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More than Just Robots: How AI is Revolutionizing the Mining Industry

Prospector explores the risks, rewards, and future of AI in mining - from optimizing operations to programming robots, AI will transform the industry!

Artificial Intelligence (AI) is taking the world by storm, and becoming increasingly prevalent across almost all industries, including mining. In Prospector's July Monthly Mining Roundup, our team dug deep into the power of AI, discussing risks and opportunities with the current trends, and gave a sneak peek into what the future of Mining AI may look like! 

Risk and Opportunities for Artificial Intelligence

In the last year alone, Artificial Intelligence has made leaps and advances throughout the globe that many have never seen before. Programs like ChatGPT have put the power of AI into everyone's hands, and acted as an introduction to what the future may have in store for us. However, as with everything and every new technology, we are seeing a wide variety of risks and opportunities being presented. 



      • AI allows for faster data-driven decision making
      • It can structure unstructured data, making it easier to understand
      • Seemingly unlimited potential uses as the training models grow


      • There are a lot of "hidden" costs of AI, such as electricity generation from non-renewable resources
      • "Garbage in = Garbage out" - making sure the data is accurate and reliable is important to training AI models
      • Potential for harm - just as people can use AI for good, it can also be used for potentially harmful purposes

Current Use Cases

When Prospector was first started, the main use case for AI was document classification and information extraction from publicly disclosed documents and filings for mining companies. When these documents come from the stock exchanges, it isn't always obvious what a documents purpose is, and they vary by stock exchange. 

For example, technical reports on Canadian stock exchanges are known as NI 43-101s, while in Australia similar documents are called JORC reports. Both of these documents are different and have different regulations, but are similar in their purpose. Training the AI model to recognize these documents and sort them apart from the drill results, press releases, and quarterly updates allows analysts to save time! 


A Look into the Future

We know how useful AI can be for things like text and data sorting, but what do future opportunities for it look like? How can the mining industry be optimized and improved through its use? 

The most obvious application for AI is in programming things like robots. Jon explains how researchers are already looking into this, using language models to help robots make decisions and implement tasks. Tetyana explains how these types of robots could assist with opportunities such as mining in space, or other places that we wouldn't want to send humans. 

But, there's more! We are already seeing companies embrace opportunities for using AI in jobs like core logging and geology. With this knowledge and in-depth data, we could see a future potential to input these geological models into another AI, and having it output optimized mine design and reduce environmental impact. In fact, we could have it run several different scenarios to best fit community and mining needs, and help create a better coexistence between mines and their communities. 


So - What Now?

As always, it is important to remember that AI is a tool, much like a calculator or Google. As noted earlier, data quality is imperative for AI, and it's important to fact check and make your own decisions. 

The mining industry has only begun to scratch the surface of AI's potential. With the rapid advances in natural language processing, computer vision, robotics and other AI disciplines, we will likely see it transform operations within the next decade. However, thoughtfully managing the risks will be key as this technology scales.

Be sure to follow us on LinkedIn to tune into our next Monthly Mining Roundup!

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