback on the compliance and law side:
- Automated DPIA: We built a generator that maps technical Federated Learning logs to GDPR Art. 35 . Does this actually move the needle for your legal teams, or is manual review still the only way?
- The “Thinker Clause”: We use policy-gated admissions to protect minority data. How should we mathematically balance “global accuracy” vs. “rare disease representation”?
- Audit Transparency: Our dashboard features a live audit stream. Is this level of telemetry enough to satisfy a HIPAA auditor, or are we missing a critical “paper trail” link? I’d love for the experts here to poke holes in our governance logic. 👉 Explore the Sovereign Mohawk Repo & Demo Click on Github-Pages for live demo. #AI #HealthTech #Privacy #GDPR #Cryptography #SovereignMohawk #OpenSource submitted by /u/Famous_Aardvark_8595
Originally posted by u/Famous_Aardvark_8595 on r/ArtificialInteligence
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