Responsible AI in structural engineering: a framework for ethical use
The integration of Artificial Intelligence (AI) into structural engineering holds great promise for advancing analysis, design, and maintenance. However, it also raises critical ethical and governance challenges—including bias, lack of transparency, accountability gaps, and equity concerns—which are...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2025-07-01
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| Series: | Frontiers in Built Environment |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fbuil.2025.1612575/full |
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| author | Vagelis Plevris Haidar Hosamo |
| author_facet | Vagelis Plevris Haidar Hosamo |
| author_sort | Vagelis Plevris |
| collection | DOAJ |
| description | The integration of Artificial Intelligence (AI) into structural engineering holds great promise for advancing analysis, design, and maintenance. However, it also raises critical ethical and governance challenges—including bias, lack of transparency, accountability gaps, and equity concerns—which are particularly significant in a discipline where public safety is paramount. This study addresses these issues through eight fictional but realistic case studies that illustrate plausible ethical dilemmas, such as algorithmic bias in predictive models and tensions between AI-generated recommendations and human engineering judgment. In response, the study proposes a structured framework for responsible AI implementation, organized into three key domains: (i) Technical Foundations (focusing on bias mitigation, robust validation, and explainability); (ii) Operational and Governance Considerations (emphasizing industry standards and human-in-the-loop oversight); and (iii) Professional and Societal Responsibilities (advocating for equity, accessibility, and ethical awareness among engineers). The framework offers actionable guidance for engineers, policymakers, and researchers seeking to align AI adoption with ethical principles and regulatory standards. Beyond offering practical tools, the study explores broader theoretical and institutional implications of AI, including risks associated with model drift, the need for lifecycle oversight, and the importance of cultural and geographic adaptability. It also outlines future challenges and opportunities, such as incorporating AI ethics into engineering education and considering the ethical impact of emerging technologies like quantum computing and digital twins. Rather than offering prescriptive answers, the study aims to initiate an essential dialogue on the evolving role of AI in structural engineering, equipping stakeholders to manage its benefits and risks while upholding trust, fairness, and public safety. |
| format | Article |
| id | doaj-art-544b7f265f5e4e4faafad1f795e0a756 |
| institution | Kabale University |
| issn | 2297-3362 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Built Environment |
| spelling | doaj-art-544b7f265f5e4e4faafad1f795e0a7562025-08-20T03:28:26ZengFrontiers Media S.A.Frontiers in Built Environment2297-33622025-07-011110.3389/fbuil.2025.16125751612575Responsible AI in structural engineering: a framework for ethical useVagelis Plevris0Haidar Hosamo1Department of Civil and Environmental Engineering, College of Engineering, Qatar University, Doha, QatarDepartment of Built Environment, Oslo Metropolitan University, Oslo, NorwayThe integration of Artificial Intelligence (AI) into structural engineering holds great promise for advancing analysis, design, and maintenance. However, it also raises critical ethical and governance challenges—including bias, lack of transparency, accountability gaps, and equity concerns—which are particularly significant in a discipline where public safety is paramount. This study addresses these issues through eight fictional but realistic case studies that illustrate plausible ethical dilemmas, such as algorithmic bias in predictive models and tensions between AI-generated recommendations and human engineering judgment. In response, the study proposes a structured framework for responsible AI implementation, organized into three key domains: (i) Technical Foundations (focusing on bias mitigation, robust validation, and explainability); (ii) Operational and Governance Considerations (emphasizing industry standards and human-in-the-loop oversight); and (iii) Professional and Societal Responsibilities (advocating for equity, accessibility, and ethical awareness among engineers). The framework offers actionable guidance for engineers, policymakers, and researchers seeking to align AI adoption with ethical principles and regulatory standards. Beyond offering practical tools, the study explores broader theoretical and institutional implications of AI, including risks associated with model drift, the need for lifecycle oversight, and the importance of cultural and geographic adaptability. It also outlines future challenges and opportunities, such as incorporating AI ethics into engineering education and considering the ethical impact of emerging technologies like quantum computing and digital twins. Rather than offering prescriptive answers, the study aims to initiate an essential dialogue on the evolving role of AI in structural engineering, equipping stakeholders to manage its benefits and risks while upholding trust, fairness, and public safety.https://www.frontiersin.org/articles/10.3389/fbuil.2025.1612575/fullresponsible AIAI governanceAI ethicsaccountabilitytransparency and explainabilityAI risk management |
| spellingShingle | Vagelis Plevris Haidar Hosamo Responsible AI in structural engineering: a framework for ethical use Frontiers in Built Environment responsible AI AI governance AI ethics accountability transparency and explainability AI risk management |
| title | Responsible AI in structural engineering: a framework for ethical use |
| title_full | Responsible AI in structural engineering: a framework for ethical use |
| title_fullStr | Responsible AI in structural engineering: a framework for ethical use |
| title_full_unstemmed | Responsible AI in structural engineering: a framework for ethical use |
| title_short | Responsible AI in structural engineering: a framework for ethical use |
| title_sort | responsible ai in structural engineering a framework for ethical use |
| topic | responsible AI AI governance AI ethics accountability transparency and explainability AI risk management |
| url | https://www.frontiersin.org/articles/10.3389/fbuil.2025.1612575/full |
| work_keys_str_mv | AT vagelisplevris responsibleaiinstructuralengineeringaframeworkforethicaluse AT haidarhosamo responsibleaiinstructuralengineeringaframeworkforethicaluse |