AI in Mining: Game-Changer, or Techno-optimism?

How AI and related technologies are forging innovations in mining, and assessing the pros and possible cons of this.

Could artificial intelligence (AI) really have discovered what may be the world’s largest as-yet undeveloped copper deposit, estimated at 247 million tonnes with a grade of 3.64%?

Chances are that it has: KoBold Metals, a company at the forefront of exploration technologies, has created a Google Maps of the earth’s crust using AI. It has recently announced that it will commission a new copper and cobalt mine in Mingomba, Zambia, in the next decade.

California-based KoBold is backed by Bill Gates and Jeff Bezos, the respective founders of Microsoft and Amazon, so it’s unsurprising that it gears its operations with Internet-of-Things (IoT) technologies and AI.

What is AI, actually?

To grasp the wider potential application of AI in mining we need to look beyond exploration, and understand the nature of AI.

According to IBM, decades-long leaders in the field, “artificial intelligence?leverages computers and machines to mimic the problem-solving and decision-making capabilities of the human mind.” The algorithms adapt to situations and learn from the problems they are coded to solve. The more they do this, the faster their ‘intelligence’ grows.

Translating this more specifically into mining, this means that AI, interlocked within IoT, forges innovation not only in exploration, but also in productivity, safety, maintenance, and environmental impact.

Productivity drivers

It’s relatively straightforward to see how mining operations’ productivity is already being improved by AI, and how this will extend in the near future.

Among other examples, 73 self-drive haulers came into service seven years ago at four of Rio Tinto’s Australian mines. The autonomous-drive vehicles can operate 24/7 (with notable safety in the controlled environment of a mine). The company reported a 15% reduction in hauling costs compared to human-operated conditions.

Self-operation is happening in other forms of mining vehicles and equipment such as drill-hole systems and long-haul trains. TOMRA’s mining solutions division creates sorting systems which it claims reduce by 12% the mass that needs to be moved.

TOMRA has modelled its IoT technologies into a prototype underground mine of the future which, besides enhanced productivity, includes energy consumption savings, lower carbon emissions, extending the longevity of the mine, and reducing the required resources to rehabilitate the area at the end of the mine’s life.

Out-of-this-world?

Then there are swarm robotics, pioneered by Luxembourg-domiciled company OffWorld Mining, whose ultimate vision is mining in space. These autonomous mechatronics – aptly named ‘Surveyor’ – work collaboratively, sense their environment, interpret data patterns, and adapt. Unlike human geologists, they navigate any terrain, under any conditions. The modular units are planned to be fitted with laser technologies to extract with far more precision, and with significantly less waste and carbon emissions, than in the blasting and drilling process. Combined, these will almost certainly accelerate the profitability of tier 2 or 3 mines.

Swarm robotics are included within Anglo American’s ‘FutureSmart Mining’ vision. Interestingly, the manifesto points out that they may, potentially, break the paradigm of scale, noting that “innovation in mining has traditionally meant scaling up – bigger trucks, bigger shovels – to increase capacity.?With robotics, the smaller the better: lightweight and modular, robots can perform multiple tasks, with precision, in any terrain.”

Better decisions, improved outcomes

Automation and smart IoT technologies, as impressive as they may be, are not the same as AI. A less dramatic but clearer example of AI in mining is its application in fleet and equipment maintenance. Over the past two decades, planned maintenance has become the standard norm in the functioning of almost any mine operation.

Now, the shift is to predictive maintenance. With its capability to process and analyse vast data gatherings from any number of sensors and devices, AI can detect deviations from established patterns and flag precisely where a problem may occur. The timing prompt may be very different to the planned maintenance schedule – but downtime based on the neutral interpretation by algorithms could be far less costly than the mining operation having to shut down unexpectedly due to unforeseen equipment failure. Beyond productivity, there is also a safety benefit: prevention is always better than reaction, and the predictive attributes of AI-driven, systemised protocols remove human biases in safety-related evaluations.

Besides improving mine safety, advanced technologies are also starting to be used to monitor environmental conditions in mining regions. AI can analyse data to predict health and safety hazards such as dust, to prompt more proactive management of tailings dams, and steer better real-time operational decision-making affecting the mine’s environmental impact. These ultimately benefit societies, especially communities in close proximity to mines.

Employment concerns

Taking the long view on the history of industrialisation, for two centuries technology advancements have shifted what people do. In some instances this has represented a clear gain – faster, safer, and better output quality. In other cases technology has slashed jobs or eroded employment opportunities. Today, The World Economic Forum (WEF) estimates that 23% of all current jobs will change by 2027, and there will be a net loss of 14 million jobs – both statistics being attributable to surging

developments in AI. 1

Digitisation is extrapolating, and countries in Africa should urgently be aligning their education and skills agendas to the jobs landscape of the future. For the mining industry in particular, the real point is that rote work will increasingly be automated – performed by robots or co-bots (industrial robots operated by humans in shared workspaces) – and analytical work will be conducted by people enabled by AI. Miners need to recruit new employees, and upskill existing ones, in technology fields, including future needs skills around automation, AI and analytics. “Just as mining workers at large companies no longer work with picks and shovels, the workers of the future will not be driving trucks and loaders. Rather, their skills will be in robotics, automation and data analytics,” say PwC in their latest industry report. 2

Mining companies eager to embrace AI should consider whether Zambia’s liberalising regulatory environment will last for very long if mining jobs fall as profits rise, if mines run on smooth technologies while local communities remain poverty-stricken. Miners investing in AI should simultaneously invest in job creation so that the future of the operation is safeguarded.

A holistic perspective

If the implications of AI should be understood with reference to the past, they should also be projected with balance. Perhaps these predictions involving AI are another manifestation of techno-optimism? Techno-optimism is defined as the firm belief that technology will improve the world (or a particular field) irrespective of the balance of forces between nations, or between industry, society and governments. Further, techno-optimism holds the view that just because an industry has caused or contributed to a problem does not disqualify it from generating innovative technologies to help address the issue.

Exploration and innovation, savings and productivity, safety and environmental outcomes: it’s clear that AI is already transforming mining, and has the potential to significantly improve the prospects and profitability of mining companies. But the jury is out on whether this will improve the industry’s social contribution – the lives

1 The Future of Jobs Report 2023, World Economic Forum, May 2023. The report is representative of 26 industry clusters across 46 countries.

2 Mine 2023: 20 th edition, The era of reinvention, PwC, June 2023. See Chapter VI.

of mining workers and the communities in mining regions. These are people-centred issues that require human input.

So, it remains unclear how, overall, AI will impact longstanding issues in the age-old industry of mining. For the moment, AI is both a potential game-changer and confirmation of the hype that surrounds technology. The answer to the question – game-changer or techno-optimism? – depends on the intentions behind its design and implementation.

Intention: this lies in the minds of people, in this case the leaders of mining enterprises. They would do well to realise that mining’s future will include AI, but also to understand that AI is not the be-all and end-all future of mining.

As one of the leading mining contractors in Zambia, JVChantete can assist infutureproofing your operations. Contact us today at [email protected].