<![CDATA[Rapid advances in artificial intelligence (AI) have transformed how humans understand, manage, and construct knowledge. In an era of digital technology and automation, it becomes essential to revisit the meaning of knowledge and human cognition, especially as machine learning systems begin to emulate and even surpass human analytical abilities. This study aims to explore how traditional epistemological concepts are transformed through the application of deep learning and its implications for scientific understanding and educational praxis. Using a Systematic Literature Review (SLR) method, this research analyzes recent scholarly works related to epistemology, deep learning, and the philosophy of knowledge within the context of AI. The findings indicate that deep learning not only signifies technological progress but also establishes a new paradigm for acquiring and validating knowledge. This paradigm emphasizes data-driven reasoning, continuous learning, and the construction of knowledge through inferential patterns similar to human thought. In conclusion, deep learning represents a holistic and dynamic model of scientific understanding, promoting synergy between artificial intelligence and human wisdom in developing meaningful and ethical knowledge in the digital era.]]>
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