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The diversity challenge for leading companies: application of AI technologies in recruitment and selection


   Centre for Accountable, Responsible and Transparent AI


Bath United Kingdom Artificial Intelligence Business Data Science Disability Studies Gender Studies Human Resource Management Machine Learning Software Engineering

About the Project

This interdisciplinary PhD project addresses the diversity challenge for leading companies by critically questioning the use of AI in processes of recruitment and selection. Our recent research (Donnelly and Gamus, 2020) has found that while ethnic minorities are successful in gaining roles in top firms (e.g. FTSE100 companies, Times Top 100 Graduate Employers), they are less likely to gain high-paying roles in corporate headquarters. The lack of diversity in leading companies represents a deep-seated public policy challenge, and as AI technologies are used by leading firms in their recruitment, important questions are emerging about their social implications. This PhD research will combine theories and methods from computer science with the social sciences to address the following questions:

  • How is the use of AI currently changing recruitment processes and potentially impacting on the diversity of leading companies in the UK?
  • In what ways are leading graduate employers using AI in their recruitment processes?
  • How does this application of AI identify and (mis)recognise ‘talent’?
  • How does the use of AI in the scoring, screening and engagement phases of recruitment map on to the identities and dispositions of groups (e.g. social class, race and ethnicity)?
  • How should policies, both private and public, take account of innovations in the development and use of AI to address the diversity challenge?
  • How should the implementation and application of AI be developed to support these policy solutions?

The use of AI could reduce the lack of diversity in top firms by mitigating the bias that occurs when humans are directly involved in the screening of job applicants. But AI could itself introduce the same or different biases and so may have the potential to entrench biases on a larger scale. Some employers may recognise these biases and risks and may be using technological innovations to overcome them. This represents a significant challenge, especially for recruiters who are less reliant on institutionalised forms of capital (such as educational qualifications) and rely more on signifiers of ‘talent’ that are embodied in the dispositions, conduct and behaviour of people. It has been argued that recruitment bias stems from differences in the way groups (re)present themselves, and the kinds of dispositions they display to recruiters. If this is the case, a crucial question is how AI technologies are disrupting, exacerbating or continuing processes of social inequality.

The PhD student will develop the exact research approach and methodology. One suggested approach could involve accessing 1 or more leading companies and learn about their use of AI in HR systems. These AI technologies could then be analysed to examine how different social and ethnic groups might fare in their applications. Knowledge about how different social and ethnic groups (re)present themselves could be gathered from analysis of CVs and interviews with applicants. A second research approach could be to replicate and innovate in relevant AI technologies and use applicant CVs to test how different social and ethnic groups fare. Counter-factuals can be introduced across both research approaches, amending the CVs to investigate how the AI technologies respond, and amending the AI to investigate the effects on different applicants.

This project is associated with the UKRI Centre for Doctoral Training (CDT) in Accountable, Responsible and Transparent AI (ART-AI).

Applicants should hold, or expect to receive, a First or Upper Second Class Honours degree in a relevant subject. A master’s level qualification would also be advantageous. Desirable qualities in candidates include intellectual curiosity, and programming experience. You will also need to have taken a mathematics course or a quantitative methods course at university or have at least grade B in A level maths or international equivalent.

Enquiries about the project should be sent to Dr Donnelly.

Formal applications should be accompanied by a research proposal and made via the University of Bath’s online application form. Enquiries about the application process should be sent to .

Start date: 3 October 2022.


Funding Notes

ART-AI CDT studentships are available on a competition basis and applicants are advised to apply early as offers are made from January onwards. We reserve the right to close the advert if all funded places are filled. Funding will cover tuition fees and maintenance at the UKRI doctoral stipend rate (£15,609 per annum in 2021/22, increased annually in line with the GDP deflator) for up to 4 years.
We also welcome applications from candidates who have their own funding.

References

Donnelly, M., & Gamsu, S. (2019). The field of graduate recruitment: leading financial and consultancy firms and elite class formation. British Journal of Sociology, 70(4), 1374-1401. https://doi.org/10.1111/1468-4446.12659

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