There is a code ceiling that prevents career advancement — irrespective of gender or race — because, in an AI-powered organization, junior employees and freelancers rarely interact with other human co-workers. Instead, they are managed by algorithms. As a result, a global, low-paid, algorithmic workforce is emerging. You will increasingly find a gap between top executives and an outer fringe of transient workers, even within organizations. Whether in retail or financial services, logistics or manufacturing, AI-powered organizations are being run by a small cohort of highly paid employees, supported by sophisticated automation and potentially millions of algorithmically managed, low-paid freelancers at the periphery. Job polarization is only part of the problem. What we should really fear is the algorithmic inequality trap that results from these algorithmic feedback loops.
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The risks of algorithmic discrimination and bias have received much attention and scrutiny, and rightly so. Yet there is another more insidious side-effect of our increasingly AI-powered society — the systematic inequality created by the changing nature of work itself. We fear a future where robots take our jobs, but what happens when a significant portion of the workforce ends up in algorithmically managed jobs with little future and few possibilities for advancement?
One of the classic tropes of self-made success is the leader who comes from humble beginnings, working their way up from the mailroom, the cash register, or the factory floor. And while doing that is considerably tougher than Hollywood might suggest, bottom-up mobility was at least possible in traditional organizations. Charlie Bell, former CEO of McDonalds, started as a crew member flipping burgers. Mary Barra, chairman and CEO of General Motors, started on the assembly line. Doug McMillon, CEO of Walmart, started in a distribution center.
By comparison, how many Uber drivers do you think will ever have the chance to attain a managerial position at the company, let alone run the ride-sharing giant? How many future top Amazon executives will start their careers by delivering packages or stacking shelves? The billionaire founder and CEO of Instacart may have personally delivered the company’s first order, but how many others will follow in his footsteps?
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Here’s the problem: There’s a “code ceiling” that prevents career advancement — irrespective of gender or race — because, in an AI-powered organization, junior employees and freelancers rarely interact with other human co-workers. Instead, they are managed by algorithms.
In this new era of digitally mediated work, there is typically a hierarchical information flow, in which the company decides the information they choose to share with you. Unlike driving a taxi, where there is open radio communication between drivers and the dispatch operator, and among the drivers themselves, when you work for Uber or Lyft, the content of your interactions is the output of an optimization function designed to maximize efficiency and profit.
To be managed algorithmically is to be subject to constant monitoring and surveillance. If you are one of the millions of food delivery workers in China working for Meituan or Ele.me, an algorithm determines how long it should take you to drop off an order, reducing your pay if you fail to meet your deadline. Similarly, employees in Amazon distribution centers are also carefully tracked by algorithms; they must work at “Amazon pace” — described as “somewhere between walking and jogging.”
When you are a gig economy worker, it is not only your AI bosses that should concern you; your co-workers are often also your competition. For example, Chicago residents who live near Amazon’s distribution points and Whole Foods stores reported the strange appearance of smartphones hanging from trees. The reason? Contract delivery drivers were desperate to trump their rivals for job assignments. They believed that hanging their devices near delivery stations would help them game the work allocation algorithm; a smartphone perched in a tree could be the key to getting a $15 delivery route mere seconds before someone else.
Work has been changing over the last few decades. The labor market has grown increasingly polarized, with middle-skill jobs being eroded relative to entry-level, low-skill work, and high-level employment that requires greater skill levels. The Covid-19 crisis has likely accelerated the process. Since 1990, every U.S. recession has been followed by a jobless recovery. This time, as AI, algorithms, and automation reshape the workforce, we may end up with something worse: a K-shaped recovery — where the prospects of those at the top soar, and everyone else sees their fortunes dive.
The new digital divide is a widening gap between workers with access to higher education, leadership mentoring, and job experience — and those without. In my recent book, The Algorithmic Leader, I explore one particularly dire scenario: a class-based divide between the masses who work for algorithms, a privileged professional class who have the skills and capabilities to design and train algorithmic systems, and a small, ultra-wealthy aristocracy, who own the algorithmic platforms that run the world.
