持续性
可持续发展
矿业
大数据
业务
风险分析(工程)
计算机科学
工程类
政治学
生态学
采矿工程
生物
操作系统
法学
作者
Long Chen,Yuting Xie,Yutong Wang,Shirong Ge,Fei‐Yue Wang
标识
DOI:10.1109/jas.2023.124182
摘要
THE mining sector historically drove the global economy but at the expense of severe environmental and health repercussions, posing sustainability challenges [1]–[3]. Recent advancements on artificial intelligence (AI) are revolutionizing mining through robotic and data-driven innovations [4]–[7]. While AI offers mining industry advantages, it is crucial to acknowledge the potential risks associated with its widespread use. Over-reliance on AI may lead to a loss of human control over mining operations in the future, resulting in unpredictable consequences. Furthermore, the design and training of AI systems can introduce biases and unfairness, exacerbating social and environmental inequalities [3]. Unchecked technological progress may undermine achievement of the Sustainable Development Goals (SDGs) in the 2030 Agenda for Sustainable Development [8].
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