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How Do Swedish Organizations Manage Bias in an AI-Based Recruitment Process?

EasyChair Preprint no. 10347

55 pagesDate: June 7, 2023


As technology has expanded in our society, organisations have happily chosen to implement technology to facilitate their tasks in a cost-effective way. Recruitment -and staffing companies have actively implemented artificial intelligence to streamline the process in a variety of ways. In this context, bias and discrimination has been a major issue in relation to AI-powered recruitment processes. Bias and discrimination have historically always been present in humans and it has also followed technology. The aim of this work is to investigate what measures and approaches organisations take to deal with bias in the recruitment process which uses artificial intelligence. Furthermore, the work aims to understand how Swedish organisations position themselves in relation to the ethical considerations and the ethical process that should be taken in organisations that use AI tools in the recruitment process. We want to do further research on how bias should be addressed in an AI-driven recruitment process and start in Sweden. The study has been conducted through a qualitative method to gain an in-depth insight and also form a good relationship with the interviewees. The results show that the focus is on the individuals in the organisation in relation to the AI tools. This is to monitor the individuals' own biases. The ethical process and ethical considerations presented in the work are what is required for organisations to be able to handle any bias that may emerge in AI-driven recruitment processes.

Keyphrases: Artificial Intelligence, Awareness, bias, Recruitment process, responsibility, transparency

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Gloria Munyaneza and Ida Louise Bengtsson},
  title = {How Do Swedish Organizations Manage Bias in an AI-Based Recruitment Process?},
  howpublished = {EasyChair Preprint no. 10347},

  year = {EasyChair, 2023}}
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