Transparency, Traceability, Explainability and Recourse
Transparency, Traceability, Explainability and Recourse connects stakeholder needs to usable disclosure, current documentation and reconstructable decisions. It communicates reasons and uncertainty without false certainty, protects content provenance and enables meaningful review, correction and remedy.
Responsible AI transformation needs decisions that can be examined and challenged. Connect traceability, explanations and recourse to the people affected by AI-enabled work.
Explore the holistic AIDIVE frameworkWhy this matters
A generic model card may leave an affected person unable to challenge a consequential decision. Large log collections may still fail to explain what happened or who had authority.
Questions to bring to the work
- What does each audience need to understand, decide or challenge?
- Can an independent reviewer reconstruct a material outcome and can a person obtain timely correction or remedy?
Explore this chapter
E.4.1Stakeholder-specific transparency and disclosureDesign disclosure around what users, operators, affected people and reviewers need to decide, supervise or challenge.
E.4.2System, model and agent documentationMaintain documentation for the deployed purpose, scope, dependencies, limitations, controls and agent authority as the configuration changes.
E.4.3Lineage, logging and audit reconstructionTest whether identities, versions, context, tools, approvals, actions and results allow an independent reviewer to reconstruct a consequential outcome.
E.4.4Explainability, uncertainty and decision rationaleExplain reasons and limitations at the level needed by the stakeholder without presenting an unsupported rationale or false certainty.
E.4.5Content provenance, identity and information integrityUse provenance and identity controls where synthetic content or agent communications could mislead people about origin, authority or involvement.
E.4.6Operational recourse, correction and remedy evidenceTest the real route to human review, correction and remedy, including its timing, authority, accessibility and effect on outcomes.
What useful evidence looks like
- Stakeholder-specific disclosures and current system, model and agent documentation.
- Reconstruction and recourse tests connecting identities, versions, evidence, approvals, actions and final outcomes.
Move from understanding to practice
AR-E15AR-E15 · System, Model and Agent Transparency Card
AR-E16AR-E16 · Decision Traceability and Audit Reconstruction
AR-E17AR-E17 · Stakeholder Disclosure and Explanation Design
AR-E18AR-E18 · Content Provenance and Information-Integrity Control
Framework source
Editorial adaptation from the supplied AIDIVE Version 1 master documents.
- AIDIVE Ethics Dimension Version-1.docx · E.4 Transparency, Traceability, Explainability and Recourse; AIDIVE Ethics - Practices & Playbook Version-1.docx · AR-E15, AR-E16, AR-E17, AR-E18
Ethics
Dimension overview ↗01Ethical Intent, Human Rights and Accountability02Risk-Based Governance, Decision Rights and Lifecycle Assurance03Responsible-AI Requirements and Enforceable Guardrails04Transparency, Traceability, Explainability and Recourse05Agentic-AI Autonomy, Identity and Human Control06Regulatory Readiness, Assurance and Responsible ScaleFind a practiceLEARN. CONTRIBUTE. APPLY.Put AI transformation
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