The Evolution of AI Model Governance: Navigating Risks with Advanced Monitoring
DOI:
https://doi.org/10.53555/ephijse.v9i2.299Keywords:
AI governance, model monitoring, AI risk assessmentAbstract
As artificial intelligence technologies gain traction in business operations, regulatory control and governance become increasingly important. Organisations must make sure they uphold moral, legal, and ethical standards even if models of artificial intelligence keep optimal performance. The rapid growth of artificial intelligence technology presents issues including prejudice, lack of openness, and regulatory non-compliance that call for wise government rules. Formal risk assessment methods and increased monitoring technologies for tracking model behavior in real time must be employed to assure AI accountability. This article examines the evolution of artificial intelligence governance with a focus on compliance-oriented AI models and the role proactive monitoring plays in mitigating the risks associated with artificial intelligence for the necessity of interpretability in artificial intelligence decision-making is emphasized, ensuring that machine learning models operate fairly and openly. ArthurAI and other modern artificial intelligence monitoring solutions help businesses to find bias, guarantee compliance, and improve the dependability of AI-generated choices. Real case studies also show how well artificial intelligence governance principles reduce risks in financial services, healthcare, and e-commerce these incidents highlight the significance of including artificial intelligence monitoring tools to ensure ethical AI application and regulatory compliance, dealing with governance calls for multidisciplinary cooperation, continuous monitoring, and adherence to new artificial intelligence norms to retain faith in systems driven by artificial intelligence.
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