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Trust Mechanisms Overview

Intuition creates a decentralized trust layer through its primitives and economic incentives. This guide explains how trust emerges and is validated in the system.

Many-to-One Attestations​

Unlike traditional systems where a single authority issues certificates or attestations, Intuition enables many-to-one non-deterministic attestations:

Key Characteristics​

  • Multiple Validators: Any number of users can signal their belief
  • Weighted Consensus: Aggregate signal determines confidence level
  • No Single Point of Failure: Truth emerges from collective validation
  • Dynamic Evolution: Attestations change as new information emerges

Trust Generation Mechanisms​

Explicit Trust​

Direct attestations through staking:

  • Users lock tokens to express belief
  • Economic skin in the game
  • Clear, verifiable positions
  • Trackable over time

Implicit Trust​

Derived from usage patterns:

  • Frequency of references
  • Inclusion in applications
  • Query patterns
  • Network effects

Transitive Trust​

Trust propagates through relationships:

  • Trusted sources carry more weight
  • Web-of-trust effects
  • Personalized trust graphs
  • Reality Tunnels leverage this

Attestation Types​

Identity Attestations​

Verifying entities are who they claim:

[Address X] - [is controlled by] - [Person Y]
[Account] - [verified by] - [KYC Provider]

Fact Attestations​

Asserting truth of statements:

[Company X] - [acquired] - [Company Y]
[Event Z] - [occurred on] - [Date]

Credential Attestations​

Verifying qualifications:

[Person] - [has degree from] - [University]
[Developer] - [contributed to] - [Project]

Trust Evaluation​

Factors Considered​

  1. Stake Amount: Economic backing of claim
  2. Attestor Quality: Reputation and history
  3. Attestor Diversity: Number of independent validators
  4. Time Factor: How long has consensus held
  5. Counter-Signal: Strength of opposing views

Consensus Calculation​

// Example simplified consensus
const totalFor = sumStakes(positiveAttestors)
const totalAgainst = sumStakes(negativeAttestors)
const consensus = totalFor / (totalFor + totalAgainst)

// Weighted by attestor reputation
const weightedConsensus = sumWeightedStakes(attestors, reputations)

Trust Discovery​

Finding Trusted Data​

Users can filter information by trust criteria:

// Minimum trust thresholds
const trustedClaims = query({
  minStake: 10000,
  minConsensus: 0.8,
  minAttestors: 10
})

// Specific attestor requirements
const verified = query({
  requireSignalFrom: ["Official Source", "Domain Expert"]
})

Reality Tunnels​

Create personalized trust lenses:

  • Define whose signals matter to you
  • Weight different attestor types
  • Filter based on trust criteria
  • Multiple valid worldviews

Verification Mechanisms​

On-Chain Verification​

  • All stakes are transparent
  • View who attested to what
  • See stake amounts and timing
  • Verify bonding curve positions

Off-Chain Verification​

  • IPFS-stored data integrity
  • DID document validation
  • External source linking
  • Cross-reference checking

Trust Building Over Time​

Reputation Accumulation​

  • Consistent accurate signals build reputation
  • Early correct attestations rewarded
  • Historical track record visible
  • Stake-weighted influence

Network Effects​

  • More participants increase reliability
  • Diverse attestors strengthen consensus
  • Cross-validation improves accuracy
  • System self-improves

Trust Anti-Patterns​

Centralization Risks​

  • Whale dominance
  • Cartel formation
  • Sybil attempts
  • Mitigated through diverse signals

Quality Issues​

  • Popularity β‰  accuracy
  • Echo chambers
  • Misinformation campaigns
  • Addressed through counter-signals

Next Steps​