Ethical and Responsible Artificial Intelligence in High-Risk Industries: A Results-Oriented Governance and Assurance Framework

Author(s)	Mr. Ali Azghar Hussain Syed Abbas
Country	India
Abstract	Artificial Intelligence (AI) is increasingly used in high-risk sectors such as healthcare, finance, and autonomous systems, where errors can create serious real-world harm. This paper introduces the Responsible AI Assurance Lifecycle (RAIAL), a practical framework that integrates global governance standards with measurable technical audits. Using synthetic experiments across three domains, RAIAL demonstrates clear improvements in fairness, model calibration, feature-drift stability, and safety performance. Results show fairness gains up to 42%, reduced calibration error, and up to 45% fewer safety-critical failures. RAIAL offers a reproducible approach for designing, evaluating, and governing responsible AI systems, making it suitable for industry practitioners and regulators.
Keywords	responsible artificial intelligence, AI governance, high-risk AI systems, RAIAL framework, fairness auditing, model calibration, feature drift, autonomous systems safety, ethical AI, AI compliance, EU AI Act, NIST AI RMF, ISO 42001, algorithmic transparency, AI risk management
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 6, Issue 6, November-December 2024
Published On	2024-12-06
DOI	https://doi.org/10.36948/ijfmr.2024.v06i06.61913

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