The Potential for AI in the Extractive Industries to Promote Multi-objective Optimization2022-11-09T13:46:50+01:00

The Potential for AI in the Extractive Industries to Promote Multi-objective Optimization

Artificial intelligence (AI) is increasing in enhancing mining sector economics: boosting productivity, optimizing operational costs, and maximizing profitability. However, the potential for AI in promoting “multi-objective optimization”, i.e., tackling multiple sustainability goals, has been overlooked. To formulate such “multi-objective” mining strategies and successfully implement them, large arrays of diverse data must be collected, processed, and analyzed to optimize the chosen pathway. The current technological tools do not capture a complete picture in terms of relevant data. Moreover, practical and evidence-based guidance is needed to ensure that AI solutions and practices are adopted by local communities and adapted to their needs and
prosperity. The proposed team is uniquely positioned to investigate and suggest solutions for employing AI for sustainable mining. Combining expertise in (1) the responsible use of AI and (2) data, knowledge, and modelling approaches to the socio-economic and environmental impacts of resource development, the project will develop guidelines and suggest practices for the responsible use of AI-enabled technologies to improve the effectiveness and sustainability of supply chains for raw materials.

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Principle Investigators

Svetlana Ikonnikova
Svetlana IkonnikovaTUM School of Management
Walter Timo de Vries
Walter Timo de VriesTUM School of Engineering
Caitlin Corrigan
Caitlin CorriganTUM School of Social Science and Technology

External Partners

Kwame Nkrumah University of Science and Technology (KNUST)Responsible Artificial Intelligence Lab (RAIL)
The University of Texas at AustinCenter for Sustainable Water Resources at the Bureau of Economic Geology (BEG)
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