A Review of the Evolution of Artificial Intelligence in Intelligent Media: From Data Processing to Automated Content Generation

Artificial Intelligence (AI) has significantly transformed the media industry by enabling advanced capabilities in data analysis, content processing, and automated decision-making. This study explores the evolution of AI in media systems, beginning from traditional machine learning-based news classification to modern deep learning, natural language processing (NLP), recommender systems, and generative AI technologies. The main objective of this research is to analyze how AI-driven methods have reshaped media data processing, content distribution, and audience engagement. The study employs a comprehensive literature-based analytical approach by reviewing previous research on text classification, recommender systems, generative content creation, and ethical implications of AI in media ecosystems. The findings indicate that AI has progressed from simple categorization tasks to complex systems capable of understanding language, predicting user behavior, and generating multimodal content such as text, images, and video. However, alongside these advancements, significant challenges have emerged, including algorithmic bias, misinformation, lack of transparency, and ethical concems regarding authorship and intellectual property. The study concludes that while AI enhances efficiency and personalization in media environments, its deployment must be balanced with ethical governance and human oversight to ensure reliability, fairness, and public trust in digital communication systems.

کلیدواژه ها:

Artificial Intelligence ، Media Analytics ، Natural Language Processing ، Recommender Systems ، Generative AI ، Algorithmic Bias