Algorithmic Bias in AI-Driven Hiring Platforms and Its Intersectional Impact on Social Inequality: A Survey of Job Seekers and Platform Users in the Global South
DOI:
https://doi.org/10.65761/jssp.2025.21Keywords:
Algorithmic bias, AI-driven recruitment, Intersectionality, Social inequality, Global SouthAbstract
Background: Artificial intelligence (AI) is increasingly used in recruitment to improve efficiency and automate candidate screening. However, concerns persist that algorithmic bias may reinforce existing social inequalities, particularly among vulnerable populations in the Global South.
Objective: To investigate perceptions of algorithmic bias in AI-driven hiring platforms and examine its intersectional impact on social inequality among job seekers and platform users in the Global South.
Methods: A cross-sectional online survey was conducted among 550 respondents recruited through LinkedIn, Facebook groups, university networks, freelancing forums, and WhatsApp communities. Data were collected using a structured questionnaire assessing perceived algorithmic fairness, experiences of discrimination, trust in AI hiring systems, employment outcomes, and attitudes toward AI governance. Statistical analyses included descriptive statistics, reliability analysis, ANOVA, correlation analysis, multiple regression, and moderation analysis.
Results: Women, respondents from lower socio-economic backgrounds, and individuals with lower educational attainment reported significantly higher perceptions of algorithmic discrimination. Digital literacy and previous exposure to AI technologies were positively associated with trust in AI recruitment systems and perceived fairness. Significant interaction effects among gender, socio-economic status, and education indicated that multiple social disadvantages amplified perceptions of algorithmic bias. Participants also expressed substantial concerns regarding transparency, accountability, and fairness in AI-assisted hiring.
Conclusion: AI-driven recruitment systems may unintentionally reproduce existing social inequalities if fairness safeguards are absent. Transparent algorithms, routine bias auditing, inclusive governance, and equitable AI policies are essential to promote fair hiring practices and equal employment opportunities in increasingly digital labor markets.
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