Colleague, Copilot, Companion, Controller – Roles of AI in Work Systems
Abstract
We initially present some findings on the importance of artificial intelligence for current HFE research based on a bibliometric study of the proceedings of the most recent annual conference of the Human Factors / Ergonomics Society in Germany (GfA, 2024). Given that importance we discuss the duality of AI as a tool and a player in work systems and based on extant research suggest that the aspects of hierarchy and emotion are considered when designing roles for AI. Using these aspects as dimensions we span a portfolio and suggest ‘colleague’, ‘copilot’, ‘companion’, and ‘controller’ as potential roles for AI in work systems thereby contributing to the discussion and analysis of yet to be properly defined “AI-infused” work systems.
Keywords: Artificial Intelligence, Human-AI collaboration, Work Systems, Roles, Hierarchy, Emotion, Human-Factors / Ergonomics
DOI: 10.54941/ahfe1005746
Cite this paper
More from this volume
- Implementing an AI Fatigue Risk Management System for Aviation Maintenance SMS: A Technology Enhanced Critical Process Human Factors Safety Plan
- Deep Learning Forecast of Perceptual Load Using fNIRS Data
- Artificial intelligence in the function of improving port systems
- Formalizing Trust in Artificial Intelligence for Built Environment Decision-Making
- Artificial Intelligence and Design: Innovation, Practical Applications, and Future Creative Horizons
- Supporting Informal Sustainability Learning with AI-assisted Educational Technology
- An assessment of the maintenance of heritage buildings using AI and IoT: a South African perspective
- What if we Could Entangle Drones? Towards the Management of a Swarm of Drones as a Non-Local Quantum Object
- Engaging All Elderly Residents in Community Renewal: Designer Spotlight Interview Tool for LLM Building
- AI Play in Higher Education: Students’ perceptions of play and co-creation of knowledge with generative AI
- Optimizing AI Involvement in Engineering University Courses Based on Students' Personality
- Predictive Model for Partner Agencies Dependency on Food Banks


AHFE Open Access