This research investigates how philosophical hermeneutics, particularly in language philosophy (philosophy) can be used to evaluate the nature of text interpretation in an age where artificial intelligence is at its core. The research focuses on understanding how much AI-generated texts show real understanding, and how this process differs from human interpretation based on history, purpose, and the exchange of meaning. Using a qualitative and philosophical approach, the study explores classical hermeneutics and modern digital text creation. Information was gathered from hermeneutic writings, language philosophy research, and examples of outputs from AI language models to compare the structure of human meaning with computational processes. The findings show that AI can create coherent language patterns, but lacks the depth of experience, meaning horizon, and reflective thinking that are essential in hermeneutics. The study also found that machine-generated interpretations are often disconnected from context and are based on existing data rather than meaningful dialogue. The unique part of this research is combining classical hermeneutics with digital interpretation methods to create a model for evaluating the limits of AI interpretation. The study’s findings highlight the importance of critical literacy when using AI-generated texts and the value of keeping human interpreters in areas like academia, education, and religion where deep understanding is necessary.
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