Integrating Human Judgment to Address Algorithmic Bias in HR Practices in the Indonesian Context
DOI:
https://doi.org/10.37641/jimkes.v13i6.4147Keywords:
Algorithmic Decision-Making, Bias, Fairness, HR, Human Judgment, TransparencyAbstract
Algorithmic decision-making is increasingly adopted in variance accounted for to streamline processes like recruitment, performance evaluations, and promotions, but it raises ethical concerns about bias, fairness, and transparency. This study aims to examine the risks, fairness challenges, and the role of human judgment in these systems. Using a qualitative literature review, the research analyzes existing studies to explore the benefits and ethical implications of algorithms in human resources. The findings reveal that algorithms enhance efficiency and objectivity but can perpetuate biases from historical data, potentially leading to unfair outcomes, particularly for marginalized groups. Human judgment is critical to ensure ethical decisions, addressing nuances like cultural fit that algorithms may overlook. In contexts like Indonesia, where cultural values influence workplace dynamics, tailored approaches are essential. The study concludes that organizations should implement regular audits, transparency protocols, and training for professionals to oversee algorithms effectively. Future research should develop fairness-focused algorithms and hybrid models integrating human oversight, especially in non-Western settings, to promote inclusive practices. This review contributes to balancing technological innovation with ethical considerations, fostering equitable human resources practices globally.
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