As artificial intelligence (AI) technology expands into decision-making domains such as recruitment, concerns over fairness, transparency, and public trust have emerged. This study examines public acceptance of AI in high-risk applications, focusing on AI-driven recruitment processes. Using secondary data analysis and a survey of the Korean public, the research explores factors influencing AI acceptability. The findings reveal that trust in humans plays a critical role in shaping attitudes toward AI. Individuals with lower interpersonal trust are more likely to accept AI, as they perceive it to be a fairer alternative to human decision-makers, who may be influenced by bias. Cross-national analysis further supports this pattern, showing that countries with lower interpersonal trust exhibit higher trust in AI. Hierarchical regression analysis confirms that trust in AI technology itself is the strongest predictor of its acceptance, while distrust in human recruiters significantly increases the likelihood of preferring AI-driven hiring. These findings highlight the complex relationship between human trust, AI acceptance, and perceptions of fairness. As AI continues to be integrated into decision-making, ensuring transparency and addressing algorithmic bias will be crucial. Future research should explore how interpersonal trust influences AI adoption across different cultural and regulatory contexts.
Chung et al. (Tue,) studied this question.