Spelling deficiencies are becoming a growing concern among employers, but few studies have quantified this phenomenon and its impact on recruiters’ choice. This article aims to highlight the relative weight of the form (the spelling skills) in application forms, compared with the content (the level of work experience), in recruiters’ judgment during the selection process. The study asked 536 professional recruiters to evaluate different application forms. The results show that the presence of spelling errors has the same detrimental impact on the chances of being shortlisted as a lack of professional experience, and recruiters’ spelling skills also moderate their judgment.

Despite the time spent on writing at work and employers’ dissatisfaction with their employees’ spelling skills, little is known about recruiters’ attribution, and decision making when they read application forms with spelling errors. This study examines the impact of spelling and typographic errors on recruiters’ attributions about applicants, and on their shortlisting decision. Based on a sample of 20 French recruiters, we conducted an experiment to collect both qualitative data through the verbal protocol method and quantitative data. Specific verbal reports are associated with different types of errors. Recruiters also form attributions about candidates. We demonstrate that spelling errors affect recruiters’ behavior more negatively than typographic ones. We discuss the implications of these findings for researchers and practitioners.

Resume screening assisted by decision support systems that incorporate artificial intelligence is currently undergoing a strong development in many organizations, raising technical, managerial, legal, and ethical issues. The purpose of the present paper is to better understand the reactions of recruiters when they are offered algorithm-based recommendations during resume screening. Two polarized attitudes have been identified in the literature on users’ reactions to algorithm-based recommendations: algorithm aversion, which reflects a general distrust and preference for human recommendations; and automation bias, which corresponds to an overconfidence in the decisions or recommendations made by algorithmic decision support systems (ADSS). Drawing on results obtained in the field of automated decision support areas, we make the general hypothesis that recruiters trust human experts more than ADSS, because they distrust algorithms for subjective decisions such as recruitment. An experiment on resume screening was conducted on a sample of professionals (N = 694) involved in the screening of job applications. They were asked to study a job offer, then evaluate two fictitious resumes in a 2 × 2 factorial design with manipulation of the type of recommendation (no recommendation/algorithmic recommendation/human expert recommendation) and of the consistency of the recommendations (consistent vs. inconsistent recommendation). Our results support the general hypothesis of preference for human recommendations: recruiters exhibit a higher level of trust toward human expert recommendations compared with algorithmic recommendations. However, we also found that recommendation’s consistence has a differential and unexpected impact on decisions: in the presence of an inconsistent algorithmic recommendation, recruiters favored the unsuitable over the suitable resume. Our results also show that specific personality traits (extraversion, neuroticism, and self-confidence) are associated with a differential use of algorithmic recommendations. Implications for research and HR policies are finally discussed.

Le marché des outils d’aide au recrutement intégrant des modules d’intelligence artificielle est en plein essor. Parmi les arguments utilisés pour promouvoir ces dispositifs, figure la promesse que ceux-ci permettraient de favoriser un recrutement non discriminatoire, en raison de leur capacité supposée à éliminer les biais de jugement humains. L’objectif de cette revue des recherches est de montrer que ces promesses sont difficilement tenables, car la correction de certains biais de jugement est contrecarrée par l’émergence de nouveaux biais induits par l’usage de l’IA 1 .

During the preselection process, recruiters use cues from résumés to form attributions about applicants' suitability. They rely on visible characteristics (e.g., origin) that activate stereotypes that can lead to discriminatory decisions. The anonymization of application forms is a possible intervention to avert discrimination. The few studies on this topic led to inconsistent conclusions. The present study aims to extend previous findings by comparing decisions on anonymous and standard résumés that differ in quality. Recruiters (N = 1,031) assessed a series of application forms whose profile (Caucasian, Moroccan, overweight, normal stature) and résumé content (experience, spelling errors) differed. Results show that anonymous application forms are rated more severely than standard forms, and are effective in neutralizing discriminatory behaviors toward overweight applicants. K E Y W O R D Sdiversity, inclusion, placement, recruitment, selection