Defining heritage science : a consilience pathway to treasuring the complexity of inheritable human experiences through historical method, AI and ML

• Main Author: Nanetti, Andrea
• Other Authors: School of Art, Design and Media
• Format: Article
• Language: English
• Published: 2020
• Subjects: Humanities; Computational History; Digital Humanities
• Online Access: https://hdl.handle.net/10356/144492
• Institution: Nanyang Technological University

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.