AI-based tools in selection
Considering the impact on applicants with disabilities
Bibliographic Data
| ID | 21422071 |
|---|---|
| Authors | Sandra L Fisher (0000-0003-3385-1103, FH Münster, corresponding author), Silvia Bonaccio (0000-0002-1509-5028, Wilfrid Laurier University), Catherine E Connelly (0000-0002-5194-1404, McMaster University) |
| Year | 2024 |
| Volume | 53 |
| Issue | 1 |
| Pages | 101036 |
| Publication date | 2024-01-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Organizational Dynamics (JOURNAL) |
| Journal identifiers | ISSN: 0090-2616 • E-ISSN: 1873-3530 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.orgdyn.2024.101036 |
| OpenAlex | W4391815181 |
| Language | EN |
| Citations received | 1 |
Selection tools employing artificial intelligence (AI), such as automated video interviews (AVIs), chatbots, and assessment games, have become popular ways for organizations to deal with large numbers of job applicants. Vendors frequently claim that these technologies are unbiased. However, the impact of these tools on applicants with disabilities is rarely addressed. We explain how these tools may have both positive and negative impacts on applicants with disabilities. In doing so, we consider fundamental principles of selection: the reliability and validity of these tools as well as the applicant experience. We end by offering recommendations to organizations that are considering incorporating AI-based tools into their selection processes
Data science · Economics · Management · Personnel selection · Reliability (semiconductor) · Selection (genetic algorithm) · AI and HR Technologies · Applied Psychology · Artificial Intelligence · Artificial Intelligence in Healthcare and Education · Computer Science · Psychology
| Citations per year | 1 |
|---|---|
| Citation span | 2026 - 2026 (1) |
| Highly cited | No |