A global, low-paid, algorithmic workforce is already emerging. In Latin America, one of the fastest-growing startups is Rappi, a mix of Uber Eats, Instacart, and TaskRabbit. Customers in cities like Bogotá and Mexico City pay about $1 an order or a flat $7 a month. In return, they can access a vast on-demand network of couriers who deliver food, groceries, and just about anything else you want. Amazon has an informal network of delivery people, called Amazon Flex, ready to drop packages right to your door — and soon even hand them to you in the street, place them in your car trunk, or open the door to your house and store your groceries in your fridge.
In his 1930 lecture Economic Possibilities for Our Grandchildren, John Maynard Keynes predicted that by around 2030, the production problem would be solved, and there would be enough of everything for everyone. The catch, however, is that machines would cause technological unemployment. The scenario that Keynes didn’t fully anticipate was our present case of high technological employment, with an accompanying degree of high inequality.
The workforce is changing; so too is the workplace. You will increasingly find a gap between top executives and an outer fringe of transient workers, even within organizations. Whether in retail or financial services, logistics or manufacturing, AI-powered organizations are run by a small cohort of highly paid employees, supported by sophisticated automation and potentially millions of algorithmically managed, low-paid freelancers at the periphery.
Job polarization is only part of the problem. What we should really fear is the algorithmic inequality trap that results from feedback loops. Once you are a gig economy worker reliant on assignments meted out by your smartphone, not only are there few opportunities for promotion or development, but other algorithms may further compound your situation. Think of it as a digital poorhouse. With their earnings and work assignments held hostage by market fluctuations, the new AI underclass may be penalized by automated systems that determine access to welfare, lending, insurance, or health care, or that set custodial sentences.
Nevertheless, it is dangerous to seek quick fixes for a problem that has yet to fully manifest, especially if it means grafting 20th-century worker protections onto 21st-century business models. Already, governments and regulators supported by populist platforms are focused on attacking global digital giants. They seek to prevent them from avoiding tax liabilities and are working to regulate their freelance workforce’s labor conditions, to apply restrictions on their collection of data, and even to tax their robots. Some of these ideas have merit. Others are premature, or worse, just political theater.
The longer-term solution to algorithmic inequality will not lie in just taxation and regulation, but rather in our ability to provide an adequate education system for the 21st century. Rebooting education will not be easy. Rather than looking for ways to use AI in teaching, the real question is: How do we teach people to harness machine intelligence in their careers? And how do we teach people to be prepared for a lifetime of constant learning and retraining?
Business leaders have a crucial role to play. Not only should they carve out channels of communication, feedback, and advancement for freelancers at the edge of their organizations, they need to get serious about retraining and community engagement. For example, AT&T is retraining half of its workforce, while Cisco, IBM, Caterpillar, McKinsey, and JPMorgan are offering internships to high school students and are working with local schools to upgrade their teaching curriculums. These are all good initiatives, but more will be needed — not just for social cohesion, but also to ensure the diversity and agility of tomorrow’s workforce.
We need a better plan for the future. Without one, the algorithmic inequality trap will be a story told not in statistics and wealth ratios, but in distress signals — smartphones hanging from trees, tent cities for the homeless, and human couriers scanning the skies for the delivery drones that spell their impending end.
OTTAWA – Canada’s unemployment rate held steady at 6.5 per cent last month as hiring remained weak across the economy.
Statistics Canada’s labour force survey on Friday said employment rose by a modest 15,000 jobs in October.
Business, building and support services saw the largest gain in employment.
Meanwhile, finance, insurance, real estate, rental and leasing experienced the largest decline.
Many economists see weakness in the job market continuing in the short term, before the Bank of Canada’s interest rate cuts spark a rebound in economic growth next year.
Despite ongoing softness in the labour market, however, strong wage growth has raged on in Canada. Average hourly wages in October grew 4.9 per cent from a year ago, reaching $35.76.
Friday’s report also shed some light on the financial health of households.
According to the agency, 28.8 per cent of Canadians aged 15 or older were living in a household that had difficulty meeting financial needs – like food and housing – in the previous four weeks.
That was down from 33.1 per cent in October 2023 and 35.5 per cent in October 2022, but still above the 20.4 per cent figure recorded in October 2020.
People living in a rented home were more likely to report difficulty meeting financial needs, with nearly four in 10 reporting that was the case.
