Education & Public Impact

Addressing Trust in AI Systems through Education: A Didactic Perspective (ICE-T)

Trust calibration as an explicit educational objective: representational richness, graduated process control (Use-Modify-Create), and capacity to contextualize errors are the teachable mechanisms behind appropriate reliance

Beyond Prompting

What the source reports

Trust calibration as an explicit educational objective: representational richness, graduated process control (Use-Modify-Create), and capacity to contextualize errors are the teachable mechanisms behind appropriate reliance

Original source

Title
Addressing Trust in AI Systems through Education: A Didactic Perspective (ICE-T)
Author
Haritz, Krone & Liebig
Publication
arXiv
Date
Wednesday, September 2, 2026