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AI Could Devastate the Developing World (bloomberg.com)
Kai-Fu Lee, Chairman and CEO of Sinovation Ventures and author of "AI Superpowers: China, Silicon Valley and the New World Order," reports of the devastating impacts artificial intelligence could have on the developing world. An anonymous reader shares the report from Bloomberg: In recent decades, China and India have presented the world with two different models for how such countries can climb the development ladder. In the China model, a nation leverages its large population and low costs to build a base of blue-collar manufacturing. It then steadily works its way up the value chain by producing better and more technology-intensive goods. In the India model, a country combines a large English-speaking population with low costs to become a hub for outsourcing of low-end, white-collar jobs in fields such as business-process outsourcing and software testing. If successful, these relatively low-skilled jobs can be slowly upgraded to more advanced white-collar industries. Both models are based on a country's cost advantages in the performance of repetitive, non-social and largely uncreative work -- whether manual labor in factories or cognitive labor in call centers. Unfortunately for emerging economies, AI thrives at performing precisely this kind of work.
Without a cost incentive to locate in the developing world, corporations will bring many of these functions back to the countries where they're based. That will leave emerging economies, unable to grasp the bottom rungs of the development ladder, in a dangerous position: The large pool of young and relatively unskilled workers that once formed their greatest comparative advantage will become a liability -- a potentially explosive one. Increasing desperation in the developing world will contrast with a massive accumulation of wealth among the AI superpowers. AI runs on data and that dependence leads to a self-perpetuating cycle of consolidation in industries: The more data you have, the better your product. The better your product, the more users you gain. The more users you gain, the more data you have. Lee says the best thing emerging economies can do is to "recognize that the traditional paths to economic development -- the China and India models -- are no longer viable." Countries with "less-educated workers" are advised to build up human-centered service industries.
"At the same time, developing countries need to carve out their own niches within the AI landscape," Lee writes. "... governments need to fund the AI education of their best and brightest students, with the goal of building local companies that employ AI."
Without a cost incentive to locate in the developing world, corporations will bring many of these functions back to the countries where they're based. That will leave emerging economies, unable to grasp the bottom rungs of the development ladder, in a dangerous position: The large pool of young and relatively unskilled workers that once formed their greatest comparative advantage will become a liability -- a potentially explosive one. Increasing desperation in the developing world will contrast with a massive accumulation of wealth among the AI superpowers. AI runs on data and that dependence leads to a self-perpetuating cycle of consolidation in industries: The more data you have, the better your product. The better your product, the more users you gain. The more users you gain, the more data you have. Lee says the best thing emerging economies can do is to "recognize that the traditional paths to economic development -- the China and India models -- are no longer viable." Countries with "less-educated workers" are advised to build up human-centered service industries.
"At the same time, developing countries need to carve out their own niches within the AI landscape," Lee writes. "... governments need to fund the AI education of their best and brightest students, with the goal of building local companies that employ AI."
'nuff said.
it's automation with a bit of machine learning, but it's easier to say "A.I." as shorthand for it. If this stuff works then yeah, China & India are pretty boned. They're going to have massive surplus populations and nothing to do with them. But they're also going to be straddled with a "if you don't work you don't eat" culture. They'll end up with dictators and massive wars. Eventually the US will get dragged into it too, just like we did with WWII. Same for the EU.
There's basically two scenarios where this doesn't happen. 1st, the tech doesn't actually work. That doesn't seem to be the case. The tech works just fine it just takes time to roll it out. Hence the timelines given in TFA. 2nd China & India pass laws blocking the tech roll out and retarding development in order to preserve jobs. There's a third possibility, which is make work projects, but that means paying taxes for people to do useless things, which the gov'ts will get called out on in most cases. #2 might actually happen though, but again, it's tough to get it past people. Again, people don't like paying for things they don't have too, and that includes paying for workers who could be replaced.
What this means is that the dystopia scenario is by far the most likely. And it's not like it's sci-fi even. The same thing happened during the last industrial revolution. Luddites weren't just scared of tech, they lost their livelihoods. There was nearly 80 years of technology unemployment until WWI & II came along and blew up enough stuff that we had to pay folks to put it back together.
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Different things are called "AI" these days. Thinking machines are still very primitive, there hasn't been a breakthrough there. What is starting to show results are statistical models on large data sets, that are constructed at least partially automatically.
But these depend on having a large data set, which means that whatever company has the most data will likely have the best model, which in turn attracts more users, allowing them to collect more data. So it's hard for a newcomer to gain traction.
In any case, the point I think the authors were making (the wrong article is linked so I can't easily verify it) is that AI will make it harder for developing nations to improve their economies, rather than making their current economies worse. So it's more a case of AI undermining evolutionary development than it being a revolution in itself.