Abstract
In the data-driven economy, AI algorithms will eventually drive power interests and value allocation of scarce resources in terms of who gets what, when, and how. However, to date, the decision-making process and internal mechanisms of algorithm-based AI remain “a black box”. Therefore, a critical systematic analysis of the benefits and limitations of AI’s practical utility and applicability, as well as legal and institutional promotion and control measures to enhance transparency in algorithm design, is needed now more than ever. The current structural situation of human oppression, control, and domination by AI power in the name of techno-engineering-based social innovation and development in the age of digital capitalism requires a multidisciplinary approach to governance that utilizes political science, educational politics, and critical theory perspectives. This paper aims to comprehensively review the emerging AI governance definitions, issues, and development plans from critical perspectives.
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