Trust in artificial intelligence within production management - an exploration of antecedents.

Journal: Ergonomics
Published Date:

Abstract

Industry 4.0, big data, predictive analytics, and robotics are leading to a paradigm shift on the shop floor of industrial production. However, complex, cognitive tasks are also subject of change, due to the development of artificial intelligence (AI). Smart assistants are finding their way into the world of knowledge work and require cooperation with humans. Here, trust is an essential factor that determines the success of human-AI cooperation. Within this article, an analysis within production management identifies possible antecedent variables on trust in AI and evaluates these due to interaction scenarios with AI. The results of this research are five antecedents for human trust in AI within production management. From these results, preliminary design guidelines are derived for a socially sustainable human-AI interaction in future production management systems. In the future, artificial intelligence will assist cognitive tasks in production management. In order to make good decisions, humans trust in AI has to be well calibrated. For trustful human-AI interactions, it is beneficial that humans subjectively perceive AI as capable and comprehensible and that they themselves are digitally competent.

Authors

  • Till Saßmannshausen
    International Production Engineering and Management, University of Siegen, Siegen, Germany.
  • Peter Burggräf
    International Production Engineering and Management, University of Siegen, Siegen, Germany.
  • Johannes Wagner
    Center for Bioinformatics, Universität Hamburg, Bundesstraße 43, 20146, Hamburg, Germany.
  • Marc Hassenzahl
    Ubiquitous Design, University of Siegen, Siegen, Germany.
  • Thomas Heupel
    FOM University of Applied Sciences, Siegen, Germany.
  • Fabian Steinberg
    Department of Sport Psychology, Institute of Sport Science, Johannes Gutenberg-University Mainz, Albert Schweitzer Straße 22, 55128, Mainz, Germany.