Abstract
As artificial intelligence rapidly advance, their growing complexity enables more sophisticated applications across sectors, including construction. However, the opaque nature of algorithms, such as generative AI, reduces human interpretability and trust. While providing benefits like enhanced efficiency, generative design’s black-box processes hamper adoption. Explainable AI can elucidate how AI algorithms generate outputs, thereby improving understanding and confidence. Despite explainable AI’s potential, construction has given it limited focus. This research systematically reviews the application of explainable AI in generative design in construction, with an aim to allay risks and enable wider utilization of these emerging technologies for improved engineering design.
Original language | English |
---|---|
Title of host publication | Proceedings of the 2024 European Conference on Computing in Construction |
Editors | Marijana Srećković, Mohamad Kassem, Ranjith Soman, Athanasios Chassiakos |
Place of Publication | Newcastle |
Publisher | European Council on Computing in Construction (EC3) |
Number of pages | 8 |
ISBN (Electronic) | 9789083451305 |
DOIs | |
Publication status | Published - 14 Jul 2024 |
Event | 2024 European Conference on Computing in Construction - Platanias at the Minoa Palace Resort, Chania, Greece Duration: 14 Jul 2024 → 17 Jul 2024 https://ec-3.org/conference2024/ |
Conference
Conference | 2024 European Conference on Computing in Construction |
---|---|
Abbreviated title | EC3 2024 |
Country/Territory | Greece |
City | Chania |
Period | 14/07/24 → 17/07/24 |
Internet address |
Keywords
- explainable artificial intelligence
- generative design
- trustworthiness
- construction
- Artificial Intelligence