Transdisciplinary Skills for AI Ecosystems: Using Future Visioning to Collaboratively Unpack Skills in UK Health and Emergency Response Scenarios

Abstract

Transdisciplinary practices in artificial intelligence (AI) requires good methodological techniques to bring researchers together from diverse disciplines. Different fields and traditions each may have an impact on the greater AI ecosystem, however, to properly gauge this impact, and include diverse voices, research methodologies must evolve to adopt new methods and techniques. To understand the shifting demands for new skills, we conducted a transdisciplinary workshop, bringing together stakeholders from industry, government and academia, by engaging with scenarios in healthcare and emergency response, using future visioning to imagine new skill requirements across job roles. We found that future visioning was a useful methodology to help frame discussions in a manner conducive to eliciting qualitative evidence of different policy approaches. Beyond individual skills, we propose the Human-AI Synergy Matrix as a collaborative competency framework, which integrates technical, professional, and strategic skills with levels of engagement such as awareness, communication, synergy, governance, and transformation. The matrix aims to facilitate evaluation and understanding of skills and critical issues in human-AI collaboration within AI ecosystems, emphasizing the need to address broader challenges in an interconnected manner.