Measuring attitudes toward responsible AI in engineering – development and validation of the RAISE scale

European Journal of Engineering Education, pp. 1–23

Abstract

As Artificial Intelligence (AI) technologies increasingly shape the field of engineering, ethical considerations are becoming essential for fostering responsible innovation. However, a validated instrument to assess attitudes toward Responsible AI, specifically in the engineering domain, is still missing to date. This study presents the development and validation of the Responsible AI Attitudes Specific to Engineering (RAISE) scale. After refining the item pool of a validated test instrument with expert input from the engineering domain, we conducted confirmatory factor analysis on data from 235 engineering students and professionals in Germany. The resulting 15-item scale measures engineers’ self-reported attitudes along three core Responsible AI dimensions: do-no-harm, transparency, and privacy. It demonstrates acceptable model fit, internal consistency, and measurement invariance across demographic groups. The RAISE scale can serve as a diagnostic and evaluative tool in engineering education and training programmes, helping to inform and assess efforts to foster Responsible AI engagement.

Authors 6

1. Marie Mirsch corresponding Aachen Gender and Diversity in Engineering (GDI)

   RWTH Aachen University

   Affiliation as printed

   Gender and Diversity in Engineering, RWTH Aachen University, Aachen

2. Nils Knoth

   University of Kassel

   Affiliation as printed

   Department of Psychology, Universität Kassel, Kassel

3. Ben Schultz Aachen Gender and Diversity in Engineering (GDI)

   RWTH Aachen University

   Affiliation as printed

   Gender and Diversity in Engineering, RWTH Aachen University, Aachen

4. Katharina Bata

   Karlsruhe Institute of Technology

   Affiliation as printed

   Scientific Computing & Mathematics, Karlsruhe Institute of Technology, Karlsruhe

5. Johannes Schleiß

   Otto-von-Guericke-Universität Magdeburg

   Affiliation as printed

   Artificial Intelligence Lab, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany

6. Leicht-Scholten Carmen Aachen Gender and Diversity in Engineering (GDI)

   RWTH Aachen University

   Affiliation as printed

   Gender and Diversity in Engineering, RWTH Aachen University, Aachen