What Type of Explanation Do Rejected Job Applicants Want? Implications for Explainable AI

Applicants expect explanations as a matter of fairness: The survey found that job applicants believe employers have an obligation to provide explanations for rejection decisions, suggesting that transparency in hiring is viewed as a basic right rather than a luxury feature.

Generic feedback is insufficient and frustrating: Current employer practices of providing minimal or generic feedback leave applicants dissatisfied, indicating that any AI explanation system must go beyond vague statements to be meaningful to users.

Applicants want actionable, improvement-focused information: Rather than just learning they were rejected, applicants specifically want to understand why they were unsuccessful and receive guidance on how to improve for future applications—suggesting XAI systems should prioritize constructive feedback over mere decision justification.

There is a gap between XAI capabilities and user needs: While XAI researchers have developed many explanation techniques, this study reveals a mismatch between what's technically available and what rejected applicants actually want, highlighting the importance of user research in designing responsible AI systems.

Scale and fairness concerns intersect in hiring: The paper suggests XAI could help employers provide explanations "at scale," but this raises questions about whether automated explanations can genuinely address applicants' desire for personalized, meaningful feedback about their qualifications.