The incorporation of Artificial Intelligence (AI) in crisis translation offers a wide range of practical possibilities for responders. Nevertheless, it is crucial to blend these technologies responsibly with the expertise of professional human translators and field specialists. This collaborative method ensures the ethical and precise application of AI-powered translation tools, facilitating immediate comprehension of vital information.

This approach encompasses several facets, including the need for training and guidelines to ensure responsible and timely use of machine translation. It involves educating individuals in machine translation literacy [12], establishing policies that outline when and how to utilize machine translation [13], particularly in crisis scenarios. Training sessions are essential not only for the use but also to prevent misuse of all available tools, emphasising the importance of human guidance to ensure responsible utilisation [14].

Additional valuable tools, in conjunction with essential policies and training, include sentiment analysis, which aids in assessing public emotions, thereby enabling more compassionate crisis responses. They also include the implementation of multilingual chatbots, driven by AI, to supports communication and assistance in various languages and enhance efficiency and accessibility. AI algorithms for data extraction and summarisation can be used to expedite the processing of vast datasets, allowing responders to focus on critical details. Voice-to-text translation, when supported by human expertise, ensures quick transcription and translation of spoken words in diverse languages.

Additionally, language models predict linguistic challenges, aiding in proactive messaging adjustments. Cross-lingual information retrieval using AI assists users in accessing relevant resources in different languages. Real-time collaboration platforms with AI-driven translation features facilitate communication among diverse responders. AI can also contribute to dynamic resource allocation based on the evolving linguistic demands of the crisis.

On the other hand, ensuring continuous model improvement, incorporating AI and user feedback, is necessary to ensure models’ adaptability to the changing linguistic landscape of crisis scenarios. Overall, the integration of AI within VOICEPATH offers a responsible approach to overcoming language barriers and enhancing crisis communication, guided by the collaborative efforts of human experts in translation, human rights, and crisis response.