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

TL;DR

This study investigates the types of explanations rejected job applicants desire, revealing that generic feedback frustrates applicants and they seek specific reasons and improvement guidance, highlighting implications for explainable AI in employment contexts.

Contribution

The paper provides empirical insights into applicant preferences for explanations, informing the development of more effective XAI tools for employment decisions.

Findings

Applicants are dissatisfied with generic feedback.

Applicants believe employers should provide explanations.

Applicants want to know why they failed and how to improve.

Abstract

Rejected job applicants seldom receive explanations from employers. Techniques from Explainable AI (XAI) could provide explanations at scale. Although XAI researchers have developed many different types of explanations, we know little about the type of explanations job applicants want. We use a survey of recent job applicants to fill this gap. Our survey generates three main insights. First, the current norm of, at most, generic feedback frustrates applicants. Second, applicants feel the employer has an obligation to provide an explanation. Third, job applicants want to know why they were unsuccessful and how to improve.