A systematic literature review on the impact of data mining on workforce privacy and employment practices: ethical concerns and risks

Ismail, Azratul Ain Nadiah and Mohamad, Ahmad Nadzri (2025) A systematic literature review on the impact of data mining on workforce privacy and employment practices: ethical concerns and risks. Journal of Information and Knowledge Management (JIKM), 15 (2): 5. pp. 55-71. ISSN ISSN:2231-8836 ; E-ISSN:2289-5337

Official URL: https://journal.uitm.edu.my/ojs/index.php/JIKM

Identification Number (DOI): 10.24191/jikm.v15i2.6962

Abstract

Data mining tools enabled by artificial intelligence can change the norms in employment practices. Employers can capitalize on data mining technologies to assist in the hiring process, employee performance assessment and behavior surveillance at the workplace. While these practices are becoming more prevalent, there is a lack of consolidated research that covers the ethical concerns of data mining on workforce privacy and employment practices. Given this context, the study examines ethical concerns and risks associated with using data mining tools in the respective sphere. The research applied the PRISMA 2020 statement for a systematic literature review. A Python script was used to assist in selecting relevant articles based on selected keywords. VOSviewer was utilized as a bibliometric mapping tool to provide a preliminary understanding of the retrieved scholarly articles. The study reviewed 154 scholarly articles from four online databases. This led to the inclusion of 21 articles for the systematic literature review. The findings suggest that employees are concerned about system biases and unconsented data usage for algorithmic decisions in employment practices. This includes the lack of transparency in using data mining tools and artificial intelligence. Another concern is using emotional data for employee profiling. Emotional data can be used to monitor work performance and behaviour through wearable devices or cameras. As such, employees have a 'trust deficit' with data mining tools and systems in work-related decision making. This is when employees view these systems as having 'less empathy' in decision-making. For that reason, better mechanisms are required to enhance trust and confidence in using these systems. This includes strengthening legal aspects and frameworks to secure employees' trust and rights. Future studies can use the findings as a theoretical basis to explore the research topic in medium and large corporations across countries.

Metadata

Item Type: Article
Creators:
Creators
Email / ID Num.
Ismail, Azratul Ain Nadiah
UNSPECIFIED
Mohamad, Ahmad Nadzri
nadzri.mohamad@gmail.com
Subjects: H Social Sciences > HD Industries. Land use. Labor > Labor. Work. Working class > Employee participation in management. Employee ownership. Industrial democracy. Works councils
H Social Sciences > HD Industries. Land use. Labor > Labor. Work. Working class > Employers' associations
H Social Sciences > HF Commerce > Personnel management. Employment management
Divisions: Universiti Teknologi MARA, Selangor > Puncak Perdana Campus > Faculty of Information Management
Journal or Publication Title: Journal of Information and Knowledge Management (JIKM)
UiTM Journal Collections: UiTM Journals > International Journal of Information and Knowledge Management (JIKM)
ISSN: ISSN:2231-8836 ; E-ISSN:2289-5337
Volume: 15
Number: 2
Page Range: pp. 55-71
Keywords: Algorithmic Decision-Making, Data mining, Employee Autonomy, Ethics, Privacy
Date: October 2025
URI: https://ir.uitm.edu.my/id/eprint/128251
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