Part 7/13:
Data Scarcity and Privacy: AI models are "hungry" for data, but acquiring high-quality, annotated data—especially with subject matter expertise—is challenging, time-consuming, and privacy-sensitive. For instance, a banking example illustrated how misreading a bank statement could lead to misclassification, underscoring the importance of accurate and high-quality data.
Accuracy and Reliability: AI cannot guarantee 100% accuracy, especially when dealing with complex or noisy data. The unpredictability in recognizing faces or interpreting handwritten notes remains a significant obstacle.