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TribalDAOs Risk Assessment

This working document outlines key risks identified through research, use case mapping, and community engagement across our TribalDAO development process. Each risk includes real-world context and detailed mitigation strategies to help us design responsibly, reduce harm, and ensure long-term adoption and trust across whānau and Indigenous collectives.

#Risk CategoryDescriptionImpact & EvidenceMitigation Strategy
1Cultural AlignmentDAO tools may not align with tikanga, consensus decision-making, or relational authority models.
  • Seen in whānau trust kōrero and simulations where voting models feel foreign
  • Risk of communities avoiding the system if tikanga isn’t upheld
  • Co-design modules with kaumātua and hapū
  • Include Elder Advisory Councils and consensus options
  • Test governance patterns with whānau-led pilots
2Accessibility & Technical ComplexityTools like wallets and DIDs may be confusing or intimidating for whānau or elders.
  • Pilot onboarding revealed confusion around terms and flows
  • Risk of low adoption if tools feel too foreign
  • Mobile-first UI with plain language
  • Step-by-step walkthroughs
  • Community-led training and support roles
3Smart Contract RisksErrors in governance or treasury contracts could result in lost funds or broken trust.
  • Known risk in any blockchain system
  • Especially critical for taonga like whenua and shared pūtea
  • Modular contracts
  • Third-party audits
  • Test in low-risk environments
  • Emergency pause controls
4Legal and Regulatory AmbiguityDAOs and tokens are not clearly recognised under NZ law or trust structures.
  • Questions raised around trust board authority and DAO actions
  • Unclear legal standing without proper structures
  • Legal partnership with Māori tech lawyers
  • Optional legal wrappers (e.g. trust + DAO hybrid)
  • KYC-ready DID system for opt-in compliance
5Centralisation of Power or VoiceToken imbalance or contributor dominance could create governance bias.
  • Observed in simulations where active users dominated decisions
  • Risk of community disengagement
  • Multi-token model (e.g., role, community, culture)
  • Cap holdings
  • Reward active engagement
  • Publish governance stats