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Labour, Technology

AI has a talent for skills training and knowledge transfer

Peter Caulfield
AI has a talent for skills training and knowledge transfer

Although Artificial Intelligence (AI) is still in its technological infancy, like human children it has a voracious appetite and is growing so quickly its elders hardly recognize it from one day to the next.

We can’t be sure what AI will look like when it’s all grown up, but one thing it already seems to have an aptitude for is skills training and knowledge transfer.

“Using AI to help train employees can help build trust in the technology,” says Steven Tobin, special adviser to the Future Skills Centre (FSC) in Toronto.

“Many people are still fearful of AI and uncertain about it, and that can hold back the adoption of artificial intelligence. There are big benefits from using AI. Not adopting it and other new technologies is partly responsible for Canada’s lagging productivity.”

Tobin says a project supported by FSC developed a set of AI skill-sets that can be used for educational and training interventions.

“The project showed that carefully designed education and training can help build trust in AI,” he says.

“Various sources of employment recruitment and job platforms have increased their use of AI for labour market matching (of job requirements with applicants).”

AI is also able to identify the skills, qualifications and responsibilities that go with job titles.

For example, OpportuNext is a free career tool that uses AI to match individuals’ skills with a variety of possible career paths.

Tobin says there are some concerns about the use of AI in career development because of the possibility it could reproduce societal biases.

However, because AI uses statistical prediction methods that can be audited, it can also be programmed to avoid bias and help equity-seeking groups and individuals in situations where human predictions might be tainted by cognitive biases.

Timescapes, a New Zealand company with an office in Vancouver, has developed a technology it says reduces the time it takes to train employees.

Timescapes Canada enterprise account executive Victoria Beaton says Timescapes cameras and platform enable project teams to capture a visual record of an entire construction process.

The cameras and platform work together to enable users to manage their projects remotely “and get actionable construction insights from the palm of your hand.”

The system captures visual data from the project and compares it with key project milestones.

It can collect and show a visual record of an entire project or just segments of one.

In addition, AI-powered analytics enable users to make better project decisions, saving time and money, Beaton says.

“It enables users to tighten up the scheduling of personnel, plant and equipment to optimize productivity, as well as quantify the impact of weather and other conditions that impact the worksite,” says Beaton.

Looking ahead, it will soon become possible to input all the data an organization has ever collected into AI and use it to plan and make decisions, Beaton says.

In addition, AI will be able customize the data for different jobs, and employees will be able to query it and get real-time responses.

“They’ll be able to develop a project schedule by going back to similar projects and seeing how scheduling was done with them,” says Beaton.

Every construction company needs to be paying attention to these developments in AI now, she says.

“Their survival depends on AI,” says Beaton. “They need to start collecting data now and ensuring their worksites have access to it.”

Vlad Mayzel, founder and president of Smart Technologies in Vancouver, says the benefits of AI are “enormous.”

“It’s like having a very cheap but very efficient workforce — but only in some areas,” says Mayzel. “It’s also susceptible to human biases. Biased people yield biased AI.”

AI is excellent at determining patterns that humans might not see.

“It’s similar to how humans know something based on past experience, but they can’t explain how they know it or how they came to the conclusion they did,” says Mayzel. “They just know it, and sometimes their gut feelings turn out to be right,”

But all of this capability comes with a catch.

“The problem is that AI still makes a lot of mistakes, just like humans,” he says.

“Sometimes it guesses but it won’t always tell us that it’s just a guess. AI has a mind of its own and it’s quite often preachy and stubborn, also just like humans. We trust AI too much and we haven’t been questioning it enough, and our complacency is only going to get worse.”

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