The current series of articles on MLOps started with an analogy with DevOps. To explain how software updates happen, I am introducing the Known Unknown matrix. The so-called "known unknown" matrix is popularized by Donald Rumsfeld and divides our knowledge into four quadrants: Applied to software development, let us consider what the knowns and the unknowns for the feature team would be. As an example, let us assume that the software is an OCR program that recognizes car license plate numbers based on heuristic algorithms. In Software 1.0 (the traditional software), bugs and feature requests are two cases when software updates are needed.

The technological advancement of Artificial Intelligence is impacting many areas of our lives like health care, manufacturing, entertainment, and farming. The development of AI, however, also comes with new problems. Bias, accuracy, privacy, and security issues in recent years made the general public worry about the ethical and legal consequences of AI. To address these concerns, many government bodies began to draft a legal framework around trustworthy AI so as to make it possible to regulate AI without hindering its development. Just as they did for data protection with GDPR (General Data Protection Regulations) in 2016, the EU led the world on Trustworthy AI by publishing Ethics Guidelines for Trustworthy AI (2019), White Paper on Artificial Intelligence -- A European approach to excellence and trust (2020), and A European Strategy for Data (2020).