Automation in Human-Machine Networks: How Increasing Machine Agency Affects Human Agency
This addresses the problem of optimizing human-machine interaction for practitioners in fields like air traffic and crisis management, but it is incremental as it builds on existing case studies without introducing new methods.
The study investigated how increasing machine agency, such as through automation, affects human agency in human-machine networks, finding that automation can strengthen human agency via responsibility sharing and task allocation in domains like air traffic and crisis management.
Efficient human-machine networks require productive interaction between human and machine actors. In this study, we address how a strengthening of machine agency, for example through increasing levels of automation, affect the human actors of the networks. Findings from case studies within air traffic management, crisis management, and crowd evacuation are presented, exemplifying how automation may strengthen the agency of human actors in the network through responsibility sharing and task allocation, and serve as a needed prerequisite of innovation and change.