The AISDP requires architectural documentation that traces the path of data through the system from ingestion to output. The data flow is structured around an eight-layer reference architecture, each layer providing specific protections against intent drift and outcome drift.
Data enters at the Data Ingestion Layer (Layer 1), where schema validation, input range enforcement, and prohibited feature blocking intercept malformed or out-of-distribution inputs. The Feature Engineering Layer (Layer 2) transforms validated data into the representation used for inference, enforcing training-serving consistency and maintaining a feature registry with proxy variable flags. The Model Inference Layer (Layer 3) applies the model with version pinning, confidence thresholding, and output constraint enforcement.
Post-inference, the Post-Processing Layer (Layer 4) applies business rules and threshold calibration, with fairness re-evaluation on production data. The Explainability Layer (Layer 5) generates explanations using methods appropriate to the model architecture. The Human Oversight Interface (Layer 6) presents the system’s recommendation alongside the explanation for operator review, with automation bias countermeasures and override capability.
The Logging and Audit Layer (Layer 7) captures immutable, append-only records of events at Layers 3, 4, and 6, using cryptographic hash chains. The Monitoring Layer (Layer 8) consumes these logs to compute performance, fairness, data drift, operational, and human oversight metrics against AISDP-declared thresholds. The data flow diagram is essential for demonstrating Article 12 compliance (record-keeping) and for enabling traceability analysis throughout the system’s lifecycle.
Key outputs
- Data flow diagram (part of AISDP Module 3)
- System context, container, and component diagrams (C4 model)