Evaluating the Impact of Artificial Intelligence on Work Ethics within Malaysian Regulatory Bodies

Citation

Ismail, Muhammad Athari and Goh, Mei Ling (2024) Evaluating the Impact of Artificial Intelligence on Work Ethics within Malaysian Regulatory Bodies. Pakistan Journal of Life and Social Sciences (PJLSS), 22 (2). ISSN 1727-4915

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Abstract

The advent of Artificial Intelligence (AI) is reshaping global professional sectors, driving innovations and operational efficiencies. In Malaysia, the burgeoning use of AI within regulatory frameworks prompts a critical evaluation of its ethical implications, particularly concerning work ethics. This research focuses on a Cyberjaya-based regulatory body, aiming to dissect AI's influence on organizational ethical norms and employee perceptions, underpinned by a comprehensive methodological framework. Previous studies have illuminated the necessity of ethical alignment in AI's organizational integration to enhance work ethics perception. Exploring AI's ethical landscape unveils challenges such as data privacy, algorithmic bias, and transparency. Previous works emphasize ethical governance's centrality, advocating for accountability and transparency in AI systems. The review extends to AI's ramifications on workforce dynamics, scrutinizing job roles, employee behaviour, and workplace culture alterations. Insights from studies highlighted that AI's dual role in augmenting and challenging work practices, with profound ethical considerations. Hence, this study will leverage the Unified Theory of Acceptance and Use of Technology (UTAUT), enriched with ethical considerations to frame AI's transformative role in professional environments. This study will provide an insight into the discourse on AI ethics, this study sheds light on the intricate relationship between AI and work ethics in Malaysian regulatory bodies. The study would also be able to advocate for ethical considerations in AI deployment, offering insights into policy development and future research directions.

Item Type: Article
Uncontrolled Keywords: Artificial Intelligence
Subjects: Q Science > Q Science (General) > Q300-390 Cybernetics
Divisions: Faculty of Business (FOB)
Depositing User: Ms Nurul Iqtiani Ahmad
Date Deposited: 03 Dec 2024 03:28
Last Modified: 03 Dec 2024 03:28
URII: http://shdl.mmu.edu.my/id/eprint/13184

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