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.

News & Updates

Principal Investigators

External Partners

Prof. Svetlana Ikonikova, TUM School of Management, The Center for Energy Markets and SEEDs Center

Univ.-Prof. Dr. Ir. Walter Timo de Vries, TUM School of Engineering and Design Centre of Land, Water, and Environmental Risk Management

External Partners

  • Kwame Nkrumah University of Science and Technology (KNUST) – Responsible Artificial Intelligence Lab (RAIL)
  • The University of Texas at Austin – Center for Sustainable Water Resources at the Bureau of Economic Geology (BEG)
Dr. Caitlin Corrigan

Caitlin Corrigan, TUM School of Social Science and Technology, Institute for Ethics in AI