Paper emphasizes importance of model risk management (MRM) for harnessing full potential of AI and machine learning (ML) models
The latest set of AI guidance from the Cloud Security Alliance (CSA), the world’s leading organization dedicated to defining standards, certifications, and best practices to help ensure a secure cloud computing environment, explores the importance of Model Risk Management (MRM) in ensuring the responsible development, deployment, and use of AI/ML models. Written for a broad audience, including practitioners directly involved in AI development and business and compliance leaders focusing on AI governance, Artificial Intelligence (AI) Model Risk Management Framework emphasizes the role of MRM in shaping the future of ethical and responsible AI.
“While the increasing reliance on AI/ML models holds the promise of unlocking vast potential for innovation and efficiency gains, it simultaneously introduces inherent risks, particularly those associated with the models themselves, which if left unchecked can lead to significant financial losses, regulatory sanctions, and reputational damage. Mitigating these risks necessitates a proactive approach such as that outlined in this paper,” said Vani Mittal, a member of the AI Technology & Risk Working Group and a lead author of the paper.
Highlighting the inherent risks associated with AI models (e.g., data biases, factual inaccuracies or irrelevancies, and potential misuse), the paper emphasizes the need for a proactive approach to ensure a comprehensive MRM framework.
The framework put forth in the paper explores MRM and its importance for responsible AI development, closely examining the four pillars of an effective MRM framework — model cards, data sheets, risk cards, and scenario planning — and how they work together to create a holistic approach to MRM. By implementing this framework, organizations can ensure the safe and beneficial use of AI/ML models with key benefits such as:
- Enhanced transparency and explainability
- Proactive risk mitigation and “security by design”
- Informed decision-making
- Trust-building with stakeholders and regulators
“A comprehensive framework goes a long way to ensuring responsible development and enabling the safe and responsible use of beneficial AI/ML models, which in turn allows enterprises to keep pace with AI innovation,” said Caleb Sima, Chair, CSA AI Safety Initiative.
Whereas this paper focuses on the conceptual and methodological aspects of MRM, those looking to learn more about the people-centric aspects of MRM, such as roles, ownership, RACI, and cross-functional involvement, are encouraged to read CSA’s AI Organizational Responsibilities – Core Security Responsibilities.
Download the AI Model Risk Management Framework now.
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#AI [Source: AI Techpark]