Heritage Beyond Singular Narratives: Embracing Diversity in Participatory Heritage Planning Empowered by Artificial Intelligence

Heritage planning is a broadening scope, from conserving the heritage property to its cultural significance. Cultural significance is defined by attributes and values, respectively, the attributes motivate the listing of a resource as heritage, and the values justify the heritage listing. A value-based approach considers heritage planning as a dynamic process in which each stakeholder, including interdisciplinary experts and communities, can convey unique cultural significance to heritage, which may vary among stakeholders. This value-based approach is strongly recommended both in academia and, by international recommendations.

Recognition of varying cultural significance by different stakeholder groups can sometimes lead to tensions. Participatory heritage, however, aims to foster consensus-building while also acknowledging the value of conflict as a means to generate new ideas and solutions. Various studies have explored how to consider both majority and minority to construct more holistic and integrated decisions. Scholars so far have applied conventional research methods in participatory practices, which can be time-consuming and expensive, particularly for built heritage, where diverse stakeholder groups are involved. While automated methods have been effective in digital humanities, their application in heritage planning is still limited.

Therefore, the objective of this research is to identify the differences and similarities between different stakeholder groups on the cultural significance they convey to built heritage, by using Artificial Intelligence (AI) models (e.g., multi-label text classification) and information repositories (e.g., social media platforms). This research presents a theoretical framework of the crucial factors affecting consensus-building on the values and attributes defining the cultural significance of heritage, in a public participation process and the relations between these factors.

Based on the presented theoretical framework, a public participation methodological framework, empowered by AI, is developed and tested in the case study of Yazd, Iran. The study focuses on windcatchers, which are key attributes conveying outstanding universal value, as inscribed on the UNESCO World Heritage List. This research compares three main stakeholder groups’ perceptions: experts, policymakers, and users.

The findings reveal that there is consensus on acknowledging windcatchers as a valuable attribute in Yazd although stakeholder groups assign different values to windcatchers. The methodological framework, empowered by AI, demonstrates its ability to reveal the stakeholders’ understanding of the cultural significance of heritage properties. This

methodological framework is replicable for other case studies, and it is a valuable resource for fostering participatory heritage practices in the future.

This thesis contributes to the advancement of knowledge on the relationship between public participation, cultural significance, and AI in heritage planning based on the case study of windcatchers in Yazd. This research offers a critical reflection on the changes expected in heritage planning, going beyond singular narratives and embracing greater diversity. It emphasizes the contribution of stakeholders in defining cultural significance and acknowledges the rising importance of public participation, empowered by AI. The findings offer guidance to heritage practitioners, culture brokers, particularly public officers, and policymakers on how to consider and align the perceptions of various stakeholder groups on cultural significance conveyed to heritage for the benefit of inclusive heritage.