The Valley of Ontological Friction: Motivating, Framing, and Guiding HRI Research on Verisimilitude and Its Implications

Tom Williams and Alexandra Bejarano

ACM/IEEE International Conference on Human-Robot Interaction

Human-Robot Interaction (HRI) researchers use a range of methodologies for empirical, hypothesis-driven research, including laboratory experiments, longitudinal field deployments, and online experiments. Within these methods, field deployments are typically seen as granting greater validity (though with lessened ecological control) and online experiments are seen as granting greater control (though with lessened ecological validity). However, we argue that HRI researchers have largely ignored other threats to validity that uniquely emerge at the center of this spectrum. In this work, we analyze (1) how HRI experiments may also differ in terms of verisimilitude; (2) the nonlinear relation between verisimilitude and ontological coherence; (3) and the way that this creates a Valley of Ontological Friction that presents unique threats to validity. In doing so, we make a number of key contributions that help to motivate, frame, and guide future research. Specifically, we (1) introduce novel theoretically-grounded concepts; (2) identify key constructs that must be operationalized and measured in future work; (3) draw theoretical distinctions that HRI researchers should observe when discussing the consequences of their choice of experimental methodology; and (4) identify key guiding questions that the field of HRI should aim to pursue.