This paper introduces a “responsible intelligence” framework that tackles safety, ethics, and cultural sensitivity. First, it leverages active learning together with graph‑based knowledge to achieve domain adaptation in specialized fields, markedly reducing hallucinations. Second, a decoding‑time alignment mechanism is proposed to intercept harmful text in real time, strengthening ethical rigor. Third, language‑specific steering is employed to respect diverse linguistic and social norms, ensuring multilingual cultural safety. Experiments on medical and legal datasets show the model outperforms baselines in accuracy, hallucination rate, and harmful text generation. The framework offers a blueprint for building next‑generation AI that is contextually knowledgeable, ethically sound, and culturally adaptable.
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