384
A. Lugonzo and K. Chege
12.5 Artificial Intelligence and the Future
of Extractives
AI, machine learning, the use of robots in mining, etc., are changing
the extractives industry landscape around the world.
44 AI especially has
seen more uptake by entities in the extractives sectors, as compared to
other forms of technology, and this is the reason for its emphasis in this
chapter.
The most critical components in the extractives are efficiency, effectiveness and environmental and human safety concerns. Extraction and
production of resources from the ground involves different processes, to
the point that the products reach the final consumer in the downstream
stage of the cycle. Minute improvements in the execution speed, the efficiency of operations, safety and reduced turnaround times, separate a
profitable venture from an unsuccessful one in the extractives.
AI has widely been adopted by mining companies in recent times to
improve the efficiency of operations in mines as well as to reduce costs,
in a capital-intensive industry by its very nature. Mining companies are
only beginning to appreciate the potential of AI in mining, and it is
expected that AI will become more commonplace, as we move towards
fully adopting the 4IR into many of our economic activities in various
sectors of our economies.
AI is instrumental in the making of decisions, by analysing algorithms, especially when discovering deposits in the prospecting phase of
the mining cycle. AI automates decisions that were previously made by
human beings, which were influenced by inherent biases and were prone
to costly mistakes. Additionally, AI assists in extracting minerals from
hard-to-reach areas, and in harsh weather conditions. Therefore, minerals
are extracted from previously inaccessible areas, without endangering the
lives of workers and with little to no human error.
Many companies are beginning to adopt technology in their operations. For example, Canada’s GoldSpot Discoveries Corporation utilizes
AI and other new technologies like machine learning, to improve mineral
44 Gerlind Wisskirchen and others, ‘Artificial Intelligence and Robotics and Their Impact on the
Workplace’ (IBA Global Employment Institute 2017).
A. Lugonzo and K. Chege
12.5 Artificial Intelligence and the Future
of Extractives
AI, machine learning, the use of robots in mining, etc., are changing
the extractives industry landscape around the world.
44 AI especially has
seen more uptake by entities in the extractives sectors, as compared to
other forms of technology, and this is the reason for its emphasis in this
chapter.
The most critical components in the extractives are efficiency, effectiveness and environmental and human safety concerns. Extraction and
production of resources from the ground involves different processes, to
the point that the products reach the final consumer in the downstream
stage of the cycle. Minute improvements in the execution speed, the efficiency of operations, safety and reduced turnaround times, separate a
profitable venture from an unsuccessful one in the extractives.
AI has widely been adopted by mining companies in recent times to
improve the efficiency of operations in mines as well as to reduce costs,
in a capital-intensive industry by its very nature. Mining companies are
only beginning to appreciate the potential of AI in mining, and it is
expected that AI will become more commonplace, as we move towards
fully adopting the 4IR into many of our economic activities in various
sectors of our economies.
AI is instrumental in the making of decisions, by analysing algorithms, especially when discovering deposits in the prospecting phase of
the mining cycle. AI automates decisions that were previously made by
human beings, which were influenced by inherent biases and were prone
to costly mistakes. Additionally, AI assists in extracting minerals from
hard-to-reach areas, and in harsh weather conditions. Therefore, minerals
are extracted from previously inaccessible areas, without endangering the
lives of workers and with little to no human error.
Many companies are beginning to adopt technology in their operations. For example, Canada’s GoldSpot Discoveries Corporation utilizes
AI and other new technologies like machine learning, to improve mineral
44 Gerlind Wisskirchen and others, ‘Artificial Intelligence and Robotics and Their Impact on the
Workplace’ (IBA Global Employment Institute 2017).