AN AHP BASED CRITERIA FOR ASSESSING AI ASSISTED DESIGNS AS PERCEIVED BY DESIGNERS
No Thumbnail Available
Date
2025-02-13
Authors
Kayed, Aseel
Journal Title
Journal ISSN
Volume Title
Publisher
An-Najah National University
Abstract
This thesis presents the development of an Analytical Hierarchy Process (AHP) framework to assess artificial intelligence (AI)-assisted architectural designs. The main objective is to construct a priority scale that reflects the experts' evaluation of the relative importance of different design elements. To this end, after an extensive systematic literature, four primary standards—authenticity, beauty, inventiveness, and harmony—were found to be crucial for judging architectural designs. Sub-criteria were derived from each of these primary criteria to offer a more detailed assessment.
A panel of professionals in the domains of architecture and artificial intelligence were administered a two-part questionnaire in order to inform the suggested framework. The participants' backgrounds and prior exposure to AI were gathered in the first section of the questionnaire. In the second section, the specified criteria and sub-criteria were evaluated. Thirty responses were collected and analyzed.
The AHP results show that, inventiveness with 35.5% weight is the most influential factor for assessing AI-assisted designs. Authenticity with a weight of 21.5% and harmony with a weight of 24% are, respectively, the next two most important criteria. Beauty was found to have a weight of 19%.
The most important sub-criterion for authenticity with their weights were found to be design consistency (36.1%), with material integrity (20.4%), authentic expression (22.7%), and historical context (20.8%). The top ranking factors for beauty are integration with the environment (43.7%), visual impact (22.1%), timelessness (20%), and detailing (14.2%). Emerged as the highest-ranking element of inventiveness is sustainable solutions (36.1%), with technical innovation (23.1%) and adaptive reuse (23.9%) also having significant effects. A smaller but still significant impact is made by spatial novelty (16.9%). Material coherence (28.3%), spatial harmony (21.2%), and proportionate balance (16.3%), environmental synchronization (34.2%) are the main components of harmony.
The study's findings led to the development of a solid and organized framework for assessing architectural projects helped by artificial intelligence. The contribution of this research is mainly for researchers, architects, and stakeholders to be able to quantitatively assess architectural designs that are produced by AI with a novel AHP based approach evaluation method.
This framework contributes to the ongoing discourse about the incorporation of Artificial intelligence in the field of architectural engineering, more specific the architectural design by prioritizing important design elements and providing a systematic method for upcoming evaluations. A thorough assessment of design quality is made possible by the framework's methodical approach, which highlights the significance of coherence, contextual integration, and sustainability.