< Back to previous page

Project

In AI we trust: determinants of continuous trust in the user/system interaction

The number of interactions between humans and digital technologies grows rapidly. Technology and automation acceptance literature investigates these interactions and identifies trust as one of the major determining factors. As a result of human biases and technology malfunction, however, faulty interactions are also on the rise and cause users’ continuous trust in technologies to dwindle. This might lead to disuse, abuse or sabotage, which could result in suboptimal system performance, suffering companies or, worse, critical incidents.
In the context of trust in Artificial Intelligence-based systems in organisations, no models currently exist that explain the different factors of trust in AI-based systems, nor does the literature benefit from a validated measurement instrument.
This PhD project consists of three studies. The first study is a qualitative study to examine which factors influence users’ continuous trust in AI-based systems and subsequently develop an empirical model representing those factors. The second study is a quantitative study where we will test study 1’s preliminary model by developing and validating a survey to measure users’ continuous trust. The third study combines a quantitative approach and a case study approach to dive deeper into the role of personality traits, and more specifically Sensory Processing Sensitivity (SPS), regarding users’ trust. SPS describes individuals’ increased susceptibility to both positive and negative stimuli in the environment which, in a context of digital transformation and increased technology usage, might create different needs for different SPS-group regarding trust-building.
Overall, we strive to increase academics and practitioners’ understanding of the inner workings of users’ continuous trust relationship with AI-based systems in the workplace. The development of a survey instrument that can act as a standard tool to measure and understand said trust is a core element of our research project in order to gain insights in this trust relationship.
Date:1 Jul 2022 →  Today
Keywords:Artificial intelligence, Trust
Disciplines:Cognitive science and intelligent systems not elsewhere classified
Project type:Service project