IMPLEMENTATION OF AI IN MINING

The project aims to leverage lessons learned and develop a framework for the industry so that organizations can develop a strong business and technical foundation for scalable and successful AI applications.

A strong foundation can:

  • Improve the reader’s understanding of AI, remove barriers to entry, and increase confidence and trust in the technologies
  • Create an understanding of some of the tools and successful use cases for AI and machine learning in mining
  • Help the reader understand and overcome the challenges and barriers to entry
  • Help readers anticipate and mitigate bias.

This project is led by the Artificial Intelligence Working Group.

KEY TOPICS

  • Business case: defining a decision-making process, the implications of AI and more
  • Setting the approach, business model and structure, project management, KPIs, and more
  • Change management and human factors: Defining the journey and resources needed, key stakeholders’ involvement, adoption cycle for workforce, training plan and more
  • Ethics: Understanding the risk of bias and the potential implications of AI
  • Data considerations: data models, data reconciliation, leveraging data analytics methodologies, intellectual property and more
  • Business operations: risk management, safeguards considerations and decision-making
  • Defining acceptance criteria, testing frameworks, infrastructure, cybersecurity, scalability and more
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