<![CDATA[The use of Generative Artificial Intelligence (GenAI) in higher education poses epistemic risks, including information hallucinations, limited accuracy, and content bias. Although AI developers include disclaimers as a risk mitigation measure, the effectiveness of this mechanism is often hampered by the phenomenon of warning fatigue, so it does not always encourage user evaluative behavior. This study aims to develop and validate the Artificial Intelligence Disclaimer Literacy Scale as a psychometric instrument to measure students' awareness, understanding, attitudes, and critical evaluation of AI disclaimers. The study employed a quantitative psychometric development design divided into five stages: literature review, indicator formulation, instrument item development, empirical testing, and statistical validation. The instrument was tested on 165 students at the Faculty of Teacher Training and Education. Data analysis included item validity testing using corrected item–total correlation, reliability testing using Cronbach's Alpha, and Exploratory Factor Analysis (EFA) using the Principal Component Analysis (PCA) method with Varimax rotation to test construct validity. The results showed that the AI-DLS instrument, consisting of 30 statement items, was proven valid and reliable. All items had a correlation value ≥ 0.30, with excellent reliability across all four dimensions (Cronbach's Alpha = 0.828 - 0.937). The EFA results showed a Kaiser–Meyer–Olkin (KMO) value of 0.932 and a factor structure capable of explaining 66.89% of the total variance. These findings indicate that the AI-DLS has strong psychometric qualities and is suitable for use as a diagnostic instrument to map students' epistemic readiness to interact with Artificial Intelligence systems critically and responsibly.]]>
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