  With the increased adoption of artificial intelligence (AI) in industry and
society, effective human-AI interaction systems are becoming increasingly
important. A central challenge in the interaction of humans with AI is the
estimation of difficulty for human and AI agents for single task
instances.These estimations are crucial to evaluate each agent's capabilities
and, thus, required to facilitate effective collaboration. So far, research in
the field of human-AI interaction estimates the perceived difficulty of humans
and AI independently from each other. However, the effective interaction of
human and AI agents depends on metrics that accurately reflect each agent's
perceived difficulty in achieving valuable outcomes. Research to date has not
yet adequately examined the differences in the perceived difficulty of humans
and AI. Thus, this work reviews recent research on the perceived difficulty in
human-AI interaction and contributing factors to consistently compare each
agent's perceived difficulty, e.g., creating the same prerequisites.
Furthermore, we present an experimental design to thoroughly examine the
perceived difficulty of both agents and contribute to a better understanding of
the design of such systems.
