Principles of AI Governance and Model Risk Management: Master the Techniques for Ethical and Transparent AI Systems

© The Author(s), under exclusive license to APress Media, LLC, part of Springer Nature 2024

J. SaylesPrinciples of AI Governance and Model Risk Managementhttps://doi.org/10.1007/979-8-8688-0983-5_4

4. Designing a Well-Governed AI Lifecycle Model

James Sayles¹  

(1)

Spring, TX, USA

 

To design a well-governed AI development lifecycle, begin with careful problem identification, align proposed solutions with ethical principles, and ensure feasibility before proceeding. Prioritize data governance through quality standards, bias assessments, responsible collection practices, and secure storage protocols. During model development, balance explainability with accuracy, incorporate bias mitigation techniques and maintain thorough documentation. Implement