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Liu Qingfeng, chairman of Chinese AI champion iFlyTek, is also a delegate to China’s National People's Congress (NPC) parliament. Photo: Handout

Chinese tech leader says AI can play a role in Beijing’s goal of eliminating poverty

  • Beijing had set 2020 as a target to rid the country of poverty but that goal has been thrown into doubt by the impact of the coronavirus pandemic on the economy
  • iFlyTek is among a number of companies providing disabled people with AI-powered tools for reading aloud and auto transcribing

China’s ambitions to eliminate poverty can be helped by using artificial intelligence (AI) technology to level uneven distribution of resources and boost employment, according to an outspoken tech leader.

Liu Qingfeng, chairman of Chinese AI champion iFlyTek – and also a delegate to China’s National People's Congress (NPC) parliament – said he expects AI technology to play a vital role in lifting China out of poverty.

Beijing had set 2020 as a target year to rid the country of poverty but that goal has now been thrown into doubt by the economic destruction caused by the coronavirus pandemic.

“We will actively respond to the call [for poverty alleviation] and promote social wellness through the development of AI industries,” he told People’s Daily online earlier this week.

iFlyTek is among a number of companies providing disabled people with AI-powered tools such as reading aloud for the blind and auto transcribing for the hearing-impaired. Liu said his company was offering these services for free more than 50 million times per day.

China’s voice recognition king doubles down on offline sales

Separately, the Shenzhen-listed company has set up data labelling factories in Guizhou province, providing local residents with “stable income” from using computers to label data required for the machine learning process.

The local government in Guizhou, one of the poorest provinces in China, has set up a dedicated department to oversee the development of its big data industry, which includes data labelling, collection and processing. While this is creating much-needed new jobs, some of this work has been criticised as being repetitive and not the kind of higher-skilled labour the advent of AI has promised.

China has set an ambitious goal of becoming a global leader in AI by 2030. The government expects the area defined as core AI to be worth 150 billion yuan (US$21.2 billion) by 2020, while related industries will reach 1 trillion yuan in value, according to a detailed road map released in 2017.

By 2030, China wants to lead the world in innovation and building a smart economy, according to the road map, with core AI activities valued at 1 trillion yuan by that time and related industries worth over 10 trillion yuan.

AI has also enabled schools in remote areas in Yunnan, Guizhou and Sichuan provinces to access quality education resources and the technology has brought assistive diagnosis and treatment tools to rural clinics, according to Liu.

AI applications surge as China battles coronavirus outbreak

Founded in 1999 and based in Hefei, the capital of eastern China’s Anhui province, iFlyTek has become the country’s foremost developer of advanced speech recognition and natural language processing systems. With state-owned China Mobile as its largest shareholder, the company has a range of products including a smart translator, teaching robots and educational toys.

Still, the technology dubbed as the fourth industrial revolution has raised concerns over automation-led job losses. Uncertainties have also been raised as to whether investment in AI can transfer into productivity growth that benefits the general public.

A growing number of academics, including some Chinese scholars, are calling for a reality check on the much-touted AI revolution, arguing it could fall victim to what is known as the Solow Paradox.

Postulated by American economist Robert Solow, the theory describes the “discrepancy between measures of investment in information technology and measures of output at the national level.” The theory was used to help understand the slowdown in productivity growth in the US in the 1970s and 1980s despite rapid development of information technology over the same period.

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