Institutional Pathways to Algorithmic Trust: Transparency, Fairness and Governance Effectiveness
Keywords:
Government Effectiveness, Regulatory Quality, Institutional Persistence, Algorithmic Transparency, Fairness-Based Trust, Institutional Theory, Procedural Justice Theory, Information Disclosure Theory, Privacy Calculus, Dynamic Governance, Responsible AIAbstract
Purpose–This study integrates macro-institutional and micro-ethical perspectives to examine the determinants of state capacity and to extend these institutional concepts to the governance of high stakes artificial intelligence (AI). The aim is to move beyond accounts of AI oversight that focus narrowly on technical safeguards, proposing instead a dynamic framework in which institutions and ethics jointly sustain trust. Moreover, the paper suggests that the structural logic behind the mechanisms that lead to fair and transparent government is also valid when it comes to mechanisms that lead to trust in algorithmic decision-making, thereby connecting the study of economic governance with the study of algorithmic accountability.
Methodology–A recurring limitation in the literature is that governance research does not always account for the persistence of institutional quality over time, and AI policy research has rarely been grounded in empirical models of how ethical constructs, in particular, fairness and transparency, relate to how much trust can be empirically measured in the people who are impacted by it. Analysis is based on two complementary models: Building on Institutional Theory, Information Disclosure Theory and Procedural Justice Theory. It is the first to apply two-step System Generalized Method of Moments (System GMM) to 64 countries in the period 2015-2024 to study the determinants of Government Effectiveness. The second mediation model is conceptual, where Perceived Transparency in AI (PTAI) moderates the relationship between Perceived Fairness (PFAI) and Trust in AI Recommendations (TAIR), which is also influenced by Privacy Concerns (PC).
Findings/Value–There is a significant level of institutional persistence, with an estimated autoregressive coefficient of approximately λ ≈ 0.797. The structural driver of governance that shows the same pattern across all countries is Regulatory Quality, with fixed-effects coefficient of around β ≈ 0.55. On the theoretical level, the paper explores the idea of fairness based transparency and Dynamic Governance Loops ways in which durable institutions can be continuously re-legitimated and are not static endowments. The significance of the study is in the linkage between governance of economies and ethics of algorithms, demonstrating that trust, either in the governments or in technological systems, is safe to be maintained if it is regularly renewed by practices that are fair.
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