Case Study Archive
Recruitment shortlisting with the NHS England London Talent team
This project looked at the issue of bias in using AI to help compare and review job descriptions and applications. It will test how algorithms perform while placing careful scrutiny on the issues of ethics, equality and inclusiveness.
Recruitment for an organisation as large as the NHS is a time-consuming and expensive operation. If artificial intelligence can successfully manage bias while improving the speed and efficiency of selection processes, this could lead to fairer opportunities, greater inclusivity and reductions in time and cost.
The project began some research to explore the various existing approaches to using AI to solve this problem, from chat bots to CV screening, and automated decision-making processes to decision-making support tools, looking at the advantages and disadvantages they offer.
This will allow the London Talent team to make an informed decision about what type of solution might be suitable for the NHS, and the possibilities for overcoming bias in this context. We will then use pseudonymised applications for closed job vacancies to train and test a model to see if a solution can be found that accounts for bias. Pseudonymisation separates data from direct identifiers (e.g. name, surname, NHS number) and replaces them with a pseudonym (for example, a reference number), so that identifying an individual from that data is not possible without additional information.