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1.4 Ensuring Trustworthiness Across the AI Development Lifecycle

Ensuring Trustworthiness Across the AI Development Lifecycle

Lifecycle-Based Trust in AI

Building trust in AI isn’t a single task, it’s a continuous process that unfolds across every phase of system development and deployment. Even with well-curated data and high-performing models, AI can still fail if ethical, legal, or technical standards aren’t upheld throughout its lifecycle.

The AI development lifecycle (Figure 11) offers a practical structure for embedding trustworthiness from start to finish. It transforms abstract principles into repeatable actions, ensuring that fairness, accountability, and safety are operationalized across planning, data handling, model design, evaluation, and deployment.

AI Lifecycle Diagram Figure 11: AI Development Lifecycle
This framework breaks AI development into five practical stages—each a checkpoint for embedding trust.

The lifecycle model aligns with international standards like ISO/IEC 229891, 53382, and 420013, and is already reflected in national AI laws, such as Korea’s AI Basic Act and the EU AI Act. As AI systems become more tightly regulated, the ability to build and demonstrate trust at every lifecycle stage becomes not just best practice—but a legal and competitive necessity.

This section walks through how to:

  • Align ethical, legal, and stable trust dimensions with each phase
  • Avoid lifecycle-specific failure points (e.g., biased data, unstable models)
  • Apply international best practices using real-world case studies

In the pages ahead, we break down each phase and explore the real work of building trustworthy AI, not just in code, but in design decisions, testing plans, documentation, and feedback loops.

Bibliography

  1. ISO/IEC. (2022). ISO/IEC 22989: Artificial intelligence concepts and terminology. https://www.iso.org/standard/74296.html ↩

  2. ISO/IEC. (2023). ISO/IEC 5338: Guidelines for AI lifecycle. https://www.iso.org/standard/81369.html ↩

  3. ISO/IEC. (2024). ISO/IEC 42001: AI management system standard. https://www.iso.org/standard/81285.html ↩