Paper Details
AI-Driven Performance Evaluation and Employee Perceptions of Fairness
Authors
Anjali Rawat, Vijay Rawat, Gulshan Joshi
Abstract
By offering data-driven assessments that strive to improve efficiency and objectivity, artificial intelligence (AI) is revolutionizing conventional appraisal systems and how they evaluate employees' performance. It is essential, however, to continue researching how AI-driven performance reviews affect workers' views of fairness. Examining the effects of AI-based assessment systems on workers' perceptions of fairness, this study zeroes in on characteristics including honesty, impartiality, and confidence. The study used a quantitative method, gathering primary data from 115 randomly selected employees from different companies using AI-driven evaluation systems through structured surveys. The study's results show that there are pros and cons to AI. On one hand, workers are excited about the possibility of less bias, but on the other hand, they are worried about things like transparency and AI's inability to fully grasp qualitative performance aspects. The findings of this study should help with HR policy formulation by suggesting ways to make AI-driven evaluations seem fairer.
Keywords
Performance, Artificial Intelligence, Fairness, Transparency, Trust
Citation
AI-Driven Performance Evaluation and Employee Perceptions of Fairness. Anjali Rawat, Vijay Rawat, Gulshan Joshi. 2024. IJIRCT, Volume 10, Issue 6. Pages 1-9. https://www.ijirct.org/viewPaper.php?paperId=2411057