Establishing Trust in AI Systems with ISO/IEC 24028

As artificial intelligence becomes deeply integrated into business and society, building systems that users and regulators can trust is a critical requirement. This course guides you through the foundational principles of AI trustworthiness, helping you understand how to identify risks, minimize bias, and ensure transparency in AI deployments. What you will learn: Understand the core pillars of AI trustworthiness, including reliability, safety, security, and privacy; Analyze the ISO/IEC 24028 framework to guide your organization's AI governance strategy; Identify common sources of algorithmic bias and apply modern mitigation strategies; Implement transparency and explainability techniques to make complex AI models understandable; Evaluate AI systems for potential vulnerabilities, threats, and ethical concerns. You will start with key terminology and foundational definitions of trust in technology before progressing to structured frameworks, risk assessments, and real-world compliance scenarios. This course is designed for beginners, and no prior technical background in programming or machine learning is required. Start reading today to build AI systems that earn and maintain human trust.