Sovereign by Design: A Blueprint for Federated, Consent-Based AI Systems

Part of the Deep Dive: Data Governance Webinar Series

Open source AI is often praised for transparency and scale—but too often overlooks one key question: who decides how data is governed?

This talk dives into how Tribal Nations across the U.S. are asserting sovereignty through technical infrastructure, community consent protocols, and legal frameworks—offering a vision for federated AI systems that center accountability and cultural relevance.

We’ll explore case studies including:

1. The Native BioData Consortium’s tribally governed biobank

2. The DataBack movement’s decentralized genomic sovereignty model

3. The implementation of CARE principles in AI pipelines

4. Jurisdiction-aware interoperability in public sector data sharing (e.g. BIA and NIH initiatives)

Attendees will leave with a set of reproducible patterns for embedding ethics into infrastructures well as insights into how co-creation, local governance, and sustainability can make our AI systems more just and open.

Video Transcript

Speaker: Sal Kimmich

Introduction

This talk explores patterns for building federated, consent-based AI systems through examples from genomics and tribal data sovereignty.

Key Topics Covered

1. Defining Sovereignty

Five Historical Dimensions:

  • Authority: Who holds the right to govern
  • Territory/Domain: Originally land, sea, air—now includes data, algorithms, and cyberspace
  • Autonomy: Self-governance capabilities
  • Recognition: Consent within systems
  • Revocation: The right to opt-in and opt-out

Types of Sovereignty:

  • Westphalian (1648): Nation-states recognizing each other’s borders
  • Legal: Supreme authority given to specific legal bodies
  • Popular: Derived from consent of the people
  • Relational: Indigenous nations’ inherent right to self-governance
  • Digital/Cyber: Control over digital infrastructure and data flows

2. Tribal Data Sovereignty Case Study

US Tribal Nations Context:

  • 574 federally recognized tribes
  • Legal status: “Domestically dependent nations”
  • Limited sovereignty with recognized self-governance
  • Direct federal relationships (bypassing states)

Tribal Security Grant Program (2023):

  • Sovereign-to-sovereign relationship with federal government (DHS, CISA, FEMA)
  • Unique regulatory space—more autonomous than cities/counties
  • Direct federal support with ongoing compliance requirements

3. Genomics as a Sovereignty Issue

The Consent Problem:

  • Western model: Individual informed consent
  • Indigenous model: Communal decision-making
  • Conflict creates data sovereignty violations

Havasupai Case (2024): Arizona State University collected blood samples for diabetes research, then repurposed the data without re-consent for:

  • Schizophrenia rates
  • Family-level genomic mapping
  • Human migration studies

This violated communal consent and created exploitation risks for an already vulnerable population.

Response: Native BioData Consortium (NBDC)

  • First indigenous-led nonprofit biobank in US
  • Run by indigenous scientists and tribal members
  • Operates within tribal jurisdictional bounds
  • Keeps data physically isolated (“closed data system”)

4. Four Key Patterns for Sovereign Data Infrastructure

Pattern 1: Community-Governed Infrastructure

  • Permissioned governance
  • Physical data restrictions when necessary
  • Modular permissions and auditable access logs

Pattern 2: Federated AI Pipelines

  • Decentralized learning with no raw data sharing
  • Data stays in community pods
  • Contributes to AI models through federated learning (TensorFlow Federated, PySyft)
  • Key insight: Openness ≠ centralized availability

Pattern 3: Ethical Metadata Layers

  • Data ethics files with consent tokens
  • FAIR principles (Findable, Accessible, Interoperable, Reusable)
  • CARE principles (Collective benefit, Authority to control, Responsibility, Ethics)
  • Consent tokens queryable via APIs
  • Policy embedded in infrastructure

Pattern 4: Jurisdiction-Aware APIs

  • FPIC flags (Free, Prior, Informed Consent)
  • Policy-aware endpoints
  • Transparency for developers about data origins

5. Zero Trust Data Infrastructure

Core Concepts:

  • Trust Boundaries: Lines where trust levels change between components
  • Verifiable Trust: Replacing institutional trust with cryptographic proof
  • Confidential Computing: Protecting data during use (Intel SGX, AMD SEV, ARM CCA)

Nation-to-Nation Infrastructure:

  • Requires secure isolation of workloads
  • Workload identity constrained in time and execution
  • Example: Italy-Switzerland-France sovereign cloud collaboration

Requirements for Sovereign Cloud:

  • Data sovereignty (data protected in use)
  • Operational sovereignty (transparency into platform operations)
  • Technical sovereignty (continuous auditing with extended supervision)

6. Recommendations

For Data Commons:

  • Enforceable residency guarantees
  • Operator separation
  • Trusted execution environments

For Open Source:

  • Transparency as the essential pillar
  • Zero trust boundaries for sovereign entity engagement
  • Consent as an architecture problem (APIs, modular design, smart defaults)

Conclusion

Building sovereign-by-design systems requires embedding governance into infrastructure, not treating it as an add-on. The future of secure, federated systems depends on moving from operational trust to cryptographically verifiable trust while respecting diverse sovereignty models.

Resources Mentioned:

  • Book: Code, Chips and Control (pre-order available)
  • Indigenous Data Sovereignty Network Summit (2026)