Using Artificial Intelligence to classify Jobseekers
The Accuracy-Equity Trade-off
Bibliographic Data
| ID | 2116166 |
|---|---|
| Authors | Sam Desiere (0000-0001-7167-8466, KU Leuven), Ludo Struyven (0000-0002-6468-040X, KU Leuven) |
| Year | 2021 |
| Volume | 50 |
| Issue | 2 |
| Pages | 367-385 |
| Publication date | 2021-04-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Social Policy (JOURNAL) |
| Journal identifiers | ISSN: 0047-2794 • E-ISSN: 1469-7823 |
| Publisher | Cambridge University Press (CUP) (PUBLISHER) |
| DOI | 10.1017/s0047279420000203 |
| OpenAlex | W3021690546 |
| Language | EN |
| Citations received | 33 |
| References cited | 29 |
Artificial intelligence (AI) is increasingly popular in the public sector to improve the cost-efficiency of service delivery. One example is AI-based profiling models in public employment services (PES), which predict a jobseeker's probability of finding work and are used to segment jobseekers in groups. Profiling models hold the potential to improve identification of jobseekers at-risk of becoming long-term unemployed, but also induce discrimination. Using a recently developed AI-based profiling model of the Flemish PES, we assess to what extent AI-based profiling 'discriminates' against jobseekers of foreign origin compared to traditional rule-based profiling approaches. At a maximum level of accuracy, jobseekers of foreign origin who ultimately find a job are 2.6 times more likely to be misclassified as 'high-risk' jobseekers. We argue that it is critical that policymakers and caseworkers understand the inherent trade-offs of profiling models, and consider the limitations when integrating these models in daily operations. We develop a graphical tool to visualize the accuracy-equity trade-off in order to facilitate policy discussions
Equity (law) · Flemish · Machine learning · Political science · Profiling (computer programming) · Artificial Intelligence · Computer Science · Digital Economy and Work Transformation · Employment and Welfare Studies · Retirement, Disability, and Employment
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| Unique citing works | 33 |
|---|---|
| Citations per year | 8,25 |
| Citation span | 2022 - 2026 (5) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 33 |