China • 9 Min Read • Feb 28, 2020
Deciphering China’s AI strategy
By Jibu Elias
The AIDP, released by China’s chief administrative body called the State Council in July 2017, sets an aim of making China the world leader in AI by the year 2030.
For centuries, long before the days of copycat manufacturing and cheap labour market, China was the cradle of inventions and innovations. From paper, silk, porcelain, tea, to gun powder, iron smelting, the compass and movable type printing, the Chinese was always a step ahead in terms of invention throughout human history.
Even though the recent centuries witnessed China losing that title as a result of wars and political instability, it regained some of its lost glory in the last few decades by emerging as a manufacturing powerhouse. This “great leap” in technological progress along with their ideology of ‘shasshoujian’ or the asymmetric military strategy, has led them to identify AI as the perfect tool that will help them in leapfrogging other global superpowers in terms of economic and military capabilities. As a neighbour and a prominent trade partner, it is imperative for India to understand, synthesize, and develop a competitive AI strategy.
Before we examine China’s official AI strategy in detail, one has to learn that since 2013 AI started to appear in various national-level policy documents of the country. One notable example is the 2015 guidelines on China’s Internet+ Action, which aimed at integrating the internet into all the elements of economy and society. The document released by the State Council “clearly stated the importance of cultivating emerging AI industries and investing in research and development,” notes a 2019 paper by Huw Roberts, et al. Similarly, the Central Committee of the Communist Party on China’s 13th Five-Year Plan from March 2016 mentioned “AI as one of the six critical areas for developing the country’s emerging industries and... an important factor in stimulating economic growth.”
However, China’s approach towards AI took a significant shift in 2016 March, when Deep Minds’s Alpha Go defeated the South Korean world champion in the game Go- Lee Sedol. The event was viewed by over 280 million people in China live. According to Kai-Fu Lee, “AlphaGo’s victories were both a challenge and an inspiration. The event turned into China’s ‘Sputnik moment’ for artificial intelligence.”
“Overnight, China plunged into an artificial-intelligence fever. The buzz didn’t quite rival America’s reaction to Sputnik, but it lit a fire under the Chinese technology community that has been burning ever since,” Lee wrote in his book ‘AI Superpowers’.
This historic moment led the Chinese Central Government to work on an ambitious plan to build artificial intelligence capabilities and thus born the ‘New Generation Artificial Intelligence Development Plan’ (AIDP) of 2017. The AIDP, released by China’s chief administrative body called the State Council in July 2017, sets an aim of making China the world leader in AI by the year 2030. It is this single policy document that one needs to study to understand China’s AI ambitions.
New Generation Artificial Intelligence Development Plan (AIDP)
The strategy laid out in the AIDP can be described as both long term and short term oriented at the same. The major goals of AIDP can be summarised in three key points. Firstly, the short term goal through which by 2020 China aims to accomplish competitiveness with other major power in terms of AI research and development. Its progress on this goal is quite clear from the country’s recent accomplishment in toppling the US in terms of publishing the most number of citable AI research papers. Furthermore, China intends to create an AI-based industry worth around 150 billion Yuan or 21 billion dollars, as well as to set ethical norms and industry standards for AI.
The second point or the medium-term strategy emphasises on the county accomplishing a breakthrough in the area of AI by 2025. The focus here is on creating world-leading AI tools, as well as in reaching significant milestones in AI research and development. The country also plans to grow its AI industry to 400 billion Yuan (58 billion dollars) by this time frame.
Finally, the third and the long term, yet the most prominent goal of China’s AI strategy, which is for the country to become the world’s innovation centre in AI or an AI superpower by 2030. The state also aims to double its AI economy to one trillion Yuan (147 billion dollars). This can also be read in part with an intention to accomplish an extraordinary milestone in AI, such as the creation of first artificial general intelligence or AGI.
However, analysing China’s AI strategy plan is only half the story. But, its implementation side is what aspiring countries such as India should try to imitate.
