AI could make digital divide worse if we’re not careful

AI vs human digital divide
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ITEM: Adoption of various AI technologies is likely to disrupt the global economy in ways that could potentially widen the digital divide unless policymakers, companies and even workers take steps to mitigate such an outcome.

That’s according to a new research discussion paper from McKinsey Global Institute in which the authors simulated the impact of AI on the world economy by 2030. The objective: determine the economic benefits of widespread AI adoption, the likely disruptions that will accompany that trend (both good and bad), how the benefits and negative effects are likely to be distributed among countries, companies and individual workers, and how that distribution could potentially hamper the overall benefits AI could potentially deliver.

(Note: the report classifies AI in five broad categories: computer vision, natural language, virtual assistants, robotic process automation, and advanced machine learning. McKinsey reckons that 70% of companies in 2030 will have absorbed at least one of these – less than half will have absorbed all five.)

The good news: “AI has the potential to deliver additional global economic activity of around $13 trillion by 2030, or about 16% higher cumulative GDP compared with today. This amounts to 1.2% additional GDP growth per year.”

The bad news: “AI might widen gaps between countries, reinforcing the current digital divide.”

For example:

Leaders of AI adoption (mostly in developed countries) could increase their lead over developing countries. Leading AI countries could capture an additional 20 to 25 percent in net economic benefits, compared with today, while developing countries might capture only about 5 to 15 percent.

According to McKinsey, that’s partly the product of developed countries having more economic incentive to adopt AI – either to stimulate higher productivity growth as GDP momentum slows down, or to replace relatively expensive human labor with automation. By contrast, developing countries have other ways to improve productivity, and the economic benefits of AI adoption are smaller compared to developed countries (although McKinsey points to China as a likely exception to this).

For companies, the report says that – unsurprisingly – frontrunners of AI adoption will reap far more benefits than laggards:

By 2030, they could potentially double their cash flow […] This implies additional annual net cash-flow growth of about 6 percent for longer than the next decade. […]

At the other end of the spectrum, nonadopters might experience around a 20 percent decline in their cash flow from today’s levels …

On the employee level, AI could shift job demand from jobs involving repetitive tasks and requiring low digital skills (which could decline as much as 40% by 2030) toward those that are socially and cognitively driven and require more digital skills (which could grow as much as 50%). That shift will impact wages, where repetitive/low-digital-skills jobs are likely to pay even less than they do now. This could be complicated by the likelihood that companies will scramble to find people with the right skill sets for high-digital-skill jobs, while the workers who don’t have those skill sets will struggle to find low-digital-skill jobs.

This might or might not impact net employment – in other words, fears of AI eliminating jobs without generating new jobs could be at least overblown, as McKinsey expects total full-time-equivalent-employment demand by 2030 to remain flat, or only slightly down. But as the above paragraph indicates, the problem won’t be the number of jobs available but the ability to fill them and what to do with the people who aren’t qualified for the new jobs that emerge.

This is an important distinction in the context of the overall debate of whether AI is a job-killer, and whose responsibility it is to ensure that it’s not. The projected numbers may indicate that we’ll still have more or less as many jobs available in 2030 as we do now (in proportion to the working population, I assume), but that’s small comfort to the average worker living paycheck to paycheck (or gig to gig) who gets replaced by automation and doesn’t have the skills to qualify for whatever new jobs may be created.

As for whose responsibility it is to mitigate this, McKinsey’s conclusion is: basically, everyone. For a start, individual workers at all levels simply have to accept the reality that the days of job stability in a single industry are done – we are shifting to a gig economy where turnover is frequent and workers must refresh and update their skills constantly to stay employable.

At the same time, however, governments and companies have a role to play, the report says:

Policy makers will need to show bold leadership to overcome understandable discomfort among citizens about the perceived threat to their jobs as automation takes hold. Companies will also be important actors in searching for solutions on the mammoth task of skilling and reskilling people to work with AI.

You can read the full report here [PDF].

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John C. Tanner
About John C. Tanner 406 Articles
John Tanner has been covering the Asia-Pacific telecoms industry since 1996. He has two degrees in telecommunications, and worked for six years in the US radio industry in various technical and advisory capacities, covering radio and satellite equipment maintenance, studio networking, news writing and production, the latter of which earned him several regional and national awards.

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