TABLE 3.

The challenges in AI models and its key points.

Challenges	Key points
Data quality and availability	Reliable, high‐quality data is essential for training and evaluating AI models Access to such data can be limited in many areas
Model interpretability	Some AI models, particularly deep learning models, can be difficult to interpret, which can make it hard to understand how they are arriving at their predictions
Robustness	AI models can be affected by the availability and distribution of the data used to train them Can be affected by changes in the environment or population. Examples: image classification, speech recognition and natural language processing

Abbreviation: AI, artificial intelligence.