Analyzing the Confluence of Algorithmic Transparency, Accountability, and Data Privacy: A Comprehensive Study on Trust Dynamics in AI Systems

Authors : Erdal Büyükbıçakcı

Pages : 440-469

Doi:10.14514/beykozad.1746992

View : 41 | Download : 177

Publication Date : 2025-12-17

Article Type : Research Paper

Abstract :The increasing ubiquity of Artificial Intelligence (AI) systems in daily life brings the issue of public trust to the forefront of technological and ethical discussions. This study aims to examine how Algorithmic Transparency (AT), Accountability Mechanisms (AM), and Data Privacy Policies (DPP) influence Trust in AI Systems (TAS). Drawing on Social Cognitive Theory, we hypothesized that AT, AM, and DPP would positively correlate with TAS, with DPP acting as a moderator between AT and TAS. Using Structural Equation Modeling (SEM) on a dataset of 398 respondents, our findings significantly supported all four hypotheses. Notably, DPP was found to moderate the relationship between AT and TAS, emphasizing its role as a critical component in shaping public trust. This study not only enriches the existing body of literature by bridging several research gaps but also provides concrete recommendations for policymakers and practitioners aiming to enhance public trust in AI systems.
Keywords : Yapay Zeka, Güven, Algoritmik Şeffaflık, Hesap Verebilirlik Mekanizmaları, Veri Gizliliği Politikaları, Yapısal Eşitlik Modellemesi, Sosyal Bilişsel Teori

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