Algorithmic Governance and Digital Ethics: An Organizational Approach to Automated Decision-Making
Abstract
Automated decision-making systems have fundamentally reshaped organizational power structures; however, there is limited empirical evidence on how algorithmic governance and digital ethics are operationalized as measurable organizational capabilities, particularly in emerging economies. This study analyzes the state of algorithmic governance and digital ethics in 120 organizations across Argentina, Brazil, Chile, and Uruguay using a quantitative approach based on structured instruments, exploratory factor analysis, and hierarchical clustering. Four key dimensions were assessed: algorithmic transparency, supervision and audit mechanisms, ethical governance structures, and institutional perception of bias. The results reveal moderate levels of transparency (M = 3.38), low institutionalization of audit mechanisms (M = 2.87), and weak adoption of formal ethical frameworks (M = 2.82), alongside a significant gap between bias awareness (61%) and mitigation practices (40%). Cluster analysis identifies that only 22% of organizations exhibit a proactive ethical governance profile. These findings demonstrate that digital ethics remains weakly integrated into organizational strategy, limiting the capacity to ensure fair and accountable automated decision-making. Based on this evidence, the study proposes an organizational governance framework that integrates transparency, ethical oversight, and institutional accountability as core components of algorithmic systems. This research contributes empirical evidence on the structural conditions required to advance responsible AI governance in Latin American organizations.Downloads
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