From Surveillance to Supervision: Supervisory Technology and Government Policies Framework: A Systematic Review of the Literature
DOI:
https://doi.org/10.61503/cissmp.v4i4.389Keywords:
Supervisory Technology (SupTech), Surveillance, Algorithmic Governance, Digital GovernmentalityAbstract
An interpretative systematic literature review was conducted which aimed to ascertain how conventional regulatory instruments, such as reporting and databases, have evolved in their approaches to technology (particularly supervisory technology or “SupTech”) via the introduction of Artificial Intelligence, Machine learning and Big Data analytics, hence transforming how regulators create and retain information with respect to regulated entities. The literature review indicated how SupTech enables sectoral regulators to move from the usage of data as a passive source for the collection of information, to actively governing entities with real-time decision-making; using data for automated, authoritative processes. The systematic literature review was conducted under the auspices of PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses), with a thorough investigation of peer-reviewed articles, white papers and conference papers from 2000 – 2025 across major scholarly databases, including Scopus, Web of Science, IEEE Xplore and Google Scholar. In light of the foundational articles, this study provides an understanding of SupTech under the umbrella of important theoretical frameworks related to Sup Tech, which include, inter-alia: Algorithmic Governance and Digital Governmentality.. The conclusion reached is that the required governance needs to balance the new technological innovations with ethical accountability and institutional capability
Downloads
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Muhammad Hasnain Ali, Huma Ali , Ahmad Tisman Pasha

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Contemporary Issues in Social Sciences and Management Practices (CISSMP) licenses published works under a Creative Commons Attribution-NonCommercial (CC BY-NC) 4.0 license.