Empowering the local governments
When it comes to the implementation of China’s AI strategy, there are two responsible governing bodies. They are the AI Strategy Advisory Committee established in 2017 by the Ministry of Science and Technology and the AI Plan Promotion Office. However, contrary to general belief outside China, these bodies, alongside the AIDP itself, only exist to provide guidelines and stamp of approval for incentivising local projects and private companies that implement or develop AI technology. This means that even though theoretically the AIDP acts as the great master plan for China’s AI ambitions, in practice the actual invention, innovation and transformation is driven by local governments, sometimes at the city or municipal level, and the private sector.
It is also to be noted that the AIDP also prioritise in building better coordination between provinces and local governments in the last few years. Furthermore, China developed a political structure in which it intends at developing “a system of incentives for fulfilling national government Policy aims”. These include promotions for provincial politicians based on economic performances, as well as other incentives for following centrally defined government initiatives. Thus, as Matt Sheehan of Marco Polo Institute pointed out “the local government becomes a hotbed for testing and developing government policies”, and in the case of AI adoption, it remains the same.
National AI Champions
Another critical component of China’s AI strategy is private players. In the private sector, the government has taken steps to endorse certain corporates and startups as AI Champions for developing AI tools in a specific sector. These AI Champions include Baidu, Alibaba, and Tencent, with their focusing sectors being vehicles, smart cities, and medical diagnosis, respectively. The AI Champion Program exists because these companies agree to focus on the national strategy. And in return, they get preference in contract bidding, easy financing and even market share protection at times as pointed out by Chinese scholar Antonio Graceffo.
“National champions are promoted for the purpose of job creation, technology and skill acquisition, and building competitive advantage. Specific brands were also selected for government subsidies to transform them into national champions. As a result of champion policies, China’s largest companies are improving on their stakes, which makes them more able to compete on a global scale,” writes Graceffo in his 2017 Foreign Policy article.
However, these AI champions also face intense domestic competition in their specific sectors, and the government patronage does not prohibit smaller companies benefiting from the financial incentive structure. On the other hand, tech startups within the country also now receive government support and subsidies for developing AI technology. Innovations centres such as Zhongguancun Innovation Town are purpose-built as an incubator workspace for these startups.
Takeaways for India
Compared to the AI superpowers such as China and the US, India lags behind significantly in terms of funding and research infrastructure in AI. However, that has not stopped the vast pool of Indian talent from developing AI programs or in implementing them to address socio-economic challenges. In fact, unlike other countries, India has positioned its AI mission to harness the power of this technology for social transformation and in empowerment of its people. However, borrowing one or two tricks from the Chinese playbook can provide the boost. According to recent estimates, AI development and adoption will add over a trillion-dollar to Indian economy by 2030.
One key factor for India for hastening its AI adoption, especially with the goal of making its impact reach the poorest of poor, is to create synergy between the central and state governments. With India’ government structure being “unitary as well as federal according to the requirements of time and circumstances”, as B. R Ambedkar pointed out, further efforts should be taken to help states promote and adopt AI. Recently, NITI Aayog has taken steps in this direction with its State Consultation workshops. However, a more incentive-based program would exponentially fasten state’s adoption of AI tools.
On the side of research and development, emulating China’s AI Champion strategy for Indian corporates and startups can be beneficial. With globally reputed IT companies and private enterprises, the AI Champion policy would provide an incentive for companies and startups to focus their development and deployment to specific sectors leading to a more balanced adoption of AI.
Comparing India’ ambitions to China and the US is never ideal, as India is unique and diverse in numerous ways, and the country itself is focusing on finding its own voice in the global AI race. However, adopting one or two strategies from China or the others that seemed to have yielded results could further boost our chances to even cross the 1 trillion mark we are expected to add to the GDP.
Image by Philip Jägenstedt from Flickr
About the author
Content and Research Lead at INDIAaiJibu Elias is the Content and Research Lead at INDIAai, currently lending his wide knowledge and keen insight into artificial intelligence for building a unified AI ecosystem in India. He specialises in ethical and legal implications of AI. He is an alumnus of the London School of Economics (LSE), where he studied International Relations, specialising in Sino-India relations.
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