Which statements correctly clarify the distinctions between AI, machine learning, and deep learning?

The chosen statement accurately reflects the hierarchical relationship between these fields. Machine learning is indeed a subset of artificial intelligence that specifically emphasizes algorithmic approaches to make predictions or decisions based on data. It serves as a crucial mechanism for enabling AI systems to learn from data, as opposed to being explicitly programmed for every possible scenario.

Furthermore, artificial intelligence is an overarching discipline that includes various approaches and methodologies, including machine learning and deep learning. Deep learning adds another layer to this hierarchy as a specific, more complex subset of machine learning that utilizes neural networks to analyze and learn from vast amounts of data.

The other statements misrepresent the relationship between these domains. Deep learning, unlike what is suggested in one option, actually automates the feature extraction process, making it distinct from traditional machine learning techniques that often require manual intervention for feature definition. Additionally, deep learning cannot be considered entirely separate from AI and machine learning, as it is integrally tied to both and builds upon their foundational principles.