Human-machine Collaboration in Mining: A Critical Review of Emerging Frontiers of Intelligence Systems in the Mining Industry
Abstract
Artificial Intelligence (AI) is driving significant transformations in numerous industries revolutionizing business processes, relationships, and engagements among individuals within organizations as well as with external service providers. These emerging smart technologies will also revolutionize the mining industry in significant ways. The future of AI in the mining industry will focus on autonomous equipment, drones and robots replacing humans in tasks performance. Mine automation is creating a new paradigm where technically savvy personnel are performing remote operations with improved workplace safety, health, and efficiencies. This study reviews the progress of mine automation, robotics, and other intelligent systems in the mining industry. We applied the technology, organization, and environment (TOE) framework to synthesize the various barriers associated with the implementation of these smart technologies in the various mining lifecycles. Using a preliminary literature review approach, we discuss enabling technologies facilitating human-machine collaboration along the mining life cycle, their impacts and synthesize the future of an industry where human and machine collaborate successfully to the benefit of humans. This review contributes to the best practices for managing change as an enabling factor to facilitate the smooth implementation of smart technologies in the mining industry.
Recommended Citation
R. Osei et al., "Human-machine Collaboration in Mining: A Critical Review of Emerging Frontiers of Intelligence Systems in the Mining Industry," Extractive Industries and Society, vol. 24, article no. 101746, Elsevier, Dec 2025.
The definitive version is available at https://doi.org/10.1016/j.exis.2025.101746
Department(s)
Mining Engineering
Keywords and Phrases
Artificial intelligence; Human–machine collaboration; Mining life cycle processes; Smart technologies
International Standard Serial Number (ISSN)
2214-7918; 2214-790X
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2025 Elsevier, All rights reserved.
Publication Date
01 Dec 2025
Comments
Centers for Disease Control and Prevention, Grant U60OH012685