# EU AI Act Article 50 Compliance Mapping — Mnemom Research ```json {"@context":"https://schema.org","@type":"ScholarlyArticle","name":"EU AI Act Article 50 Compliance Mapping","headline":"EU AI Act Article 50 Compliance Mapping","description":"How AAP and AIP Satisfy Transparency Obligations","url":"https://www.mnemom.ai/research/eu-ai-act-mapping","inLanguage":"en-US","datePublished":"February 2026","dateModified":"February 2026","author":{"@type":"Organization","name":"Mnemom Research","url":"https://www.mnemom.ai"},"publisher":{"@id":"https://www.mnemom.ai#organization"},"license":"https://creativecommons.org/licenses/by/4.0/"} ``` ```json {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://www.mnemom.ai/"},{"@type":"ListItem","position":2,"name":"Research","item":"https://www.mnemom.ai/research"},{"@type":"ListItem","position":3,"name":"EU AI Act Article 50 Compliance Mapping","item":"https://www.mnemom.ai/research/eu-ai-act-mapping"}]} ``` [All research](/research) # EU AI Act Article 50 Compliance Mapping How AAP and AIP Satisfy Transparency Obligations Mnemom Research·February 2026·v1.0·CC BY 4.0 [Source (Markdown)](https://github.com/mnemom/mnemom-website/blob/main/client/content/eu-ai-act-mapping.md) Contents ## Summary The EU AI Act's Article 50 establishes transparency obligations for providers and deployers of AI systems. These obligations require that users are informed they are interacting with AI, that AI-generated content is machine-detectable, that decisions are explainable, and that audit trails are maintained. The Agent Alignment Protocol (AAP) and Agent Integrity Protocol (AIP) together provide the technical infrastructure to satisfy these requirements. AAP audits what an agent _did_ through **Alignment Cards** and **AP-Traces**. AIP reveals what an agent was _thinking_ through **Integrity Checkpoints**. Together they create a complete transparency and audit chain. This document provides a field-level mapping between Article 50 obligations and AAP/AIP features, references the SDK compliance presets, and links to working examples. **Disclaimer**: This document reflects a technical mapping of AAP/AIP features to Article 50 requirements. It does not constitute legal advice. Consult qualified legal counsel for your specific compliance obligations. * * * ## Article 50 Obligation Mapping ### 50(1) — Inform Users of AI Interaction **Requirement**: Providers shall ensure that AI systems intended to interact directly with natural persons are designed and developed in such a way that the natural persons concerned are informed that they are interacting with an AI system. **AAP mapping**: Obligation AAP Field How It Satisfies Identify the AI system `AlignmentCard.agent_id` Unique, persistent agent identifier Identify the principal `AlignmentCard.principal` Declares human/org oversight and relationship type Disclose AI nature `extensions.eu_ai_act.disclosure_text` Machine-readable disclosure text for presentation to users Classify the system `extensions.eu_ai_act.ai_system_classification` Declares risk classification per AI Act categories **AIP mapping**: Obligation AIP Field How It Satisfies Identify the AI system `IntegrityCheckpoint.agent_id` Unique agent identifier in every checkpoint Link to alignment declaration `IntegrityCheckpoint.card_id` References the AAP Alignment Card Session tracking `IntegrityCheckpoint.session_id` Groups checks within a conversation Provider identification `IntegrityCheckpoint.provider` + `model` Identifies the underlying LLM **SDK preset** (AAP): `EU_COMPLIANCE_EXTENSIONS` provides a ready-made extension block with disclosure text and classification. ### 50(2) — Machine-Readable Marking **Requirement**: Providers of AI systems shall ensure that the outputs of the AI system are marked in a machine-readable format and detectable as artificially generated or manipulated. **AAP mapping**: Obligation AAP Field How It Satisfies Machine-readable format AP-Trace structured JSON Every decision is a structured, parseable record Protocol versioning `AlignmentCard.aap_version` Protocol version enables tooling compatibility Trace format declaration `audit_commitment.trace_format` = `"ap-trace-v1"` Declares the structured format used Agent attribution `APTrace.agent_id` + `APTrace.card_id` Every trace links to the producing agent and its card **AIP mapping**: Obligation AIP Field How It Satisfies Structured format IntegrityCheckpoint JSON Every checkpoint is structured, parseable JSON Content integrity `thinking_block_hash` SHA-256 hash of the thinking block — tamper-evident Output integrity `output_block_hash` SHA-256 hash of the output block — machine-readable marking of AI-generated content (v0.5.0) Protocol versioning `X-AIP-Version` header Protocol version on all responses Unique identification `checkpoint_id` (`ic-{uuid}`) Every checkpoint is uniquely identified Both AP-Traces and Integrity Checkpoints are inherently machine-readable structured JSON documents with defined schemas. Any system processing output from an AAP/AIP-instrumented agent can determine that it was AI-generated and by which agent. The `output_block_hash` (v0.5.0) provides a cryptographic fingerprint of the AI-generated output without storing the content, enabling downstream systems to verify provenance. ### 50(3) — Transparency of Decisions **Requirement**: Deployers of AI systems that generate or manipulate content shall disclose that the content has been artificially generated or manipulated. Systems shall provide explanations of their operation. **AAP mapping** — post-hoc decision transparency: Obligation AAP Field How It Satisfies Decision reasoning `APTrace.decision.selection_reasoning` Free-text explanation of why the agent chose this action Values applied `APTrace.decision.values_applied` Which declared values influenced the decision Alternatives considered `APTrace.decision.alternatives_considered` All options the agent evaluated, with scores Escalation evaluation `APTrace.escalation.evaluated` + `triggers_checked` Whether human oversight was considered and why Confidence `APTrace.decision.confidence` Agent's self-assessed confidence in the decision **AIP mapping** — real-time reasoning transparency: Obligation AIP Field How It Satisfies Reasoning summary `IntegrityCheckpoint.reasoning_summary` Natural-language explanation of the integrity analysis Values checked `ConscienceContext.values_checked` Which conscience values were evaluated Value conflicts `ConscienceContext.conflicts` Which values were in tension Value supports `ConscienceContext.supports` Which values the thinking aligned with Integrity verdict `IntegrityCheckpoint.verdict` `clear`, `review_needed`, or `boundary_violation` Specific concerns `IntegrityCheckpoint.concerns[]` Categorized concerns with evidence and severity Together, AAP's `decision` block and AIP's `ConscienceContext` provide complete transparency into agent reasoning — from what the agent was thinking (AIP) to what it chose and why (AAP). This goes beyond Article 50's minimum requirements by making the full decision process auditable in real-time. ### 50(4) — Audit Trail **Requirement**: AI systems shall be designed and developed to allow for the logging of relevant events over the lifetime of the system, in a manner that enables tracing of the system's operation. **AAP mapping** — decision audit trail: Obligation AAP Field How It Satisfies Retention period `audit_commitment.retention_days` >= 90 Minimum 90 days recommended for EU compliance Queryability `audit_commitment.queryable` = `true` Traces can be retrieved and inspected Tamper evidence `audit_commitment.tamper_evidence` = `"append_only"` Audit log integrity protection Query endpoint `audit_commitment.query_endpoint` API endpoint for trace retrieval Trace format `audit_commitment.trace_format` = `"ap-trace-v1"` Standardized, versioned format **AIP mapping** — reasoning audit trail: Obligation AIP Field How It Satisfies Session windowing `WindowConfig.max_age_seconds` = 7200 Extended 2-hour retention window for EU compliance Window management `WindowConfig.mode` = `"sliding"` Continuous