On February 7, Dentons' Montreal office hosted the local chapter of Women in Mining Canada for a lunchtime event on artificial intelligence and mining. A lively panel discussion took place before more than 60 people among the following panelists:
- Sarane Sterckx, Project Manager, Goldspot Discoveries Inc.
- Guy Desharnais, Director of Mineral Resource Evaluation, Osisko Gold Royalties Ltd.
- Maiko Sell, Earth Data Scientist, Rio Tinto
- Caitrin Armstrong, Machine Learning Engineer at Aifred Health and MSc candidate in Computer Science in the Network Dynamics Lab at McGill University
- Adam Allouba, Partner, Dentons
Dentons partner Mira Gauvin moderated the panel, and the event was chaired by WIM Montréal president Kimberly Darlington of Refined Substance. SNC-Lavalin provided an interactive demonstration of equipment from its Innovation Centre in Toronto at the start of the luncheon.
With each panelist contributing insights from his or her own area of expertise, several themes emerged from the discussion. First, AI has serious potential to revolutionize numerous aspects of the mining industry. From analyzing geological survey results to directing autonomous vehicles to monitoring environmental or health & safety conditions, AI can be a useful tool in any application that blends data analysis with predictive capacity. As a data-driven industry, mining is a natural fit for AI. What's more, many of the legal concerns that typically arise with AI, such as privacy and ethical questions, are typically not at issue in the natural resources sector since the data is purely scientific and technical in nature.
Second, as useful as it promises to be, AI is no magic bullet. Implementing AI requires the creation of multidisciplinary teams – including geologists, data scientists and, yes, even legal counsel! – to ensure that the project addresses the business' real needs. The AI tools will need to be tested and retested before being deployed, and employees will need to be trained to use them properly. It also requires buy-in from senior management, who will often want to see proof of its value before making the required investments – and as the technology is so new and changing so rapidly, that proof is not always easy to provide.
Third, it's essential not to neglect the legal aspects of implementing AI. Who is liable if something goes wrong: the software provider, the mining company, a third-party consultant or someone else in the supply chain? When drafting their contracts, the parties need to ensure to include the language necessary to protect them, including clear descriptions of the software being provided and its limitations, representations and warranties regarding the training data and the performance of the finished product, and indemnification provisions. What about intellectual property considerations, such as whether the company has the necessary rights to the training data or who will own any new IP that may be created by the AI software itself?
What's for certain is business applications of AI are still in their infancy. As new use cases emerge, practical applications tested and best practices crafted, the technical, legal and other considerations that AI entails will evolve in ways that we in 2019 can't yet envision. Only by closely monitoring developments in both the mining and technology sectors can an observer hope to keep up with the rapid pace of development that undoubtedly will only accelerate in the future.
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