| Title |
Synergy of Patent and Open-Source-Driven Sustainable Climate Governance under Green AI: A Case Study of TinyML |
| ID_Doc |
31874 |
| Authors |
Li, T; Luo, JQ; Liang, KT; Yi, CN; Ma, L |
| Title |
Synergy of Patent and Open-Source-Driven Sustainable Climate Governance under Green AI: A Case Study of TinyML |
| Year |
2023 |
| Published |
Sustainability, 15, 18 |
| DOI |
10.3390/su151813779 |
| 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. |
| Author Keywords |
climate governance; environmental sustainability; green AI; TinyML; patent; open source |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI) |
| EID |
WOS:001072589500001 |
| WoS Category |
Green & Sustainable Science & Technology; Environmental Sciences; Environmental Studies |
| Research Area |
Science & Technology - Other Topics; Environmental Sciences & Ecology |
| PDF |
https://www.mdpi.com/2071-1050/15/18/13779/pdf?version=1694773002
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