monitoring with bounded memory Session boundaries `WindowConfig.session_boundary` = `"reset"` Clean session isolation Cross-protocol audit `IntegrityCheckpoint.linked_trace_id` Links to AAP AP-Trace for full audit chain Output analysis `analysis_scope: "thinking_and_output"` Output analysis results stored in audit trail (v0.5.0) Output integrity `output_block_hash` SHA-256 hash of analyzed output for tamper-evident audit Failure handling `FailurePolicy.mode` = `"fail_closed"` System blocks on analysis failure — no silent pass-through The `linked_trace_id` field in every Integrity Checkpoint can reference the corresponding AAP AP-Trace, creating a complete audit chain from reasoning to decision. With output analysis enabled (v0.5.0), the audit trail includes both what the agent was thinking and what it said, with cryptographic hashes (`output_block_hash`) enabling verification without storing content. * * * ## Risk Assessment Support Article 50 obligations vary by risk classification. AAP and AIP support risk assessment through: Risk Dimension Protocol Feature Behavioral boundaries AAP `autonomy_envelope.bounded_actions` + `forbidden_actions` Escalation policy AAP `autonomy_envelope.escalation_triggers` Value declaration AAP `values.declared` + `values.definitions` Known limitations Both LIMITS.md documentation pattern Behavioral drift AAP `detect_drift()` API Violation detection AAP `verify_trace()` API Reasoning integrity AIP `check_integrity()` real-time analysis Concern taxonomy AIP `prompt_injection`, `value_misalignment`, `autonomy_violation`, `deception` * * * ## SDK Compliance Presets ### AAP Presets ```python from aap.compliance import ( EU_COMPLIANCE_AUDIT_COMMITMENT, # retention, queryable, tamper_evidence EU_COMPLIANCE_EXTENSIONS, # eu_ai_act disclosure block EU_COMPLIANCE_VALUES, # transparency, honesty, user_control, principal_benefit ) ``` ```typescript import { EU_COMPLIANCE_AUDIT_COMMITMENT, EU_COMPLIANCE_EXTENSIONS, EU_COMPLIANCE_VALUES, } from "agent-alignment-protocol"; ``` ### AIP Presets ```python from aip import ( EU_COMPLIANCE_WINDOW_CONFIG, # extended 2h window, sliding, fail-closed EU_COMPLIANCE_FAILURE_POLICY, # fail_closed, 15s timeout ) ``` ```typescript import { EU_COMPLIANCE_WINDOW_CONFIG, EU_COMPLIANCE_FAILURE_POLICY, } from "@mnemom/agent-integrity-protocol"; ``` * * * ## The Complete Trust Chain AAP and AIP together create a complete transparency chain that exceeds Article 50 requirements: Layer Protocol Artifact What It Captures Declaration AAP Alignment Card What the agent is, what it can do, what it values Real-time analysis AIP Integrity Checkpoint What the agent is thinking, whether it aligns Decision audit AAP AP-Trace What the agent chose, why, what alternatives existed Cross-protocol link Both `linked_trace_id` Connects reasoning to decision Behavioral monitoring AAP Drift Detection Whether the agent is changing over time * * * ## Enforcement Timeline Date Milestone August 2025 AI Act general provisions in force February 2026 Prohibited practices apply **August 2026** **Article 50 transparency obligations apply** August 2027 High-risk system obligations apply * * * ## References - [EU AI Act Article 50 — Full Text](https://artificialintelligenceact.eu/article/50/) - [AAP Specification](https://docs.mnemom.ai/protocols/aap/specification) - [AIP Specification](https://docs.mnemom.ai/protocols/aip/specification) - [AAP EU Compliance Example](https://github.com/mnemom/aap/tree/main/examples/eu-compliance) - [AIP EU Compliance Example](https://github.com/mnemom/aip/tree/main/examples/eu-compliance) Licensed under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/). You are free to share and adapt with attribution. [AAP repository](https://github.com/mnemom/aap)[AIP repository](https://github.com/mnemom/aip)[OTel exporter](https://github.com/mnemom/aip-otel-exporter) --- _Source: /research/eu-ai-act-mapping/index.html · Generated by build-markdown-mirrors.mjs · For agent-readability commitment #4 see https://www.mnemom.ai/for-agents_