AI to help find causes of and reduce labour market gender and ethnic bias
A new £1m project will tackle the problem of gender and ethnic bias in recruitment and human resource management.
BIAS – Responsible AI for Labour Market Equality will look at how Artificial Intelligence can lead to unintentional bias in the processes of job advertising, hiring and professional networking, which are increasingly digitalised.
Lancaster University will lead the three-year project, working alongside Essex University and the University of Alberta. The Economic and Social Research Council through UK Research and Innovation’s (UKRI) Fund for International Collaboration; the Canadian Institutes of Health Research (CIHR); the Natural Sciences and Engineering Research Council (NSERC); and the Social Sciences and Humanities Research Council (SSHRC) have provided funding of £987,000.
BIAS is one of ten interdisciplinary projects funded, worth a total of £8.2 million, where UK and Canadian researchers have joined forces for the first time to support the development of responsible AI.
The BIAS researchers will work with industrial partners to understand gender and ethnic bias within human resource processes, such as hiring and professional networking. They will analyse data from across hiring and recruitment platforms and develop new tools and protocols to mitigate and address such bias. This will allow companies, HR departments and recruitment agencies to tackle such issues in future recruitment.
Professor Monideepa Tarafdar, Professor of Information Systems and Co-Director of the Centre for Technological Futures at Lancaster University Management School, will lead the research as principal investigator, working with Lancaster colleagues Dr Yang Hu, from Sociology, and Dr Bran Knowles, from the School of Computing and Communications.
Professor Tarafdar said: “AI has reached the stage where the rubber is meeting the road and organisations are coming up against the road bumps. Bias is a huge one. We need to tackle labour market inequalities caused by gender and ethnic biases in hiring, job advertising and professional socialisation. They prevent equal and sustainable socio-economic development across all groups in society, and the recruitment process can often be the start of these issues. There are different causes and sources of this bias, and we want to investigate and mitigate them.
“In both the UK and Canada, access and rewards to work remain shaped around social distinctions, such as gender, race, and ethnicity, and the use of Artificial Intelligence is known to exacerbate such inequalities through a perpetuation of existing gender and ethnic biases in hiring and career progression.”
Dr Hu added: “We want to understand these biases and develop a tool that will mitigate against them. There is no way to remove all bias, and that would not be preferable – if I’m hiring somebody, I want there to be some variations that produces the best candidate – but we want to reduce it where we can to ensure fairness and equality in labour market processes.”
The research ties in with the UK's Industrial Strategy, which has 'putting the UK at the forefront of the AI and data revolution' as one of its grand challenges, as well as the UK's AI sector deal that aims to 'boost the UK's global position as a leader in developing AI technologies'. It also speaks directly to the Canadian SSHRC's goal of tackling persistent ethnic and gender disparities in workforce selection and development.
Dr Knowles said: “We believe that our research will allow businesses and recruitment agencies to better target potential employees without unintended bias that results in women or people from certain ethnic backgrounds from even applying for positions, let alone being recruited into them.”
The project will look to develop a protocol for responsible and trustworthy AI that reduces labour market inequalities by tackling gender and ethnic/racial biases in job advertising, hiring and professional networking processes.
Professor Jennifer Rubin,ESRC Executive Chair, said: “The increasing prevalence of artificial intelligence, machine learning and automation in our lives is generating a range of challenges and opportunities that demand better understandings and sophisticated solutions. This raises social, technical, and cultural questions that the social sciences in collaboration with other disciplines can help address.
“Recent work has revealed that there is not enough interdisciplinary collaboration in AI research,and that building bridges between the mathematical and computational sciences and other disciplines will enrich the field.
“Collaborating with Canadian funding agencies and other UKRI research councils (AHRC, EPSRC and MRC) on these projects using an interdisciplinary approach will contribute to the inclusive, responsible and impactful development of AI technologies, and address important economic, societal, health and global challenges.”
UK Research and Innovation works in partnership with universities, research organisations, businesses, charities, and government to create the best possible environment for research and innovation to flourish. They aim to maximise the contribution of each of their component parts, working individually and collectively. They work with their many partners to benefit everyone through knowledge, talent and ideas. Operating across the whole of the UK with a combined budget of more than £7 billion, UK Research and Innovation brings together the seven research councils, Innovate UK and Research England.Back to News