Comprehensive Survey of Modern Artificial Intelligence: Technologies, Applications, and Responsible Governance

Artificial Intelligence (AI) has swiftly evolved from a theoretical concept to a foundational technology driving profound transformation across industries and society. This article offers a comprehensive survey of the current landscape of AI, exploring its historical progression from symbolic and rule-based systems to modern deep learning and neuro-symbolic models. Emphasizing both theoretical underpinnings and practical advancements, the review covers core AI techniques—including supervised, unsupervised, and reinforcement learning—as well as the emergence of hybrid architectures that integrate symbolic logic and neural networks. The paper highlights how AI is being deployed in critical sectors such as healthcare, finance, smart cities, retail, and environmental science, providing real-world examples of AI-driven diagnostics, risk assessment, optimization, and decision support. Alongside these technical advances, the article addresses pressing ethical, legal, and social challenges, including algorithmic bias, data privacy, transparency, explainability, and the environmental impact of large-scale AI models. Special attention is given to responsible AI governance, reviewing current regulatory approaches such as the European Union’s AI Act, and outlining best practices for safe and ethical deployment. The survey draws on peer-reviewed research published between 2019 and 2025, synthesizing state-of-the-art findings and identifying persistent gaps in fairness, accountability, and sustainability. Furthermore, the paper discusses future research directions that will shape the next decade of AI: continual learning, edge AI, quantum-enhanced algorithms, and human-AI collaboration. By integrating insights from foundational theory, industrial application, and ethical oversight, this article aims to serve as an authoritative resource for students, practitioners, and policymakers seeking a balanced and up-to-date overview of the AI field. Ultimately, the review underscores the need for multidisciplinary cooperation and vigilant governance to ensure that the rapid evolution of artificial intelligence benefits society at large, aligning technological progress with human values and global priorities. Keywords: Artificial Intelligence, Machine Learning, Deep Learning, Reinforcement Learning, Ethics, Responsible AI

کلیدواژه ها:

Artificial Intelligence ، Deep Learning ، Ethics ، Machine Learning ، Reinforcement Learning ، Responsible AI