Quality Objectives for AI Development & Deployment

The core Quality by Design (QbD) objectives for AI system development and deployment can be summarized as:

1. Reliability & Consistency: Ensure stable, dependable system performance QbD1: Ensure that the AI system produces consistent, reliable outputs across various real-world conditions and over time.
2. Accuracy & Precision: Optimize for precise, relevant AI outputs QbD2: Ensure the AI system provides accurate predictions or decisions that are aligned with real-world requirements.
3. Bias Mitigation & Fairness: Design for fairness, equity & inclusivity QbD3: Ensure that the AI system is fair, equitable and free from bias that could result in discriminatory outcomes.
4. Ethical Alignment: Ensure the AI system aligns with ethical standards QbD4: Ensure that the AI system operates in an ethical manner, respecting societal values, human rights and legal frameworks.
5. Transparency & Explainability: Foster trust through clear & understandable AI behavior QbD5: Design AI systems to be transparent and provide explanations for their decisions, fostering trust among stakeholders.
6. Compliance & Regulatory Adherence: Meet all legal, regulatory & data protection standards QbD6: Ensure the AI system meets regulatory and legal requirements, such as those set by government bodies, industry standards and data protection laws.
7. Security & Privacy: Protect data and ensure secure system operations QbD7: Safeguard the AI system against security threats and ensure the privacy of user data.
8. Scalability & Adaptability: Build flexible, future-proof systems capable of handling growth & change QbD8: Ensure the AI system is scalable and can handle increasing loads or changing requirements over time.
9. Usability & User-Centered Design: Prioritize user experience & accessibility QbD9: Ensure the AI system is user-friendly, intuitive and aligned with the needs of the end-users.
10. Continuous Improvement & Monitoring: Keep systems up-to-date with continuous feedback & optimization QbD10: Establish a system of ongoing evaluation, allowing for continuous improvement throughout the AI system’s lifecycle.

By embedding these objectives into the AI development lifecycle, organizations can achieve high-quality, trustworthy and compliant AI systems that meet both technical requirements and societal expectations.

Using the following link you can access this sandbox SIPOC model in the ProcessHorizon web app and adapt it to your needs (easy customizing) and export or print the automagically created visual AllinOne SIPOC map as a PDF document or share it with your peers: https://app.processhorizon.com/enterprises/Fe6MLDTERNZ266w9Zt7oLias/frontend