Sarah Sharples, University of Nottingham
The notion of automation has been the subject of much discussion amongst Ergonomics and Human Factors (E/HF) practitioners and researchers for many decades. More recently, automation – the replacement of elements of tasks previously conducted by humans with machines or computation – has been accompanied with discussion around autonomy.
The notion of autonomy builds on automation, but includes consideration of an ‘intelligence’ or ‘decision maker’ within the system, and presents new challenges for E/HF design.
In complex systems, we rarely consider individual technology elements in isolation. As noted by authors including Hollnagel and Woods, we more frequently have a ‘joint cognitive system’ where multiple people work with multiple technologies to collaboratively complete tasks and actions. Therefore there is a need for theories that help us to understand the impact and inform the design of automation to take into account the complexity of context, and the collaborative nature of human-hybrid decision making.
This is becoming of importance in a range of contexts.
This paper will identify opportunities and challenges for automation and autonomy in three different contexts, drawn from case studies of current work: Transport, Healthcare and Manufacturing. In transport, the different requirements of and attitudes towards autonomous control in automotive, rail and aerospace will be considered, and particular challenges about the ethics of autonomy will be considered. In healthcare, work demonstrating the value of automated capture of work performance for clinicians will be presented. And in manufacturing, the opportunities for autonomy within future intelligent manufacturing will be identified.
The paper will conclude by considering how the current E/HF models of automation, which identify ‘levels’ of automation, should be adapted and evolved to take into account the increasing prevalence of autonomy, and the collaborative, hybrid and integrated nature of the joint cognitive system.