From a distance, everything looks normal at Rio Tinto’s Yandicoogina and Nammuldi mines in Pilbara, Western Australia. Huge trucks trundle along the mines’ reddish-brown terraced sides laden with high-grade iron ore. Back and forth, almost endlessly.
Watch for long enough, however, and you’ll see that no-one ever steps out of the cab. No lunch stops. No toilet breaks. No change of shift. That’s because these house-sized trucks are being remotely operated by ‘drivers’ based 1,200 kilometres away in Perth.
Automation is fast becoming a reality in the world of mining. Rio Tinto is reportedly trialling driverless trains and robotic drilling at its Pilbara sites too. Tele-remote ship loaders, automated rock breakers and semi-autonomous crushers are just some of the high-tech equipment now being rolled out by the sector’s leading edge companies.
The idea of 21st century mines being run from centralised control centres far from the dust of the coalface has several significant selling points. Automation is arguably greener, safer and – after the initial up-front investment – has cheaper running costs.
Mine workers, local suppliers and government tax agencies are justified in being a tad sceptical, however. More robotic technology potentially means fewer low-skilled workers, less local contracting and lower mine-related tax receipts.
“If you’re moving from mines that employ 5,000 to 10,000 people down to 500 or 1,000, then you’re obviously not going to get the same amount of local jobs,” says Howard Mann, senior adviser on international law at International Institute for Sustainable Development (IISD) and co-author of a recent study on the impact of automation in the mining sector.
According to the report’s findings, mine automation is set to hit resource-rich countries in the developing world hardest, with national gross domestic product potentially reducing by as much as 4% in some cases.
It’s not just local jobs that might go. Local procurement in poor countries could dramatically reduce too. Based on data from two multinational mining companies, the report’s authors calculate that large mine operators in low-income countries spend about one fifth (21%) of their procurement locally. For OECD countries, that figure is closer to 91%.
“The ‘shared value’ paradigm was intended to reduce that gap and give developing countries the opportunity to close those ratios. What automation is going to do is just step in the way and block that from happening in a significant way,” says Mann.
The notion of ‘shared value’ lies at the crux of the debate around how best to manage automation’s impacts for mining. Now a staple in the corporate social responsibility lexicon, the term describes the mutual benefits that can ideally accrue from mineral extraction. By generating value for host countries, the argument runs, Big Mining can justify expatriating large chunks of value elsewhere – not least to shareholders in rich countries.
For Mann, automation has come like a “bolt out of the blue” for governments and mining companies alike. With the deployment of automated technologies expected to peek in 10-15 years, now is the time to rethink how the mining pie is currently sliced up.
“The mining sector model is almost a colonial model. The mining companies own the resources, they own the land and they own all the benefits of harvesting the resources,” he says. “‘What share of taxes and royalties should governments get?’ used to be the baseline question. I think we’re going to see a reversal of that in the coming years.”
In other words, in a more automated future, national governments should think about how to restructure the mining sector so as to best compensate for lost jobs and income. In Mann’s view, policymakers need to consider a greater role for state-owned companies, tighter profit-sharing agreements and more service-oriented (rather than ownership) concessions, among other measures.
Aidan Davy, chief operating officer at the International Council for Mining and Metals, is wary about rewriting the rule book just yet. Automation is as likely to result in the redeployment of jobs within the mining sector, as it is the removal of those jobs. Nor will automation be rolled out universally. The speed and spread of uptake will depend heavily on local issues, such as mineral type and availability of necessary skills.
All the same, he concedes that companies could potentially do more to help diversify local economies away from mining – a major recommendation of the IISD report. Helping to open up new markets for people in mining areas by maximising rail, road and other mining-related infrastructure investments would be one way to do so.
Directing state revenues from mining to economic diversification projects is another possible option, Davy suggests: “You can make the case for saying that perhaps it is appropriate that there is a diversion of at least a proportion of that to the broadening of economic opportunity in producing areas on the basis that there is less direct opportunity associated with employment within the mine.”
Yet efforts to promote economic diversification take mining companies out of their comfort zone. It’s not impossible, though. Davy points towards the example of Cerro Verde copper concession in Peru, where US-based mine operator Freeport-McMoRan has helped poultry farmers and artisan weavers build up their businesses. Such as they exist, however, most job creation schemes tend to focus on integrating local businesses into mining companies’ own supply chains.
Another option is to focus on building local capacity. Automated technology is not about to go away. So emerging economies heavily dependent on mining should consider how best to obtain the skills and technical know-how to best exploit it.
So argues Nahom Ghebrihiwet, a PhD candidate at VU University Amsterdam and a specialist in technology and knowledge “spillovers” related to foreign direct investment projects. Large mining companies already invest in universities and other specialist research centres in mature markets such as Australia. With the right incentives, similar initiatives could take root elsewhere too, he argues.
“Other sectors will also benefit from these sorts of skills, so it makes sense for the government to invest in this … and if companies are convinced of the fact that they can establish these centres, then the next step obviously will be that the company themselves will begin to transfer skills to [local people] and train them,” he says.
A case in point is Rio Tinto’s Analytics Excellence Center in Pune, India, which is run jointly with information technology service provider IGATE Patni. The purpose of the research hub is to predict and prevent engine breakdowns and other downtime events by analyzing equipment data from Rio’s worldwide operations.
Peter Knights, head of the mining engineering division at Australia’s Queensland University, goes further, arguing host governments in developing countries could mandate local knowledge transfer. He compares it to similar requirements for US defense companies that have sales contracts with Australia.
“If we’re going to look at developing autonomous mining in developing countries then including offsets to upskill local people is probably a legitimate request,” he says.
It’s not just low-income countries where research and upskilling is required, however. Educators in advanced economies are still puzzling over precisely what skills and management strategies mining professionals will need in a more automated future.
“In many ways, we are still nutting what these new roles will be. In Australia, for example, we’ve seen a number of companies invest in what we call Remote Operation Centres, which have created a whole class of jobs that were not previously available in the mining industry,” says Knights.
Automation’s impact on the global mining sector is unlikely to be either smooth or homogenous. But one thing looks certain: if its claims to shared value are to remain valid into the future, it will have to ditch its ‘colonial’ model for a more collaborative, confederate one instead.