A writer by day and a reader by night, Evelyn is a blogger and content marketer from Australia.
Whenever the implications of Artificial Intelligence are discussed, the conversation tends to focus on high-income countries. Most of the research on this subject covers the United States and Europe while overwhelmingly developing world regions such as South Asia, Africa and South America are often overlooked.
However, any discussion about automation that doesn’t include its impact on the developing world is myopic, to say the least.
For more than two centuries, industrialization has been the key to poverty alleviation. Countries have achieved economic growth by setting up factories that employ a large number of semi-skilled workers. China has used this formula to lift 850 million people out of extreme poverty.
But advanced AI promises to eliminate the need for labor-intensive factories, creating a dilemma for countries striving to achieve economic betterment.
It’s estimated that 42.39% of Indians work in agriculture. Compared to this, farmers and ranchers are just 1.3% of the American workforce. It’s also important to remember that India is the second most populous country in the world with 1.3 billion citizens.
Most of the work associated with these sectors is routine and repetitive. It’s work that’s bound to get automated in the coming years. Taking this into consideration, automation will hit poorer countries harder and could lead to mass unemployment.
Harvard University economist Dani Rodrik calls it “premature deindustrialization” where countries who have just begun to grow through industrialization are at the risk of losing their manufacturing jobs.
“The term deindustrialization is used today to refer to the experience mainly of these advanced economies.” Rodrik writes in a paper published in 2015. “With some exceptions, confined largely to Asia, developing countries have experienced falling manufacturing shares in both employment and real value added, especially since the 1980s”.
But even some of Asia's emerging economies are at risk of losing whatever they’ve achieved in the last few years. These countries are not yet rich enough to soften the blow automation will deal to them.
For instance, Bangladesh owes its rise largely to textile. It’s the second biggest exporter of ready-made clothing after China and depends heavily on garments for foreign reserve. According to one estimate, 80% of textile jobs in the country could be lost when AI takes over.
One thing is for certain, automation is coming. Manufacturers wouldn’t think twice about integrating technologies that promise to optimize their procedures while reducing cost at the same time.
Sooner than later, the fashion industry will embrace AI and this will create several challenges for countries such as Bangladesh. Naturally, the developing nations will aim to up-skill their population but that will be another mountain to climb.
Such efforts will require policy initiatives on a broad scale that will include everything from infrastructure development to social, healthcare and education provision. Even then, these will be insufficient considering the scale on which AI will disrupt industries.
Developing countries have the option of disincentivizing automation by taxing the use of robots or incentivizing the use of human labor through tax breaks or cutting minimum wages. However, this could push companies into countries that don’t discourage automation —which is why it’s unlikely that low-income countries will ever go this way.
Futurists such as GigaOM’s Byron Reese believe AI will create more jobs than it will displace. According to Reese; “AI will be the greatest job engine the world has ever seen.”
While there’s no doubt algorithms would need human help for training and maintenance, and this will create new job opportunities —some believe the developing world might miss out.
Ian Goldin, a professor at the University of Oxford, who has extensively researched globalization, believes most AI jobs will be concentrated in the developed world. “(The) fact that poor countries also tend to suffer shortages of highly skilled labour could further undermine their competitiveness.” he explains.
Goldin believes the widespread use of 3D printing might make things worse for emerging economies. “The development of supplementary technologies will add to the challenge. 3D printing, will combine with AI to allow consumers in rich countries to manufacture individually customised clothes, shoes, devices and other products, by themselves, much closer to home.”
Production of this sort will eliminate any need for companies to outsource their production to lower-income countries.
Goldin believes this will lead to increased inequality and more concentration of wealth in parts of the world that are already rich.
Center for Global Development’s 2018 study advises policymakers in the developing world to stay ahead of the machines.
“A—risky but potentially inevitable—long-term coping strategy for developing countries would be to anticipate automation trends and to try to (further) develop a productive post-industrial sector.”
The authors point toward some Automation Resistant Sectors (ARS) that governments can invest in to create employment. “Such an ARS could, for example, involve the social, education and health-care sectors, and some forms of tourism, and infrastructure construction which are generally considered resilient despite increasing service automation”.
However, the study highlights that these sectors do not provide high value addition as of it and may not sufficiently scalable. But it is one of the many ways low-income countries can save themselves from the onslaught of Artificial Intelligence.
AI-induced unemployment is one of the major challenges for the developing world. But the same technology promises to help these countries counter some of their long-standing issues.
Children in remote regions of Africa often lack access to good educational facilities. Dapito, an adaptive learning platform helps students study remotely. It uses AI to design courses whose structure, assessment and content are based on the weakness and strengths of students.
Some emerging nations are also short on doctors and have an extremely high cost for healthcare. AI could assist medical personnel and optimize the diagnostic process. Nirmai in India is doing exactly that by providing a cost-efficient way to detect breast cancer in patients. It uses Thermalytix, which is a computer-aided diagnostic engine enabled by AI, to provide a low-cost alternative to mammography.
Likewise, developing regions also have to deal with a bulk of refugees due to political instability. In Uganda, Refunite is a microtasking platform that’s giving refugees small income for performing verified tasks. It uses image categorization for training algorithms.
Experts such as Ian Goldin argue that AI could improve health and education in poor countries and create new jobs for the people. However, they don’t believe there’s enough evidence to prove these technologies will disrupt the region in a good way.
Even though there are examples in countries like Uganda, Kenya and India of AI changing life for the better, it isn’t certain that this could be replicated all around the developing world.
Job security and inequality are the two biggest issues policymakers in emerging economies will have to address as the world embraces Artificial Intelligence. It’s high time for legislators in these countries to institute policies that will help them weather the storm.
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