Artificial Intelligence in the Era of Big Data: A Comprehensive Review of Architectures, Applications, and Challenges

The convergence of Artificial Intelligence (AI) and Big Data represents a paradigm shift in modern information systems, reshaping decision-making processes, educational frameworks, and network infrastructures. This literature review synthesizes findings from five key research papers to explore the symbiotic relationship between AI and Big Data. It examines the historical evolution of AI, tracing its resurgence through the availability of massive datasets and enhanced computing power. The review analyzes critical themes including the architecture of AI systems in wireless networks, the management of infectious disease data, and the pedagogical shifts toward precision education. Furthermore, it identifies significant challenges such as algorithmic bias, data privacy, and the "black box" problem of interpretability. By integrating diverse perspectives- from business management and public health to telecommunications and education—this article provides a holistic overview of the current state of AI in Big Data, highlights existing limitations, and proposes a future research agenda focused on human-AI collaboration, robust data governance, and the development of explainable AI models.

کلیدواژه ها:

Artificial Intelligence ، Big Data ، Precision Education ، Wireless Networks ، Infectious Disease Analytics ، Human-AI Symbiosis