Conference Agenda
Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).
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Daily Overview |
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SES 3-2-1: Artificial Intelligence machine learning 1 Location: HSB0 Session Chair: Eran Friedler Session Chair: Namrata Karki | |
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10:30am - 10:45am
The AI-enabled Researcher: Contemporary Tools for Urban Drainage Research 1: University of Exeter, Exeter, United Kingdom; 2: East Sussex County Council, Lewes, United Kingdom This study compares traditional research workflows with AI-enhanced methodologies in water engineering, focusing on how Large Language Models (LLMs) can expedite literature reviews, idea generation, and manuscript drafting. Building on historical examples like calculator adoption, we illustrate both the efficiency gains and potential drawbacks—including biased outputs, “hallucinated” references, ethical concerns, and environmental impacts. Despite these risks, LLMs offer significant promise in automating repetitive tasks and providing creative insights. By maintaining active human oversight and transparent practices, researchers can harness AI’s capabilities to enhance, rather than undermine, the integrity and depth of academic work. | |