A Conceptual Framework for Autonomous AI Governance in Smart Digital Ecosystems - Bambang Saras Yulistiawan (Jurnal Teknik Informatika C.I.T Medicom, 2023)
The rapid advancement of autonomous Artificial Intelligence (AI) technologies has significantly transformed smart digital ecosystems across sectors such as smart cities, healthcare, fintech, autonomous transportation, Internet of Things (IoT), and Industry 4.0. While autonomous AI offers substantial benefits in automation, efficiency, and intelligent decision-making, its increasing adoption also creates complex governance challenges related to algorithmic bias, lack of transparency, cybersecurity threats, privacy violations, accountability ambiguity, and long-term societal risks. This study aims to develop a conceptual framework for autonomous AI governance in smart digital ecosystems by integrating ethical, technical, regulatory, adaptive, and human-centered governance dimensions into a unified governance architecture. This study employs a qualitative conceptual research approach using theory-building methodology and literature synthesis. Data were obtained from academic journals, conference proceedings, AI governance reports, international regulations, policy documents, and institutional publications related to autonomous AI, responsible AI, cybersecurity, and digital governance. The analysis was conducted using systematic literature review, thematic analysis, comparative framework analysis, conceptual mapping, and governance modeling techniques. The findings indicate that autonomous AI governance requires a multidimensional and interconnected governance structure capable of addressing ethical, legal, technical, organizational, and sustainability challenges simultaneously. The proposed framework consists of six governance dimensions: ethical governance, regulatory governance, technical governance, data governance, adaptive governance, and human-AI collaboration governance. These dimensions collectively support fairness, transparency, accountability, cybersecurity, privacy protection, ecosystem resilience, and human oversight within autonomous AI environments. This study concludes that integrated and adaptive governance mechanisms are essential for ensuring responsible, transparent, secure, and sustainable AI implementation in smart digital ecosystems while supporting trustworthy and resilient digital transformation.