<![CDATA[The rapid expansion of the digital economy has intensified the use of algorithmic systems in decision-making across sectors such as finance, e-commerce, and social media, raising concerns about legal accountability, transparency, and regulatory fairness. This study aims to examine the crisis of legal accountability in algorithmic governance and its implications for regulatory justice by integrating normative legal analysis, empirical observations, and quantitative simulation. A mixed-method approach is applied through literature review, legal analysis, and probabilistic simulation to assess transparency, audit mechanisms, and bias distribution. The findings indicate that transparency levels remain relatively low, with e-commerce at 48%, ride-hailing at 44%, and social media at 38%, while fintech performs moderately at 62%. Bias analysis reveals disparities in algorithmic accuracy, where majority groups reach 91% compared to 79% in minority rural groups, along with higher false positive (15%) and false negative (12%) rates. In addition, the gap between technological development and regulatory response has increased from 10 points in 2015 to 27 points in 2023, reflecting reactive regulatory frameworks. These results illustrate the presence of systemic bias and declining accountability in algorithmic systems. This study contributes by offering an integrative framework that connects technical algorithmic processes with legal accountability and regulatory justice, highlighting that transparency without strong audit mechanisms and adaptive regulation remains insufficient to ensure fairness and accountability in digital governance.]]>
