AI 자동 뉴스 추천 서비스 사용자가 인지하는 정보 편향성에 대한 연구: AI 서비스의 윤리 원칙 수립을 중심으로

AI-driven news recommendation systems are widely used today, providing personalized news consumption experiences. However, there are significant concerns that these systems might increase users' information bias by mainly showing information from limited perspectives. This lack of diverse information access can prevent users from forming well-rounded viewpoints on specific issues, leading to social problems like Filter bubbles or Echo chambers. These issues can deepen social divides and information inequality. This study aims to explore how AI-based news recommendation services affect users' perceived information bias and to create a foundation for ethical principles in AI services. Specifically, the study looks at the impact of ethical principles like accountability, the right to explanation, the right to choose, and privacy protection on users' perceptions of information bias in AI news systems. The findings emphasize the need for AI service providers to strengthen ethical standards to improve service quality and build user trust for long-term use. By identifying which ethical principles should be prioritized in the design and implementation of AI services, this study aims to help develop corporate ethical frameworks, internal policies, and national AI ethics guidelines.