The use of artificial intelligence and algorithmic decision-making in public policy processes is influenced by a range of diverse drivers. This article provides a comprehensive view of 13 drivers and their interrelationships, identified through empirical findings from the taxation and social security domains in Belgium. These drivers are organized into five hierarchical layers that policy designers need to focus on when introducing advanced analytics in fraud detection: (a) trust layer, (b) interoperability layer, (c) perceived benefits layer, (d) data governance layer, and (e) digital governance layer. The layered approach enables a holistic view of assessing adoption challenges concerning new digital technologies. The research uses thematic analysis and interpretive structural modeling.

June 2018 was an intense time in Vietnam when one saw the role of social media in revealing and facilitating the (dis)congruity between connectivism, collectivism, and conservatism. On June 12, the National Assembly of Vietnam passed the controversial Cybersecurity Law by a landslide of 86 percent agreement despite widespread public dissent, including an online petition signed by more than sixty-five thousand people. The new Cybersecurity Law was said to further restrict the already limited freedom of expression in Vietnam and grant too much power to the police in surveying and punishing online citizens.