A Critical Perspective from AI- Assisted Architectural Heritage Conservation

Abstract

The integration of artificial intelligence into architectural design processes has created opportunities for creativity and innovation while simultaneously posing challenges regarding equity and fair participation in the labor market. This paper examines how algorithmic bias inherent in AI design tools can inadvertently marginalize architects from underrepresented cultural and regional contexts—particularly in the Middle East—and analyzes the impact of this bias on professional recognition, project distribution, and employment opportunities within the architectural sector. Concurrently, the paper explores how artificial intelligence is transforming the restoration, redesign, and documentation of historic buildings. Drawing on interdisciplinary literature regarding algorithmic systems and sociocultural design practices, researchers propose strategic approaches—including the use of culturally sensitive datasets, participatory design protocols, and continuous algorithmic review—to mitigate the perpetuation of cultural biases. Five artificial intelligence algorithms—Naive Bayes, Logistic Regression, Decision Tree, K-Nearest Neighbors, and Support Vector Machine—were trained and tested on visual datasets derived from historical archives and field surveys. The AI provided practical restoration assessments and creative architectural suggestions to preserve aesthetic and cultural identity. Compared to traditional methods, the AI approach was faster, more cost-effective, more accurate, and safer. The study concluded that artificial intelligence enhances the technical and cultural aspects of heritage rehabilitation, enabling more informed and sustainable restoration strategies. Future AI applications should incorporate multidisciplinary expertise, digital archives, and real-time structural health monitoring systems to improve accuracy and sensitivity. Furthermore, the ethics of intervention and cultural authenticity must be considered, alongside public engagement. Thus, this research contributes to advancing digitally enabled heritage preservation by employing intelligent algorithms to protect historical sites from the pressures of modern development; furthermore, it concludes by outlining practical implications for designers, policymakers, and AI developers, thereby contributing to broader efforts to ensure accountability and inclusivity in AI-mediated professional practices.