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AI In Mining

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Artificial Intelligence Bulletin

Recent developments in Artificial Intelligence (AI) are changing the way mining companies do business. Traditionally AI has been the domain of tech giants, but the wide ranging application of its techniques has the potential to disrupt almost every industry. Mining companies must begin to prepare for these seismic changes as these new techniques unlock new potential.

AI Basics

Despite recent gain in popularity, AI has been around in one form or another for quite some time. Up until recently, the amount of computing power required to deploy AI tools put them out of reach for all but the largest of technology companies. However, cheap cloud computing has caused a rush of investment and has unlocked the use of AI techniques in more industries.

At its core, AI is an advanced data analysis technique, and as such, it seeks to understand complex relationships and make predictions. AI is not, however, a panacea to all corporate woes. AI is a sophisticated tool and is best used for increasing the efficiency of an operation rather than reinventing it.

Mining and AI

In the mining industry specifically, it is estimated that AI could reduce extraction cost by 10%, yet only 30% of mining and energy companies effectively utilize the captured data. This is often due to disparate and siloed systems which inhibit a holistic analysis of a company's operations. Moreover, companies are frequently unaware of the amount and types of data they are collecting across all these systems.

Before beginning an AI project it is important for companies to understand what data they have and where it came from. Data can sometimes carry privacy and copyright concerns and it is important to deal with these important legal issues early on in the process as it is often more difficult to separate data after it has been combined. Part of this process will also include examining the data for any potential biases because sensitive AI algorithms can confuse a bias for a genuine signal. Companies often seek to engage a data scientist or analytics company for assistance when dealing with these potential concerns.

When engaging external data consultants, companies should keep in mind the unique security and legal issues that surround data. This can include both ownership issues in the data itself and of the software or algorithms which are based on it. When outsourcing the production and design of AI tools, it is important that both parties have a clear understanding of what the end product will do and have mechanisms in place to ensure performance.

As mining companies increasingly develop and adopt AI technologies, proprietary AI tools will become part of a company's competitive advantage. Whether it is improved exploration target selection, autonomous vehicles, or increased operational efficiencies, companies should consider legal protections to preserve their advantage and increase their return on investment.

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