Algorithmic accountability in AI-driven digital media: Cybersecurity risks, transparency, and content integrity

This study examines algorithmic accountability in AI-driven digital media, focusing on the interrelationship between cybersecurity risks, transparency, and content integrity. As artificial intelligence becomes increasingly embedded in content production and distribution processes, new challenges emerge related to algorithmic opacity, data manipulation, and misinformation. The study adopts a qualitative analytical approach based on systematic thematic analysis of academic literature, policy frameworks, and real-world AI applications in digital media. The analysis identifies key vulnerabilities associated with cybersecurity threats and limited transparency, and examines their impact on the reliability and credibility of digital content. The findings indicate that the absence of integrated accountability mechanisms significantly increases system vulnerability and undermines public trust in digital media platforms. The study demonstrates that transparency and cybersecurity are interdependent dimensions that jointly influence content integrity. This research proposes an integrated analytical framework that links algorithmic accountability with cybersecurity and transparency to enhance content reliability in AI-driven media environments. The study contributes to the field by offering a comprehensive perspective that bridges technological, organizational, and regulatory dimensions of AI governance.