Identification of Knowledge, Skills, Abilities and Other Behaviors to Predict Technological Fluency

Abstract

In industry, academia, military, and the public sector, future operations will require humans to team with increasingly sophisticated and evolving technologies, including artificial intelligence (AI). Critically, these future intelligent technologies will be required to adapt in-field to keep pace with competition and other emerging needs. As such, operators and leaders in these domains will require increased technological aptitudes and skills to leverage their expertise and creativity to work with and adapt these intelligent technologies. We refer to this aptitude as technological fluency (TF), or the ability of operators to use and rapidly adapt new and intelligent technologies without formal training on these systems. Knowing an individual’s level of TF can assist in staffing or team composition decisions and can inform where training efforts are likely to be most needed or fruitful. Technological fluency is a complex concept, however, so it is crucial to understand what sorts of knowledge, skills, abilities, and other behaviors (KSBs) are required for individuals to become technologically fluent. Here, we outline five preliminary categories of KSBs that we believe underlie technological fluency within human-technology interaction domains. Future efforts will aim to develop refined practical measures of TF and to test which KSBs are most predictive of TF across contexts.

Keywords: Technological Fluency, Human Computer Interaction, Technological Adaptation

DOI: 10.54941/ahfe1005022