Session A: April 15, 2024, 12:00 noon to 1:30 p.m. ET
Rocks & Robots: The AI Revolution in Geoscience

Session Chair: Hannah Chessell, P.Geo.
A moderated Q & A will follow the panel presentations.

Presentation 1: Use of Artificial Intelligence (AI) in Professional Practice

Speaker: David Slade, P.Eng., Practice Advisor, Professional Practice Standards & Development, Engineers and Geoscientists British Columbia - SEE SPEAKER'S BIO

SUMMARY

Artificial intelligence (AI) is a pervasive technology with widespread adoption expected across all areas and industries of practice within Professional Geoscience and Engineering in the coming years. As this technology is increasingly built into the best systems and tools for the job, professionals will have an important decision to make:

1. Avoid the technology entirely and risk being left behind as the industry advances.
2. Adapt to a rapidly evolving technological landscape. Learn about the risks and benefits of AI tools as well as how to implement their use while maintaining good professional practice.

During this presentation, we will discuss a high-level overview of EGBC’s latest practice advisory covering the use of AI in Professional Practice including the following topics:

• - A background and overview of AI, defining what the technology is and the different types of AI professionals may encounter
• - Risk factors, risk assessment and risk management
• - Quality management including:

• - Disclosure on the use of AI in professional practice
• - Environmental and equity considerations

Presentation 2: Data Does Not Lie… or Does It? The Hidden Pitfalls of Machine Learning/AI Workflows in Mineral Exploration

Speaker: Shishi Chen, Principal – Data Science, Exploration Excellence and Innovation, BHP - SEE SPEAKER'S BIO

Machine learning/AI holds great promises for mineral exploration, but without proper checks, it can just as easily lead us astray. Flawed data, spatial biases, and imbalanced training data can turn sophisticated algorithms into little more than digital divining rods—producing predictions that look precise but lack real-world reliability. This presentation unpacks the critical mistakes that can render machine learning models useless or even dangerously misleading. We’ll explore why data quality is king, how spatial correlation can deceive, and why ignoring model risks leads to costly exploration dead ends. In the high-stakes world of mineral exploration, trusting an unchecked model is like chasing fool’s gold—unless we refine our approach.

Presentation 3: Using Artificial Intelligence and Machine Learning in Canada’s Water Sector

Speaker: Chris Gerrits, M.Sc., P.Eng., Director, Land Development, CROZIER - SEE SPEAKER'S BIO

The global water sector is a data intensive industry, with many water and wastewater plants collecting and storing massive amounts of data from SCADA systems for decades. The discussion will focus on real world applications of artificial intelligence and machine learning in the water sector using readily available existing data. Chris will also cover uses for AI/ML in data analysis and imputation as well as using AI for object and image detection.

Register online for this session or the full Symposium.