AI Transparency Satisfaction
Information SystemsReliability: alpha 0.893 sample items
About this scale
A multi-item measure of user satisfaction with AI transparency — clarity about how the AI works, what data it uses, and how decisions are made.
Sample item(s)
“I understand how the AI system makes its decisions”
“The AI provides clear information about its data sources”
“The AI is transparent about its limitations”
Reliability
Reported internal consistency: alpha 0.89. As a rule of thumb, Cronbach’s α ≥ .70 is considered acceptable, ≥ .80 good, and ≥ .90 excellent for established measures.
Notes
Pair with XAI satisfaction.
Source & citation
Liao, Q. V., Gruen, D., & Miller, S. (2020): Questioning the AI: Informing design practices for explainable AI user experiences. Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, Article 463.
Source. Scale details are summarised from the publication cited above. Always consult the original source for the full item set, scoring, and permission to use.
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