AI use for cybervetting
Exploring hallucination disclaimers and applicants’ race in applicant evaluations and hiring decisions
Bibliographic Data
| ID | 21422337 |
|---|---|
| Authors | J R Frampton (0000-0001-9436-7521, The University of Tennessee), William Roth Smith (0000-0001-9289-1397, The University of Tennessee, corresponding author) |
| Year | 2026 |
| Volume | 54 |
| Issue | 1 |
| Pages | 21-41 |
| Publication date | 2026-01-02 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Journal of Applied Communication Research (JOURNAL) |
| Journal identifiers | ISSN: 0090-9882 • E-ISSN: 1479-5752 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/00909882.2025.2602653 |
| OpenAlex | W4417441825 |
| Language | EN |
| Citations received | 1 |
| References cited | 45 |
Organizations use artificial intelligence (AI) to screen job candidates. However, inaccurate information provided by AI can negatively affect employment outcomes, especially for underrepresented groups. U.S. lawmakers suggest adding hallucination disclaimers to AI outputs to mitigate biased decision-making. Thus, drawing from truth default theory and correspondent inference theory, our 2 × 2 experiment examined how hallucination disclaimers and applicants’ race affect judgments about applicants’ deceptive behavior, subsequent attributions about applicants’ traits, and ultimately evaluators’ hiring decisions when AI-vetted information conflicts with candidate-supplied information. AI literacy was also examined as a potential moderator. Results show that exposure to hallucination disclaimers reduces perception of deception in job applications. The perception that a person lied in an application predicted judgments about their honesty and negatively impacted their likelihood of being hired. Theoretical and practical implications are discussed
Affect (linguistics) · Employment discrimination · Personnel selection · Qualitative research · Race (biology) · AI in Service Interactions · Employer Branding and e-HRM · Ethics and Social Impacts of AI
Mails - Meta AI literacy scale
Artificial Intelligence in Human Resources Management
Conceptualizing AI literacy
From Acts To Dispositions The Attribution Process In Person Perception
Race in the Courtroom
Machine Heuristic
Ethics and discrimination in artificial intelligence-enabled recruitment practices
The Intuitive Psychologist And His Shortcomings
Are Emily and Greg More Employable Than Lakisha and Jamal? A Field Experiment on Labor Market Discrimination
The Ultimate Attribution Error
Does AI Debias Recruitment? Race, Gender, and AI’s “Eradication of Difference”
Social Media Use in Organizations
How Black Are Lakisha and Jamal? Racial Perceptions from Names Used in Correspondence Audit Studies
Artificial intelligence and mass personalization of communication content—An ethical and literacy perspective
The worker as politician
When the alteration of information is viewed as deception
Different ways new information technologies influence conventional organizational practices and employment relationships
The correspondence bias
Résumé screening heuristic outcomes
Distinguishing technologies for social interaction
Discrimination in a Low-Wage Labor Market
Walking the Talk? What Employers Say Versus What They Do
The hunt for red flags
Truth-Default Theory (TDT)
| Citations per year | 1 |
|---|---|
| Citation span | 2026 - 2026 (1) |
| Highly cited | No |