Responsible AI for labour market equality (BIAS)

Alla Konnikov, Irina Rets, Karen D. Hughes, Jabir Alshehabi Al-Ani, Nicole Denier, Lei Ding, Shenggang Hu and Dengdeng Yu

Chapter 5 in How to Manage International Multidisciplinary Research Projects, 2022, pp 75-87 from Edward Elgar Publishing

Abstract: This case study focusses on the BIAS project, an interdisciplinary and international collaboration between researchers in Canada and the UK, investigating Responsible AI for labour market equality. The project was funded by the UK Economic and Social Research Council (ESRC) and the Social Sciences and Humanities Research Council of Canada (SSHRC) under the Canada-UK Artificial Intelligence Initiative. Drawing on interviews with the founding team, and a survey with all team members, this case study examines how the core project team managed the research process. It illustrates the challenges of collaborating and decision-making in a highly diverse team, and the value of adopting an egalitarian approach to team management, based on flexible mindsets, and an openness towards disciplinary differences. The case study analyses the strategies developed to ensure effective communication across disciplinary and cultural boundaries. The discussion highlights the lessons learnt, and the practical solutions and rewards of intra- and inter-disciplinary work.

Keywords: Asian Studies; Business and Management; Development Studies; Economics and Finance; Education; Environment; Geography; Innovations and Technology; Law - Academic; Research Methods; General Academic Interest; Urban and Regional Studies (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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