AI and other technology must play a bigger role in accelerating learning, training and professional development if the mining industry hopes to address major skills gaps in areas such as tailings management, a webinar involving some of the industry’s highly respected academics in the field has heard.
“There is definitely a role to play for some of the emerging technologies, and some technologies that already exist, to really accelerate the rate at which we can bring new people up to speed with the skills they need,” Boston Consulting Group’s Rohin Wood said on the Global Acceleration of Tailings Expertise (GATE) webcast hosted by Australian mining software company K2fly.
Wood was joined on a panel by Colorado School of Mines mining engineering professor Priscilla Nelson and Colorado State University associate professor Chris Bareither in the US.
University of Queensland professor David Williams and University of Western Australia professor Andy Fourie joined from Australia.
All four academics have been pushing their respective tertiary institutions, and industry, to address what has been shown to be a yawning gap in the number of skilled engineers needed to help the industry meet requirements of its new Global Industry Standard on Tailings Management (GISTM).
Wood brought more of a technologist’s viewpoint as BCG’s global lead for mining analytics. He is also a managing director and partner with the firm in Australia.
“On the supply side we’ve already heard about some of the challenges of basically filling the pipeline of human capital to solve the problem,” he said.
“The obvious thought that comes to mind is, can we fully automate this using technology?
“Can we create artificial EORs [engineers of record], for instance?
“The prevailing view a couple of years ago was that sort of thing is 50-to-100 years out.
“I think the prevailing view now is probably 10-to-20.
“We’re still a long way off. We’re not going to get there fast enough, I think is the answer [to address the current skills gap].
“You can’t pick up any newspaper without reading about generative pre-trained transformers or GPTs as they’re known. There’s a lot of discussion around the role of these technologies, not just here, but actually across all labour markets.
“[But] we still need humans, primarily because as amazing as the technology is, largely at the moment it’s basically still autocomplete on steroids.”
Williams said making validated field information, captured experience, and course material available via interactive Chat-type platforms could be part of the solution to an array of challenges in front of industry and academia.
“A lot of students just want an equation and the numbers to put into an equation – a typical engineering-type solution – and I tell them, if that’s all you can do in a very short space of time you’ll have no role,” he said.
“Rohin’s just highlighted this … We don’t want trained monkeys.
“What we need is to be able to embed in students this curiosity to think critically and add value.
“And I can see an increasing role for AI in that.
“We need to engender in young people who get into the tailings field [an ability] to exercise judgment. And if they can get information through AI, perfect.
“How many students go to a library these days at universities? Most don’t. They’ll first search Google.
“One of the unfortunate things about Google is it probably only goes back a certain time, because prior to, say, 20 or 30 years ago, people haven’t bothered putting up material into Google. In the last 20 or 30 years, they have.
“So it’s biased. And we don’t learn generationally that way because we haven’t gone back more than one generation.”
Nelson said: “I’m concerned we’re going to be facing many retirements in the not so distant future.
“A lot of experience is going to retire with the people who leave.
“We have to find some way to capture that experience and … to [have] on-demand access to expertise so that when we have people going out into the field, perhaps not having as much experience, not necessarily understanding what they’re seeing, there is access for them.
“That involves on-demand mentorship [and] on-demand access to experience.”
Wood said “virtual assistants” had important roles to play in accelerating classroom learning and also experiential training.
“These algorithms are already quite good at paraphrasing and representing information in ways that can effectively help people understand and have those kind of aha moments, and hopefully accelerate the rate at which people understand how to do all the tasks they need to do to be a competent tailings engineer,” he said.
“Now you can imagine a world in which instead of getting a list of things that might be useful, you’re talking be an algorithm that’s read all of that and can actually direct you to the information more efficiently and much faster.
“This is to the reason businesses are investing billions of dollars into research.
“This is the thing that could dislodge Google, it is that disruptive.”
Williams said continuing professional development, or CPD, demand was “about 10-times bigger than the formal degree demand” for instruction and accreditation.
“Just imagine a ChatGPT equivalent [for] tailings,” he said.
“Or mining in general.
“The audience globally is big enough to probably support that.”
