Description
Course Description:
This 4-hour LU/HSW course examines the integration of Generative Artificial Intelligence (AI) through the lens of an architect’s sole duty: the protection of the health, safety, and welfare of the public. As AI tools increasingly and more precisely automate Architecture, Engineering, and Construction (AEC) tasks, the licensed design professional must maintain “Responsible Control” to ensure these technological tools do not compromise the “standard of care” and go unchecked. Participants will move beyond basic AI concepts to explore practical applications that directly impact occupant safety and building performance.
The course provides technical instruction on using Large Language Models (LLMs) to verify complex occupant load factors and single-exit exceptions, and utilizing Test-to-Image (TTI) tools to visualize environmental hazards and Crime Prevention Through Environmental Design of CPTED-based security strategies. A portion of the course is dedicated to the ethical and legal frameworks established by governing bodies like NCARB and the AIA and other AEC-related governing bodies.
Through a “Human-in-the-Loop” (HITL) methodology, participants will learn to mitigate the risks of AI hallucinations in code-compliance reports and identify data biases that could lead to poor design or possible engineering issues. By the conclusion of the course, AEC design professionals will be equipped to implement AI policies and ensure AI-assisted deliverables prioritize the physical and social well-being of the building’s occupants.
Learning Objectives:
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Ability to differentiate between Traditional and Generative AI to appropriately use AI tools within architectural workflows, specifically leveraging Generative AI to optimize structural systems for enhanced occupant safety and to conceptualize site designs that elevate human welfare and environmental resilience
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Understand and Apply advanced Generative AI prompting strategies (such as Chain of Thought and Step-Back prompting) to analyze complex project constraints and building codes, and utilize Text-to-Image and Large Language Models to visualize and develop wellness-focused environments that support occupant health and separate public and private zones safely.
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Evaluate and Implement Generative AI tools (TTI, LLM, and Latent Space Modeling) to automate critical life-safety tasks, including occupant load calculations for code compliance as it relates to egress capacity, CPTED-based security strategies, and the visualization of environmental risks to ensure health and safety of the built environment.
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Understand and Apply the principles of “Responsible Control” and “Human-in-the-Loop” protocols to mitigate professional liability risks–including AI hallucinations and data bias–ensuring that AI-assisted technical submissions or deliverables meet the “standard of care” required to protect the public’s health, safety, and welfare.
Instructor: Mitchell Ramseur, AIA, NOMA
Mitchell Ramseur, AIA, NOMA is the Owner, Principal Architect and Architect-Developer of M Ramseur & Associates (MRA), a North Carolina based architectural practice specializing in commercial design and Higher education design, land development, and third-party code compliance reviews in the United States. He is professionally licensed in good standing in North Carolina, Alabama, and Georgia.
AIA Course Number: AIAPDH276
Learning Units: 4 LU/HSW hours
