paperarXivTrust 82 · PrimaryPublished 10d agoLive · 9d ago

Causal Evidentiary Governance for High-Risk Machine Learning Systems

Machine learning systems deployed for credit, hiring, and resource distribution are increasingly subject to regulatory oversight from policies such as the EU AI Act and GDPR. Current fairness governance practices rely on observational fairness metrics, post-hoc explainability, and immutable audit logs, but provide limited support for causal attribution and efficient evidentiary verification. We introduce Causal Evidentiary Governance (CEG), a framework in which regulated institutions commit to a versioned directed acyclic graph (DAG) that partitions causal pathways into allowable and disallowe

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PossiblePossibly related (embedding) · 54%Enterprise Machine Learning Governance Guide for 2026 - appinventiv.com →
PossiblePossibly related (embedding) · 54%Anti-Causal Domain Generalization: Leveraging Unlabeled Data - Apple Machine Learning Research →
PossiblePossibly related (embedding) · 54%Regulators publish draft guidance on AI transparency →
PossiblePossibly related (embedding) · 52%The Challenge of Regulatory Preemption in AI Governance - The Regulatory Review →
FuzzySimilar title/name (fuzzy) · 84%amitness/learning →
“Fuzzy title match (0.92): “Causal Evidentiary Governance for High-Risk Machine Learning” ≈ “amitness/learning””
FuzzySimilar title/name (fuzzy) · 66%DataTalksClub/machine-learning-zoomcamp →
“Fuzzy title match (0.78): “Causal Evidentiary Governance for High-Risk Machine Learning” ≈ “DataTalksClub/machine-learning-zoomcamp””
FuzzySimilar title/name (fuzzy) · 66%stefan-jansen/machine-learning-for-trading →
“Fuzzy title match (0.78): “Causal Evidentiary Governance for High-Risk Machine Learning” ≈ “stefan-jansen/machine-learning-for-trading””
FuzzySimilar title/name (fuzzy) · 59%EthicalML/awesome-production-machine-learning →
“Fuzzy title match (0.73): “Causal Evidentiary Governance for High-Risk Machine Learning” ≈ “EthicalML/awesome-production-machine-learning””

Covers

newsEnterprise Machine Learning Governance Guide for 2026 - appinventiv.com newsAnti-Causal Domain Generalization: Leveraging Unlabeled Data - Apple Machine Learning Research newsRegulators publish draft guidance on AI transparency newsThe Challenge of Regulatory Preemption in AI Governance - The Regulatory Review

Implements (incoming)

repoamitness/learning repoDataTalksClub/machine-learning-zoomcamp repostefan-jansen/machine-learning-for-trading repoEthicalML/awesome-production-machine-learning reporasbt/python-machine-learning-book

authored (incoming)

personSamah Kareem personBarış Çeliktaş

Covers (incoming)

newsApplying causal machine learning to assess and improve cleantech policy design - Nature

Related across the graph

personBarış Çeliktaş repostefan-jansen/machine-learning-for-trading newsThe Challenge of Regulatory Preemption in AI Governance - The Regulatory Review newsApplying causal machine learning to assess and improve cleantech policy design - Nature repoamitness/learning reporasbt/python-machine-learning-book newsEnterprise Machine Learning Governance Guide for 2026 - appinventiv.com newsRegulators publish draft guidance on AI transparency newsAnti-Causal Domain Generalization: Leveraging Unlabeled Data - Apple Machine Learning Research personSamah Kareem repoDataTalksClub/machine-learning-zoomcamp repoEthicalML/awesome-production-machine-learning

Topics

cs.AI