Overview
A consistent theme in the debates around AI and work is the need for a highly skilled workforce to ensure society is economically competitive and can adapt to the ever-changing occupational landscape. Lifelong learning is recognised as central to these aims by policy makers, the commercial sector, and the public. As AI becomes increasingly commonplace, there has been an increasing interest in using AI for Education to support learning across the life course.
However, traditionally, AI in Education tends to conceptualise learning as a matter of acquisition, i.e., the process of obtaining skills typically via one to one interaction with an EdTech system. In a world mediated by AI this oversight is hugely problematic. A focus on acquisition risks increasing unemployment through automation and misses opportunities for positive social change as it neglects how people can learn by building new knowledge with AI systems. Drawing on a systematic review of the evidence, analysis of expert interviews, and theoretical modelling this project addresses two questions:
- In what ways can human-AI relations be conceptualised for lifelong learning?
- How might these different relationships mediate or exacerbate risks of automation in the workplace?
