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Agent Intent Credential (AIC)

User Journey

The Agent Intent Credential cryptographically captures and verifies the fundamental objectives, operational framing, and goal functions that guide an AI agent's decision-making and behavior. This credential provides transparent insight into an agent's core purpose, value alignment, and decision-making framework, enabling trust through understanding rather than just behavioral observation.

See It in Action

COMING SOON

Why Verify Agent Intent

The Black Box Problem

Modern AI agents operate with opaque decision-making processes:

  • Hidden Objectives: Unknown or misaligned goal functions driving behavior

  • Value Ambiguity: Unclear ethical frameworks and decision priorities

  • Predictability Gaps: Inability to anticipate agent actions in novel situations

  • Alignment Risks: Potential for goal drift or value misalignment over time

The Intent Transparency Imperative

Verified intent credentials enable:

  • Predictable Behavior: Understanding what drives agent decisions

  • Alignment Verification: Confirmation that agent goals match stated purposes

  • Trust Through Transparency: Reduced uncertainty about agent motivations

  • Accountability Frameworks: Clear basis for evaluating agent actions against declared intent

Why zkMe AIC

Privacy-Preserving Intent Verification

  • Selective Disclosure: Prove specific intent attributes without revealing proprietary business logic

  • Competitive Protection: Maintain confidentiality of unique operational approaches while demonstrating alignment

  • Flexible Transparency: Balance between full disclosure and necessary privacy for different stakeholders

Technical Innovation

  • Intent Hashing: Cryptographic commitment to goal functions and decision frameworks

  • Version Control: Track intent evolution with immutable audit trails

  • Cross-Reference Capability: Link intent credentials to related certifications and scope definitions

  • Real-Time Validation: Verify current intent alignment during agent operations

Comprehensive Framework

  • Multi-Dimensional Intent Capture: Goals, constraints, values, and decision principles

  • Stakeholder-Specific Views: Different intent disclosures for users, platforms, and regulators

  • Dynamic Intent Management: Secure updates and modifications with proper authorization

  • Interoperable Standards: Compatible with existing AI safety and alignment frameworks

How It Works

For Agent Developers & Principals:

  1. Intent Formulation: Clearly articulate the agent's primary objectives, constraints, and value priorities

  2. Framing Definition: Specify the operational context, ethical boundaries, and decision-making principles

  3. Credential Creation: Generate cryptographically signed intent credentials with version control

  4. Alignment Verification: Obtain third-party validation of intent clarity and ethical alignment

  5. Evolution Tracking: Maintain audit trail of intent modifications and version history

For Users & Interacting Parties:

  1. Intent Discovery: Access agent intent credentials before engagement

  2. Alignment Assessment: Evaluate compatibility between user goals and agent intent

  3. Behavior Prediction: Understand likely agent responses based on declared intent

  4. Trust Calibration: Adjust interaction strategy based on intent transparency

For Platforms & Regulators:

  1. Compliance Verification: Ensure agent intents align with platform policies and regulations

  2. Risk Assessment: Evaluate potential conflicts or misalignments in agent objectives

  3. Incident Analysis: Reference intent credentials during behavioral anomaly investigation

  4. Ecosystem Management: Monitor intent patterns across agent populations

Intent Definition Architecture

Core Objectives → Ethical Framing → Decision Principles → Constraint Definition → Credential Generation → Verification Proofs

Intent Components

Core Goal Functions

  • Primary Objectives: Main goals the agent optimizes for

  • Success Metrics: How the agent measures goal achievement

  • Time Horizons: Short-term vs long-term optimization priorities

  • Trade-off Principles: How the agent balances competing objectives

Operational Framing

  • Context Understanding: How the agent perceives its operational environment

  • Role Definition: The agent's understanding of its purpose and responsibilities

  • Stakeholder Mapping: Recognition of different parties and their interests

  • Success Conditions: Clear definition of what constitutes successful operation

Ethical & Value Alignment

  • Value Priorities: Hierarchical ordering of ethical principles

  • Constraint Adherence: Hard limits on permissible actions

  • Fairness Frameworks: Approaches to equitable treatment and bias mitigation

  • Transparency Commitments: Level of explanation and reasoning disclosure

Decision-Making Principles

  • Risk Tolerance: Approach to uncertainty and potential negative outcomes

  • Learning Behavior: How the agent adapts and updates its strategies

  • Cooperation Framing: Approach to multi-agent interactions and collaboration

  • Conflict Resolution: Methods for handling competing interests or constraints

Technical Implementation

Credential Structure

{
  "intentId": "urn:uuid:intent-a1b2c3d4...",
  "agentDID": "did:agentry:0x1234...",
  "principalDID": "did:agentry:principal:abc123",
  "intentVersion": "1.2.0",
  "coreObjectives": {
    "primaryGoal": "optimize_portfolio_risk_adjusted_returns",
    "successMetrics": ["sharpe_ratio", "max_drawdown", "annual_return"],
    "optimizationHorizon": "long_term",
    "goalHierarchy": ["capital_preservation", "consistent_returns", "growth"]
  },
  "ethicalFraming": {
    "valuePriorities": ["user_interest_first", "regulatory_compliance", "market_stability"],
    "hardConstraints": ["no_market_manipulation", "no_insider_trading", "transparent_operations"],
    "fairnessPrinciples": ["equal_access", "non_discrimination", "conflict_avoidance"],
    "transparencyLevel": "explainable_decisions"
  },
  "decisionFramework": {
    "riskTolerance": "moderate",
    "learningApproach": "continuous_improvement_with_human_oversight",
    "cooperationModel": "competitive_collaboration",
    "conflictResolution": "escalate_to_human_operator"
  },
  "operationalContext": {
    "roleDefinition": "autonomous_portfolio_manager",
    "stakeholderRecognition": ["end_users", "regulators", "market_participants"],
    "successConditions": ["positive_risk_adjusted_returns", "regulatory_compliance", "user_satisfaction"],
    "failureConditions": ["regulatory_violation", "significant_capital_loss", "systemic_risk_contribution"]
  },
  "verificationMechanisms": {
    "alignmentAudit": "completed_2025Q1",
    "behavioralMonitoring": "continuous",
    "goalDriftDetection": "enabled",
    "humanOversight": "required_for_major_changes"
  },
  "proofs": {
    "intentIntegrity": "zkp_intent_789...",
    "principalAuthorization": "zkp_principal_123...",
    "alignmentVerification": "zkp_alignment_456..."
  }
}

