A multimodal framework combines speech, text, and image data with gradient reversal unlearning to reduce demographic bias in Mild Cognitive Impairment detection. The method outperforms existing multilingual and multimodal baselines on TAUKADIAL and PREPARE, with reduced performance gaps across sex and language subgroups, and shows improved transfer across datasets.