<![CDATA[This study examines how recommendation algorithms, powered by big data and artificial intelligence, drive the growth of digital businesses by personalizing user experiences. Through a review of 21 studies, it identifies key ethical challenges such as algorithmic bias, privacy breaches, lack of transparency, and behavioral manipulation through dark patterns. To mitigate these issues, the literature emphasizes the importance of implementing the Fairness, Accountability, and Transparency (FAT) framework using explainable AI, user data control mechanisms, regular algorithm audits, and compliance with legal frameworks such as the GDPR. The study further highlights the need for deeper research on data governance, integration between GDPR and Indonesia’s Personal Data Protection Law (UU PDP), and more interdisciplinary and longitudinal studies, particularly in Southeast Asia. These findings underscore the necessity of maintaining a balance between technological innovation and ethical accountability to foster a sustainable and trustworthy digital ecosystem that supports both user protection and business growth.]]>
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