The impact of mental health disorders on determining criminal responsibility in Iraqi and Emirati law.

Abstract

AI is revolutionising human resource management (HRM) by automating recruiting, performance evaluation, workforce analytics, employee engagement, and talent development. While AI offers increased efficiency, data-driven decision-making, and personalisation, its implementation presents substantial legal, ethical, and administrative issues. Algorithmic bias can result in discriminatory outcomes, making companies liable under anti-discrimination legislation and data protection regimes like the GDPR and the EU AI Act. Opacity ("black box" judgements), invasions of privacy, depreciation of human dignity, and accountability gaps are all ethical difficulties. Managers encounter skills shortages, reluctance to change, integration challenges, data quality issues, and strategic misalignment. This article synthesizes recent literature and regulatory developments to examine these challenges and outlines governance, technical, and organizational responses necessary for responsible AI-HRM. Successful integration requires human oversight, bias auditing, transparency, clear accountability frameworks, and alignment with organizational values to balance efficiency with fairness, trust, and compliance