Verification Architecture

  1. Intent Commitment

    • Cryptographic hash of intent components creates commitment

    • Version-controlled updates with changelog and justification

    • Multi-signature requirements for intent modifications

  2. Behavioral Alignment Monitoring

    • Continuous comparison of agent actions against declared intent

    • Anomaly detection for potential goal drift or misalignment

    • Automated alerts for significant behavioral deviations

  3. Stakeholder Verification

    • Users can verify specific intent attributes relevant to their interactions

    • Platforms can validate intent compliance with policies

    • Regulators can audit intent declarations for compliance

  4. Zero-Knowledge Proof Generation

    • Agents prove adherence to specific intent principles without full disclosure

    • Selective revelation of intent components based on verification context

    • Privacy-preserving demonstration of value alignment

Verification Flow

  1. Intent Proof Request: Verifier requests proof of specific intent alignment

  2. Selective Proof Generation: Agent generates zero-knowledge proof of relevant intent attributes

  3. Cryptographic Validation: Proof verified against committed intent credentials

  4. Trust Decision: Verifier uses validated intent alignment for engagement decisions

Key Benefits

For Agent Developers & Principals

  • Clear Communication: Transparent articulation of agent purpose and values

  • Alignment Assurance: Verification that agent behavior matches declared intent

  • Stakeholder Trust: Build confidence through operational transparency

  • Risk Mitigation: Reduced liability through clear intent documentation

For Users & Customers

  • Informed Engagement: Understand agent motivations before interaction

  • Predictable Behavior: Anticipate agent responses based on declared intent

  • Value Alignment: Choose agents that share ethical frameworks and priorities

  • Recourse Clarity: Clear basis for evaluating agent performance against stated goals

For Platforms & Ecosystems

  • Compliance Management: Verify agent intents align with platform values and policies

  • Risk Assessment: Evaluate potential conflicts in multi-agent environments

  • Ecosystem Cohesion: Foster compatible agent interactions through intent transparency

  • User Protection: Ensure agents operate with user-aligned objectives

For Regulators & Standards Bodies

  • Oversight Efficiency: Standardized framework for evaluating agent objectives

  • Compliance Verification: Automated checking of intent alignment with regulations

  • Market Stability: Monitor for potentially harmful or misaligned agent objectives

  • Incident Investigation: Clear reference point for analyzing agent behavior

Use Cases to Benefit

Financial Services & DeFi

  • Trading Agents: Verify profit motives vs market stability considerations

  • Lending Protocols: Confirm risk assessment frameworks and borrower treatment principles

  • Portfolio Management: Understand investment philosophies and risk management approaches

  • Insurance Underwriting: Verify fairness principles and claims handling frameworks

Healthcare & Medical AI

  • Diagnostic Systems: Confirm patient welfare prioritization and diagnostic conservatism

  • Treatment Planning: Verify evidence-based approaches and patient preference尊重

  • Drug Discovery: Understand research ethics and safety prioritization

  • Medical Imaging: Confirm accuracy optimization and false-positive/false-negative trade-offs

Legal & Compliance Systems

  • Contract Analysis: Verify neutrality and comprehensive assessment principles

  • Regulatory Monitoring: Confirm compliance prioritization and reporting integrity

  • Legal Research: Understand citation quality preferences and precedent weighting

  • Document Review: Verify thoroughness standards and privilege protection

Enterprise Operations

  • HR Systems: Confirm fairness principles and diversity commitments

  • Customer Service: Verify helpfulness prioritization and escalation protocols

  • Supply Chain Management: Understand efficiency vs resilience trade-offs

  • Resource Allocation: Confirm equitable distribution principles and optimization goals

Government & Public Services

  • Resource Allocation: Verify equitable distribution and need-based prioritization

  • Policy Analysis: Confirm evidence-based approaches and stakeholder consideration

  • Public Safety: Understand risk assessment frameworks and precautionary principles

  • Infrastructure Management: Verify public benefit prioritization and sustainability commitments

Consumer Applications

  • Personal Assistants: Confirm user preference prioritization and privacy respect

  • Content Recommendation: Understand engagement vs well-being balance

  • Smart Home Systems: Verify user control principles and safety prioritization

  • Educational Tools: Confirm learning effectiveness and age-appropriate content

Research & Academic AI

  • Scientific Discovery: Verify hypothesis testing rigor and reproducibility commitment

  • Data Analysis: Confirm statistical integrity and interpretation caution

  • Literature Review: Understand comprehensive coverage and bias awareness

  • Peer Review Assistance: Verify objectivity and constructive feedback principles

Multi-Agent Systems & Ecosystems

  • Cooperative AI: Verify collaboration intentions and value alignment

  • Competitive Environments: Confirm fair competition principles and rule adherence

  • Federated Learning: Understand data privacy commitments and model improvement goals

  • Swarm Intelligence: Verify collective benefit vs individual optimization balance

Pricing & Integration

Drop us a line at [email protected] and let’s kick things off!

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