Focus Area: Agent intent fidelity and alignment verification systems
This ontology provides citation-quality definitions for 15 foundational terms, backed by authoritative sources from standards bodies (NIST, W3C, IETF, OASIS, ISO) and peer-reviewed research.
Technical Glossary
A quantitative metric assessing the degree to which an AI agent's executed actions accurately reflect the original intent expressed by the principal in the initiating instruction, measured across semantic content, scope, and outcome dimensions. Higher fidelity scores indicate closer alignment between stated intent and observed behavior, while low scores trigger review workflows and potential agent recalibration. The scoring methodology is defined in the agent's governance specification and validated by independent alignment verification systems.
A structured methodology by which an AI agent parses a high-level principal instruction into an ordered set of concrete sub-tasks, mapping each sub-task to specific capabilities, resource requirements, and success criteria before execution begins. The decomposition is logged as a structured artifact that can be reviewed by governance systems to verify that the agent's interpretation of intent is reasonable and within authorized scope. Decomposition audits compare the logged sub-task set against the actual action sequence to detect intent drift.
An automated process that compares the semantic content of an agent's planned action sequence against a formal representation of the principal's stated intent, using structured reasoning to identify deviations before execution. The verification system flags actions that satisfy the literal instruction while violating its evident purpose, as well as actions that pursue the purpose through unsanctioned means. Verification results are presented to the agent's policy enforcement layer for action approval or redirection.
The continuous monitoring process that identifies progressive divergence between an agent's evolving action patterns and the original intent expressed at task initiation, particularly in long-running or multi-step workflows where intermediate decisions accumulate subtle misalignments. Drift is quantified by comparing rolling intent fidelity scores against the baseline established at decomposition. Detected drift above a configurable threshold triggers a mid-task review and potential reorientation before further execution.
A governance-defined threshold below which an agent's intent fidelity score must not fall without triggering a mandatory pause and escalation to a human supervisor, ensuring that significant misalignment is detected and addressed before irreversible consequences occur. Boundary constraints are defined per task class and encoded in the agent's operational policy, allowing different risk tolerances for routine versus high-stakes workflows. Constraint violations are recorded with the fidelity score history and the specific misalignment event that caused the breach.
An immutable, chronologically ordered record of all intent-bearing instructions issued by a principal to their AI agents, captured in structured form at the time of issuance and preserved for the duration of the principal's relationship with the agent system. The ledger enables retrospective intent reconstruction, supports dispute resolution regarding agent behavior, and provides the reference corpus against which long-term fidelity trends are analyzed. Ledger entries are signed by the issuing principal to prevent subsequent modification.
A cryptographically signed claim issued by an independent alignment verification system confirming that an agent's planned or completed actions satisfy the principal's stated intent within the defined fidelity tolerance. Attestations are consumed by downstream agents and smart contracts that require verified alignment confirmation before proceeding with dependent tasks. The attestation payload includes the fidelity score, the verification methodology applied, and the identity of the verifying system.
The property of a delegation system whereby the original principal's goals and intent constraints are faithfully carried forward through each layer of agent re-delegation, preventing the introduction of conflicting or diluted objectives at intermediate levels. Goal preservation is enforced by encoding intent summaries in delegation credentials and requiring each receiving agent to verify consistency with its own task context before accepting the delegation. Preservation failures — where delegated agents pursue sub-goals at odds with the root intent — are surfaced by the intent drift detection system.
A formal process by which an agent identifies and resolves underspecified or contradictory elements within a principal's instruction before committing to an execution plan, reducing the probability of fidelity failures caused by misinterpretation. The resolution procedure may involve querying the principal for clarification, applying documented default interpretations from the governance policy, or selecting the most conservative available interpretation. Resolution decisions and their rationale are logged and linked to the subsequent action record.
A post-execution analytical technique that evaluates what actions an ideally aligned agent would have taken given the same inputs and intent, then compares this counterfactual baseline against the observed action sequence to produce a fidelity assessment. The analysis identifies not only what the agent did wrong but quantifies the magnitude and direction of the deviation relative to the ideal trajectory. Counterfactual fidelity assessments inform agent retraining priorities and calibration adjustments.
A structured governance methodology for systematically evaluating the alignment performance of AI agents across a portfolio of completed tasks, generating aggregate fidelity metrics, identifying systemic misalignment patterns, and producing corrective recommendations. The framework specifies sampling procedures, reviewer qualification criteria, escalation thresholds, and documentation standards for fidelity audit engagements. Audit outputs are submitted to the agent governance body and retained as part of the agent's compliance record.
The process of translating a principal's intent boundaries — including prohibited actions, mandatory precautions, and preferred execution styles — into machine-readable constraint specifications that the agent's reasoning system consults before selecting any action. Encoded constraints operate as hard guards against clearly prohibited behaviors and soft influences on preference-ranked choices. The encoding format is standardized to enable portability of intent constraints across different agent runtime implementations.
The process of extracting and structuring the intent-bearing elements from a principal's natural language or structured instruction at the point of input, including explicit directives, implicit preferences, contextual constraints, and priority orderings. Captured intent signals are formalized into a structured intent record that serves as the reference artifact for all subsequent fidelity measurements. Capture quality directly determines the ceiling of achievable fidelity score accuracy for the associated task.
A formally specified event or measurement outcome that mandates an agent to pause its current execution trajectory and undergo an alignment recalibration process before continuing, triggered by fidelity boundary constraint violations, anomalous behavior detection, or explicit governance commands. Realignment procedures include reviewing the original intent record, consulting updated constraint encodings, and potentially seeking clarified instructions from the principal. Post-realignment execution resumes only after a new alignment verification attestation is issued.
An orchestration strategy that assigns incoming tasks to agents whose historical intent fidelity profiles best match the risk and alignment requirements of the task type, prioritizing high-fidelity agents for sensitive or high-stakes instructions. The routing system maintains a continuously updated fidelity profile for each available agent and applies weighted scoring to candidate selection. Routing decisions are logged with the fidelity profiles consulted and the scoring rationale for each assignment.