Skilling the gap

: identifying barriers in AI education to open up pathways and broaden opportunities

Abstract

As technologies such as Artificial Intelligence (AI) and Robotics advance, it becomes more and more important for the public to understand these technologies and how to retrain in these areas if they wish. Further to this, the rapid advancement of these technologies has created a ‘skills gap’ which means companies need more workers with skills in AI-related areas to conduct their business. This thesis aims to understand the barriers preventing the public from taking advantage of opportunities to learn about or retrain in AI, particularly those who have the desire and resources to do so. Initially, 21 stakeholders (7 thought leaders, 2 industry experts, 6 adult educators and 6 members of public) were interviewed about AI training. This study was used to gain an understanding of current thoughts on AI training for the public. To further probe into the barriers identified by the interviews, two online surveys were designed to understand the requirements to work in AI-related areas. Firstly 39 members of the public were surveyed. They were questioned on what they believed were the skills, qualifications and traits needed to work in AI-related areas. As well as how these requirements could be obtained and how easy or difficult obtaining them would be. The second survey asked similar questions of 15 hiring managers about the requirements they looked for when hiring for these jobs. They were also asked about their company’s involvement in retraining and allowing employees to move into AI-related roles. Finally, a co- design strategy is proposed for development of community AI education (which did not go ahead because of the pandemic) as future work. The barriers identified include a lack of a clear path on how to move into AI-related roles and a stereotypical view of those who work in AI. Further to this there exists a narrow view of AI roles (as highly technical), and as such there is a lack of education for those who work alongside AI (rather than build or create it). Importantly, there is gatekeeping coming from experts, hiring managers and people themselves which prevents AI education from reaching those who are not technical or degree educated. Recommendations on how these barriers can be addressed and an outline of a co-design programme for community AI education have also been included.

Date of Award	9 May 2023
Original language	English
Awarding Institution	University of Bristol University of the West of England
Sponsors	Engineering and Physical Sciences Research Council
Supervisor	Sabine Hauert (Supervisor) & Lucy J Wenham (Supervisor)