Artificial intelligence (AI) technologies have enhanced operational efficiency and personalized services in news through content generation, distribution, and user behavior analysis. However, they introduce privacy risks like unauthorized data collection across the data lifecycle. Meanwhile, the industry faces dual challenges from technological implementation complexities and lagging legal-ethical frameworks. This survey systematically reviews AI-driven privacy protection in news, outlining application scenarios, privacy risks, and technical, legal-ethical solutions (e.g., federated learning, differential privacy). By synthesizing existing research contributions and identifying gaps, this work proposes future research directions in technical optimization, legal framework enhancement, and social ethics construction, providing a comprehensive reference for the field's advancement.