http://scholars.ntou.edu.tw/handle/123456789/26556| Title: | Artificial intelligence in negotiating energy production and other interests in marine spatial planning-managing transparency and bias | Authors: | Jao, Juei-Cheng Chuah, Jason C. T. |
Issue Date: | Jan-2026 | Publisher: | OXFORD UNIV PRESS | Journal Volume: | 19 | Journal Issue: | 1 | Source: | JOURNAL OF WORLD ENERGY LAW & BUSINESS | Abstract: | The placement of offshore energy production units and structures (such as pipelines) will invariably come within the scope of any prevailing marine spatial planning (MSP) regime. There is increasing reliance on AI to ensure precision in placement. The data generated in many instances would be adopted by the authorities in implementing any applicable marine spatial plan. However, where there are many competing socio-economic and legal interests in the marine space, the use of AI by offshore energy corporates might well produce bias, whether intentional or not. This work maps out the risks of bias in this offshore energy and MSP context. It asks whether a liability system scheme like the EU AI Law could work. It concludes with thoughts on how, from a legal and regulatory perspective, spatial data sharing and AI used in an MSP context for offshore energy could be improved. |
URI: | http://scholars.ntou.edu.tw/handle/123456789/26556 | DOI: | 10.1093/jwelb/jwaf029 |
| Appears in Collections: | 海洋法律研究所 |
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