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• W3130266503 abstract "Societies have always used their heritage to remain resilient and to express their cultural identities. Today, all the still-available experiences accrued by human societies over time and across space are, in principle, essential in coping with the twenty-first century grand challenges of humanity (refer to the 17 UN Sustainable Development Goals). Artificial intelligence and machine learning algorithms can assist the next generation of historians, heritage stakeholders, and decision-makers in (1) decoding unstructured knowledge and wisdom embedded in selected cultural artefacts and social rituals, (2) encoding data in machine-readable systems, (3) aggregating information according to the user’s needs in real time, and (4) simulating the consequences of either erasing, neglecting, putting in latency, or preserving and sharing specific human experiences. What our global society needs is a multilingual and transcultural approach to decode-encode the treasure of human experience and transmit it to the next generation of world citizens. This approach can be the pathway to work on a new science of heritage, its ethics, and empathy." @default.
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• W3130266503 date "2021-02-15" @default.
• W3130266503 modified "2023-10-11" @default.
• W3130266503 title "Defining Heritage Science: A Consilience Pathway to Treasuring the Complexity of Inheritable Human Experiences through Historical Method, AI, and ML" @default.
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• W3130266503 doi "https://doi.org/10.1155/2021/4703820" @default.
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