PERCEPTION OF AFFORDANCES IN INTERACTION WITH AUTONOMOUS SYSTEMS

The advancement and increasing prevalence of autonomous systems prompt natural questions regarding our understanding of affordances in interactions with them. Drawing from research in human-autonomy teaming and interaction with autonomous vehicles, we assert that autonomous systems represent a gradient increase in the complexity of structured information to be entrained but do not fundamentally alter existing affordance frameworks. That is, from a system view where the agent, the enhanced tool (autonomous in this instance), and the environment dynamically interact, autonomous systems represent a natural part of the information array that must be attuned to but are no different from learning to drive a car or ride a horse. Furthermore, we argue that current applications of autonomous systems, where they can be engaged or disengaged at will, is a natural extension of our current understanding of affordance under tool use, namely, that the perception of multiple affordances, in this case, resulted not from a shift in goal-directed intentions nor the diverse properties of the environment, but from a shift in the embodied capabilities of the agent.