Global organizations are increasingly utilizing artificial intelligence (AI) hiring tools to streamline recruitment processes. Initially perceived as a way to minimize administrative burdens and eliminate biases, these AI systems are now linked to perpetuating existing labor market inequalities, particularly affecting women with career breaks due to caregiving responsibilities. Research indicates that AI often favours linear career trajectories, penalizing non-linear resumes typical among women. Key AI functions, including resume screening and candidate matching, can inadvertently uphold historical hiring biases embedded in training data, disadvantaging women and non-white candidates. A LinkedIn survey revealed 70% of Indian recruiters leverage AI to identify hidden talent, yet these systems may still reinforce discriminatory patterns. To combat these biases, researchers advocate for equality-focused algorithms and diverse training datasets. Transparency in algorithmic criteria is essential, alongside robust regulations to promote fairness in AI-driven hiring practices. Organizations must combine AI efficiency with human oversight to ensure equitable candidate evaluations.
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