Description
The objective of this workshop is to critically examine ethical and responsible use of artificial intelligence in civil and construction engineering, as AI technologies are increasingly embedded in design, construction, inspection, and infrastructure management processes. The workshop will provide a multidisciplinary forum to discuss ethical risks, societal impacts, and governance challenges associated with AI-driven decision-making in the built environment. Key themes include transparency and explainability of AI models, bias and fairness in data and algorithms, accountability and liability in automated systems, data governance and privacy, and human-AI collaboration in engineering practice. The scope spans both research and practice, covering methods, case sudies, standards, and policy perspectives relevant to the AEC industry. Expected outcomes include a shared understanding of ethical challenges and best practices, identification of research gaps and practical needs, and the development of actionable recommendations to support responsible AI adoption in civil and construction engineering.

Description
Artificial Intelligence (AI) is rapidly transforming civil engineering practice, enabling new capabilities in design, construction, operation, and infrastructure management. At the same time, AI adoption introduces significant risks related to data quality, bias, transparency, accountability, safety, and workforce impacts. This workshop aims to provide a balanced and critical examination of both the opportunities and challenges associated with AI deployment across the civil engineering lifecycle. Through expert presentations and interactive panel discussion, participants will explore how AI can enhance productivity, sustainability, and resilience while also considering ethical, technical, and organizational risks. The session will emphasize sector-specific considerations unique to civil engineering, including long project lifecycles, multi-stakeholder environments, and safety-critical decision-making. The workshop will conclude with practical insights and recommendations for responsible and effective AI adoption in research, education, and practice.

Description
This workshop introduces participants to advanced methods for analyzing construction operations using discrete-event simulation (DES) which, when integrated with BIM, GIS, and field sensor data, can be used to model, measure, and optimize complex workflows in real projects. The session will also examine the role of DES in emerging applications such as integrated product–process modeling, digital twins for operations monitoring, and reinforcement-learning-based approaches to planning and resource optimization. Attendees will be guided through a hands-on tutorial using a construction-focused operations simulation platform to visualize processes, diagnose bottlenecks, and make data-driven decisions about mobilizing resources on site. Each participant will receive a two-week implementation package suitable for professional training or inclusion in an advanced university course. This package includes lecture slides, video tutorials, solved examples, and practical exercises, providing ready-to-use materials that support innovation, collaboration, and continuous improvement across the construction lifecycle.