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Demystifying AI in the Water Industry

Participants and organizers of the TriCon AI Workshop: (L-R) Travis Wagner (Trinnex), Alana Gildner (BV), Yudu (Sonia) Wu (WSP), Madeleine Driscoll (Hazen and Sawyer), Craig Daley (City of Baltimore), John Smith (Haley Ward), Brian Ball (VA Engineering), David Gisborn (DC Water), and Davar Ardalan (TulipAI). Brandon O’Daniel of Xylem, one of the speakers, was not present in the photo

Water industry professionals explored the intersection of artificial intelligence (AI) and machine learning (ML) during a pre-conference workshop in Ocean City, Maryland yesterday, discovering that while AI’s roots go back to 1948, today’s Generative AI has the potential to completely upend their industry.

Designed to make AI technologies accessible and relevant, the sessions emphasized the critical role of data and the importance of data governance, sparking excitement and curiosity among participants — all leading up to the Chesapeake Tri-Association Conference (TriCon), the water industry’s premier event.

Craig Daly, Chief of Water Facilities Division, City of Baltimore DPW on the fundamentals of AI and ML

Professionals from the City of Rockville, WSSC, City of Baltimore, DC Water, and regional engineering companies gathered to explore how AI can be effectively applied to their field. Presented by the CWEA and CSAWWA Asset Management Committee, the session featured Craig Daly from the City of Baltimore, Travis Wagner of Trinnex, Brandon O’Daniel of Xylem, John Smith of Haley Ward and Davar Ardalan of TulipAI.

The workshop focused on practical, actionable steps, showing participants how these tools can enhance accuracy, save time, and optimize their water systems. Breakout sessions also introduced participants to the real-world applications of generative AI tools.

Travis Wagner, Vice-President at Trinnex presented on Economics of AI in Treatment Processes

John Smith of Haley Ward and Davar Ardalan of TulipAI led a special segment titled “Responsible AI Adventures: Innovating Environmental Engineering,” which highlighted the importance of ethical considerations when using AI in the water industry.

Smith and Ardalan introduced the beta version of John Smith GPT, an AI assistant designed to support John and his team of environmental engineers in tasks like proposal writing, cost estimating, and marketing strategies. They emphasized two critical points: first, never share proprietary information with an open AI tool; and second, always be transparent when using AI, just as you would with a bibliography or by naming your sources. This transparency is essential for maintaining trust and integrity in how AI is integrated into professional practices.

Try the beta version of John Smith GPT here. The custom AI:

Leverages decades of civil engineering knowledge from veteran civil engineer John Oliver Smith.

Provides information on materials relevant to grant projects, enhancing proposal detail.

Supplies data on eco-friendly materials and methods, supporting sustainability objectives.

John Smith also underscored the importance of not sharing confidential information with AI systems. He likened AI to a powerful tool that, like any other, needs to be used responsibly. Moreover, he encouraged attendees to pilot AI tools with their teams before full-scale implementation, allowing for collaborative input and refinement of the technology to suit specific needs. Their message was clear: AI can transform the industry, but it must be used thoughtfully and with full awareness of its ethical implications.

As AI tools continue to develop, sessions like this at TriCon are essential for staying informed and prepared. They equip water professionals with the tools and understanding they need to harness new technologies effectively and responsibly.

This content was crafted with the assistance of artificial intelligence, which contributed to structuring the narrative, ensuring grammatical accuracy, summarizing key points, and enhancing the readability and coherence of the material.

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Demystifying AI in the Water Industry was originally published in Becoming Human: Artificial Intelligence Magazine on Medium, where people are continuing the conversation by highlighting and responding to this story.

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