Dr. Ellen M. Rathje

Dr. Krishna Kumar 

How AI is Changing Geotechnical Engineering

The excitement about AI and machine learning (ML) is all around us, but how does it impact geotechnical engineering?

<p>The excitement about AI and machine learning (ML) is all around us, and we are just starting to explore how AI/ML can directly impact our work as geotechnical engineers. The use of AI/ML in geotechnical engineering generally has focused on: (1) Large Language Models (LLM), such as ChatGPT, to assist with technical documentation, interpret geotechnical reports, automate routine calculations, and accelerate desk studies and (2) ML techniques to develop regression or classification models that better predict the response of geotechnical systems. These applications have shown great promise, but the pitfalls of AI/ML models remain (e.g., LLM hallucinations, poor extrapolation, violating physics, etc.). This presentation will introduce some examples of AI/ML modeling approaches and their specific application to geotechnical engineering. These applications include LLM-assisted design code interpretation and compliance checking, automated generation of geotechnical reports from field and laboratory data, and ML prediction models for earthquake-induced lateral spreading and seismic slope displacements. We will highlight key issues to consider when evaluating AI/ML models, such as the critical need to verify LLM outputs against established engineering principles, potential liability concerns with AI-generated content, and the importance of maintaining engineering judgment. Additionally, we will discuss the balance between ML model explainability and model performance, and how to address the “black box” nature of ML models by utilizing “glass box” approaches.</p>

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How AI is Changing Geotechnical Engineering

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