AI models operate through complex layers that are not easily interpretable by humans.
Modern AI develops its own decision-making patterns, which often remain opaque.
Bias in the data can lead to biased outcomes without clear indicators of origin.
Advancing explainable techniques, integrating assistive technologies, and adopting certification standards can lead to fair, trustworthy, dynamic, and innovative AI systems.