It is concluded that accounting is called to shift from a logic of walls to a logic of bridges, aligning symbolic capital with practical relevance, methodological pluralism, and social responsibility.
Abstract
Abstract This theoretical essay examines how the diffusion of artificial intelligence (AI) may reconfigure the epistemic and institutional boundaries of accounting under specific conditions of data, governance, and academic incentives. Drawing on a critical review, thematic analysis, and integrative synthesis, it connects classic and recent literature across four axes: the sociology of scientific fields, philosophy of science, the psychodynamics of work, and AI applications in auditing, financial reporting, and tax classification. Four propositions are advanced: (1) AI expansion tends to reward hybrid research that integrates substantive theory, interdisciplinary design, and out-of-sample validation; (2) programs combining accounting and data science may expand institutional impact while facing legitimation barriers; (3) models that are robust to automated validation tend to gain recognition when supported by transparency, substantive interpretation, and governance; and (4) algorithmic ubiquity may strain paradigm fragmentation when institutional incentives foster interdisciplinary co-authorship. Early adoption experiences suggest context-specific operational gains, while regulators and recent research emphasize transparency, bias auditing, and data documentation. The essay concludes that accounting is called to shift from a logic of walls to a logic of bridges, aligning symbolic capital with practical relevance, methodological pluralism, and social responsibility.
This article examines how Artificial Intelligence (AI) is framed within emerging regulatory debates in Latin America and how these framings shape governance trajectories. Focusing on Argentina, Brazil, Chile, and Mexico, the study compares historical data protection frameworks with recent AI-related legislative and pol...
Juan Martín Marinangeli· Revista Latinoamericana de E...· 0 citations
This article aims to reconceptualize the legitimacy crisis of algorithmic governance as a problem of epistemic boundaries rather than technical design. Debates on algorithmic justice have largely revolved around transparency, explainability, and user trust, while a more basic question has remained in the background: on...
Harun Serpil· The Turkish Online Journal o...· 0 citations
This review article synthesizes social science scholarship on algorithmic governance through the lens of anticipation. Building on research in the sociology of expectations, Science and Technology Studies, and futures studies, we lean on the concept of anticipatory assemblages to conceptualize algorithmic governance...
N. Chan, Chao Chris Su, Rui-Wen Zhou· Sociology Compass· 0 citations
Artificial intelligence is reshaping scientific knowledge production in ways that risk reinforcing existing inequalities. This article introduces the concept of epistemic algorithmic drift to explain how AI-mediated scholarly infrastructures, trained on historically stratified data, generate cumulative and often imperc...
A multi-level framework of contestable accountability comprising four nested levels (epistemic, procedural, institutional and contestatory) intersected by three temporal moments of ex ante design, in itinere operation and ex post decision is developed.
Ramniyata Jairath· Frontiers in Social Sciences...· 0 citations
Platform companies present the freedom to choose when to work as the defining virtue of gig labor, and labor economists have priced that flexibility. Yet workers’ income and access to tasks are governed by algorithmic assessments they can rarely see or contest. This article asks whether temporal flexibility suffices to...
Olivia Putri Dahlan· Journal of Economic Epistemo...· 0 citations
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