Part 7/14:

An illustrative analogy involved surgical operations—highlighting that in high-stakes scenarios, human oversight remains indispensable. Balancing automation with human-in-the-loop strategies is thus vital for safe and effective deployment.

Data-Driven AI: The Need for Context and Support

The focus was on data-driven approaches, contrasting rule-based systems like fault detection with modern machine learning models that analyze time series, images, and text. These models can respond dynamically to real-time data, adapt to changing conditions, and generate autonomous recommendations.

Key principles for AI deployment include:

• Selecting appropriate algorithms that fit specific use cases.

• Ensuring compatibility with existing control and control systems.