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Synergy of Patent and Open-Source-Driven Sustainable Climate Governance under Green AI: A Case Study of TinyML

Author

Listed:
  • Tao Li

    (School of Intellectual Property, Nanjing University of Science and Technology, No. 200 Xiaolingwei Street, Xuanwu District, Nanjing 210094, China
    Centre for Innovation and Development, Nanjing University of Science and Technology, Nanjing 210094, China
    School of Business, Xianda College of Economics & Humanities Shanghai International Studies University, No. 390 Dong Tiyuhui Rd., Hongkou District, Shanghai 200083, China)

  • Jianqiang Luo

    (School of Management, Jiangsu University, No. 301 Xue Fu Rd., Zhenjiang 212013, China)

  • Kaitong Liang

    (School of Intellectual Property, Nanjing University of Science and Technology, No. 200 Xiaolingwei Street, Xuanwu District, Nanjing 210094, China
    Centre for Innovation and Development, Nanjing University of Science and Technology, Nanjing 210094, China)

  • Chaonan Yi

    (School of Intellectual Property, Nanjing University of Science and Technology, No. 200 Xiaolingwei Street, Xuanwu District, Nanjing 210094, China
    Centre for Innovation and Development, Nanjing University of Science and Technology, Nanjing 210094, China)

  • Lei Ma

    (Centre for Innovation and Development, Nanjing University of Science and Technology, Nanjing 210094, China
    School of Public Affairs, Nanjing University of Science and Technology, Nanjing 210094, China)

Abstract

Green AI (Artificial Intelligence) and digitalization facilitate the “Dual-Carbon” goal of low-carbon, high-quality economic development. Green AI is moving from “cloud” to “edge” devices like TinyML, which supports devices from cameras to wearables, offering low-power IoT computing. This study attempts to provide a conceptual update of climate and environmental policy in open synergy with proprietary and open-source TinyML technology, and to provide an industry collaborative and policy perspective on the issue, through using differential game models. The results show that patent and open source, as two types of TinyML innovation, can benefit a wide range of low-carbon industries and climate policy coordination. From the case of TinyML, we find that collaboration and sharing can lead to the implementation of green AI, reducing energy consumption and carbon emissions, and helping to fight climate change and protect the environment.

Suggested Citation

  • Tao Li & Jianqiang Luo & Kaitong Liang & Chaonan Yi & Lei Ma, 2023. "Synergy of Patent and Open-Source-Driven Sustainable Climate Governance under Green AI: A Case Study of TinyML," Sustainability, MDPI, vol. 15(18), pages 1-21, September.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:18:p:13779-:d:1240734
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