Sociotechnical imaginaries of social inequality in the design and use of AI recruitment technology
Bibliographic Data
| ID | 12657992 |
|---|---|
| Authors | L Sartori (0000-0002-4490-6686, University of Bologna, corresponding author), Catherine Collett (0000-0002-2806-1273, Oxford Internet Institute, University of Oxford, Oxford, United Kingdom) |
| Year | 2025 |
| Volume | 27 |
| Issue | 3 |
| Pages | 409-432 |
| Publication date | 2025-04-22 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | European Societies (JOURNAL) |
| Journal identifiers | ISSN: 1461-6696 • E-ISSN: 1469-8307 |
| Publisher | Routledge (PUBLISHER • GB) |
| DOI | 10.1162/euso_a_00035 |
| OpenAlex | W4409655453 |
| Language | EN |
| References cited | 54 |
Through interviewing 12 companies in Italy that either design (vendors) or use (clients) AI recruitment technology systems, we explore how these companies perceive their systems to interact with issues of social inequality and how these perceptions, in practice, carry societal impacts. Three sociotechnical imaginaries (Jasanoff and Kim, 2015) were consistently embedded within these companies’ visions of this intersection: the third eye, the river, and the car bonnet. Through critically analysing these imaginaries, we find that they exhibit an overriding desire for productivity and talent capture from clients, and a consequential de-prioritisation of addressing social inequality and scrutinising the ways it could be reproduced from both vendors and clients. It demonstrates that the current ‘desired’ futures, shown by the sociotechnical imaginaries that vendors and clients share for AI recruitment technologies (AI-rec-tech) are really leading us towards an ‘undesirable’ future of hiring that continues to perpetuate social inequality. This study contributes one of the first pieces of empirical work to simultaneously assess the perceptions of AI-rec-tech vendors’ and clients’ surrounding social inequality, to shed light on the priorities for design and the motivations for usage, and to reflect upon how these impact society. This is a significant and original contribution to the evolving body of literature on AI-rec-tech in sociology, critical data studies, and communications
Inequality · Knowledge management · Social inequality · Sociology · Sociotechnical system · Computer Science · Digital Economy and Work Transformation · Ethics and Social Impacts of AI · Mathematics
More than a Glitch
Algorithms of Oppression
Discriminated by an algorithm
What is Education For? On Good Education, Teacher Judgement, and Educational Professionalism
Mitigating bias in algorithmic hiring
Artificial Intelligence in Human Resources Management
The Relevance of Algorithms
Disability, fairness, and algorithmic bias in AI recruitment
A sociotechnical perspective for the future of AI
Where fairness fails
Responsibility, rationality, and acceptance
Investing in AI for social good
Online Interviewing
Dreamscapes of Modernity
Feminist Research Practice
Does AI Debias Recruitment? Race, Gender, and AI’s “Eradication of Difference”
The Hustle
Regimes of justification in the datafied workplace
Why has the growth of female employment in Italy been so slow
No Sissy Boys Here
Containing the Atom
Understanding perception of algorithmic decisions
Using thematic analysis in psychology
How sociotechnical imaginaries shape consumers’ experiences of and responses to commercial data collection practices
Automating Inequality
Big Data and Human Resources Management
Emotional Expressions Reconsidered
Artificial Intelligence
Fit and Skill in Employee Selection
Toward a Sociology of Artificial Intelligence
Platforms Disrupting Reputation
The Society of Algorithms
The ethnographer and the algorithm
Recruitment
| Citation velocity | historical |
|---|---|
| Highly cited | No |