That compares with just under a quarter of those living in an owned home by a household member.
Immigrants were also more likely to report facing financial strain last month, with about four out of 10 immigrants who landed in the last year doing so.
That compares with about three in 10 more established immigrants and one in four of people born in Canada.
This report by The Canadian Press was first published Nov. 8, 2024.
The Canadian Institute for Health Information says health-care spending in Canada is projected to reach a new high in 2024.
The annual report released Thursday says total health spending is expected to hit $372 billion, or $9,054 per Canadian.
CIHI’s national analysis predicts expenditures will rise by 5.7 per cent in 2024, compared to 4.5 per cent in 2023 and 1.7 per cent in 2022.
This year’s health spending is estimated to represent 12.4 per cent of Canada’s gross domestic product. Excluding two years of the pandemic, it would be the highest ratio in the country’s history.
While it’s not unusual for health expenditures to outpace economic growth, the report says this could be the case for the next several years due to Canada’s growing population and its aging demographic.
Canada’s per capita spending on health care in 2022 was among the highest in the world, but still less than countries such as the United States and Sweden.
The report notes that the Canadian dental and pharmacare plans could push health-care spending even further as more people who previously couldn’t afford these services start using them.
This report by The Canadian Press was first published Nov. 7, 2024.
Canadian Press health coverage receives support through a partnership with the Canadian Medical Association. CP is solely responsible for this content.
As Canadians wake up to news that Donald Trump will return to the White House, the president-elect’s protectionist stance is casting a spotlight on what effect his second term will have on Canada-U.S. economic ties.
Some Canadian business leaders have expressed worry over Trump’s promise to introduce a universal 10 per cent tariff on all American imports.
A Canadian Chamber of Commerce report released last month suggested those tariffs would shrink the Canadian economy, resulting in around $30 billion per year in economic costs.
More than 77 per cent of Canadian exports go to the U.S.
Canada’s manufacturing sector faces the biggest risk should Trump push forward on imposing broad tariffs, said Canadian Manufacturers and Exporters president and CEO Dennis Darby. He said the sector is the “most trade-exposed” within Canada.
“It’s in the U.S.’s best interest, it’s in our best interest, but most importantly for consumers across North America, that we’re able to trade goods, materials, ingredients, as we have under the trade agreements,” Darby said in an interview.
“It’s a more complex or complicated outcome than it would have been with the Democrats, but we’ve had to deal with this before and we’re going to do our best to deal with it again.”
American economists have also warned Trump’s plan could cause inflation and possibly a recession, which could have ripple effects in Canada.
It’s consumers who will ultimately feel the burden of any inflationary effect caused by broad tariffs, said Darby.
“A tariff tends to raise costs, and it ultimately raises prices, so that’s something that we have to be prepared for,” he said.
“It could tilt production mandates. A tariff makes goods more expensive, but on the same token, it also will make inputs for the U.S. more expensive.”
A report last month by TD economist Marc Ercolao said research shows a full-scale implementation of Trump’s tariff plan could lead to a near-five per cent reduction in Canadian export volumes to the U.S. by early-2027, relative to current baseline forecasts.
Retaliation by Canada would also increase costs for domestic producers, and push import volumes lower in the process.
“Slowing import activity mitigates some of the negative net trade impact on total GDP enough to avoid a technical recession, but still produces a period of extended stagnation through 2025 and 2026,” Ercolao said.
Since the Canada-United States-Mexico Agreement came into effect in 2020, trade between Canada and the U.S. has surged by 46 per cent, according to the Toronto Region Board of Trade.
With that deal is up for review in 2026, Canadian Chamber of Commerce president and CEO Candace Laing said the Canadian government “must collaborate effectively with the Trump administration to preserve and strengthen our bilateral economic partnership.”
“With an impressive $3.6 billion in daily trade, Canada and the United States are each other’s closest international partners. The secure and efficient flow of goods and people across our border … remains essential for the economies of both countries,” she said in a statement.
“By resisting tariffs and trade barriers that will only raise prices and hurt consumers in both countries, Canada and the United States can strengthen resilient cross-border supply chains that enhance our shared economic security.”
This report by The Canadian Press was first published Nov. 6, 2024.
