Artificial intelligence has become a main driving force for a new round of industrial transformation around the world. Many countries including China are seizing the opportunity of the AI revolution to promote domestic economic and technological development. This Perspective briefly introduces the New Generation Artificial Intelligence Development Plan of China (2015–2030) from the point of view of the authors, a group of AI experts from academia and industry who have been involved in various stages of the plan. China’s AI development plan outlines a strategy for science and technology as well as education, tackling a number of challenges such as retaining talent, advancing fundamental research and exploring ethical issues. The New Generation Artificial Intelligence Development Plan is intended to be a blueprint for a complete AI ecosystem for the country.
Subscribe to Journal
Get full journal access for 1 year
only $8.25 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Tax calculation will be finalised during checkout.
Rent or Buy article
Get time limited or full article access on ReadCube.
All prices are NET prices.
China issues guideline on artificial intelligence development. Gov.cn http://english.gov.cn/policies/latest_releases/2017/07/20/content_281475742458322.htm (2017).
Pan, Y. Heading toward artificial intelligence 2.0. Engineering 2, 409–413 (2016).
Pan, Y.-h. Special issue on artificial intelligence 2.0. Front. Inform. Technol. Electron. Eng. 18, 1–2 (2017).
Pan, Y.-h. Special issue on artificial intelligence 2.0: theories and applications. Front. Inform. Technol. Electron. Eng. 19, 1–2 (2018).
Zhuang, Y.-t., Wu, F., Chen, C. & Pan, Y.-h. Challenges and opportunities: from big data to knowledge in AI 2.0. Front. Inform. Technol. Electron. Eng. 18, 3–14 (2017).
Peng, Y.-x et al. Cross-media analysis and reasoning: advances and directions. Front. Inform. Technol. Electron. Eng. 18, 44–57 (2017).
Li, W. et al. Crowd intelligence in AI 2.0 era. Front. Inform. Technol. Electron. Eng. 18, 15–43 (2017).
Zheng, N.-n et al. Hybrid-augmented intelligence: collaboration and cognition. Front. Inform. Technol. Electron. Eng. 18, 153–79 (2017).
Zhang, T. et al. Current trends in the development of intelligent unmanned autonomous systems. Front. Inform. Technol. Electron. Eng. 18, 68–85 (2017).
Fisk, P. Meituan Dianping: China’s everything-app to “eat better, live better”. Gamechangers https://www.thegeniusworks.com/gamechanger/meituan-dianping/ (2019).
China’s consumer credit balance expected to exceed 10t yuan by 2020. China Banking News http://www.chinabankingnews.com/2019/01/21/chinas-consumer-credit-balance-expected-to-exceed-10t-yuan-by-2020/ (2019).
The Mobile Economy 2020 (GSMA Intelligence, 2020).
Global Status Report on Road Safety 2018 (World Health Organization, 2018).
Chen, W. et al. Cancer statistics in China, 2015. CA: Cancer J. Clin. 66, 115–132 (2016).
Bi, W. L. et al. Artificial intelligence in cancer imaging: clinical challenges and applications. CA: Cancer J. Clin. 69, 127–157 (2019).
LeCun, Y., Bengio, Y. & Hinton, G. Deep learning. Nature 521, 436–444 (2015).
Hosny, A., Parmar, C., Quackenbush, J., Schwartz, L. H. & Aerts, H. J. W. L. Artificial intelligence in radiology. Nat. Rev. Cancer 18, 500–510 (2018).
Bejnordi, B. E. et al. Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer. JAMA 318, 2199–2210 (2017).
Papandreou, G. et al. Weakly-and semi-supervised learning of a deep convolutional network for semantic image segmentation. In Proc. IEEE Int. Conf. Computer Vision 1742–1750 (IEEE, 2015).
Bonawitz, K. et al. Towards federated learning at scale: system design. Preprint at https://arxiv.org/abs/1902.01046 (2019).
Song, J. et al. IEEE Trans. Neural Netw. Learn. Syst. https://doi.org/10.1109/tnnls.2020.2989364 (2020).
Growing IoT in China (GSMA, 2019).
Zhuang, Y. et al. The next breakthroughs of artificial intelligence: the interdisciplinary nature of AI. Engineering 6, 245–247 (2020).
Wu, W., Huang, T. & Gong, K. Ethical principles and governance technology development of AI in China. Engineering 6, 302–309 (2020).
Amini, A. Soleimany, A. P., Schwarting, W., Bhatia, S. N. & Rus, D. Uncovering and mitigating algorithmic bias through learned latent structure. In Proc. 2019 AAAI/ACM Conf. AI, Ethics, and Society 289–295 (ACM, 2019).
Papernot, N., Abadi, M., Erlingsson, U., Goodfellow, I. J. & Talwar, K. Semi-supervised knowledge transfer for deep learning from private training data. In 5th Int. Conf. Learning Representations (ICLR, 2017).
China AI Development Report 2018 (Tsinghua Univ., 2018).
Lv, Y.-G. Artificial intelligence: enabling technology to empower our society. Engineering 6, 205–206 2020).
Roberts, H. et al. The Chinese approach to artificial intelligence: an analysis of policy and regulation. Preprint at https://doi.org/10.2139/ssrn.3469784 (2019).
We thank H. Shum and Z. Zhang for discussions and comments. We also thank the strategic consulting research project of the Chinese Academy of Engineering ‘AI 2.0 in China’, and the disruptive information technology research group of the Department of Information and Electronic Engineering at the Chinese Academy of Engineering. This paper is partly supported by AI Young Scientists Alliance, STCSM(Xuhui), SHEITC, NSFC (61625107).
The authors declare no competing interests.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Wu, F., Lu, C., Zhu, M. et al. Towards a new generation of artificial intelligence in China. Nat Mach Intell 2, 312–316 (2020). https://doi.org/10.1038/s42256-020-0183-4
Engineering with Computers (2021)
Dual-path network with synergistic grouping loss and evidence driven risk stratification for whole slide cervical image analysis
Medical Image Analysis (2021)
Can Students’ Computer Programming Learning Motivation and Effectiveness Be Enhanced by Learning Python Language? A Multi-Group Analysis
Frontiers in Psychology (2021)
Reform and innovation of artificial intelligence technology for information service in university physical education
Journal of Intelligent & Fuzzy Systems (2021)