Theoretical analysis reveals optimal sense of agency in human-robot interaction, indicating that intermediate control maximizes motivation and performance.
Key Points
To examine the relationship between the human sense of agency and intrinsic motivation to define optimal control balances in AI-assisted robotic systems.
Synthesized theoretical frameworks linking psychological sense of agency with intrinsic motivation.
Evaluated application paradigms across industrial work environments and healthcare assistive robotics.
Proposes that intrinsic motivation peaks at an intermediate level of agency between full manual control and total system autonomy.
Identifies the calibrated balance between user control and machine autonomy as a critical design requirement for maximizing user engagement and operational performance.