Adaptive stewardship of understanding: Artificial intelligence and intergenerational governance in mining

Mining stewardship has traditionally focused on the governance of physical assets, operational performance, environmental impacts, and organizational decision-making. While these responsibilities remain essential, they assume that the understanding supporting stewardship is comparatively stable. In reality, understanding continually evolves as new observations emerge, assumptions are revised, stakeholders change, institutions adapt, and stewardship extends across increasingly long temporal horizons. Artificial intelligence further transforms this process by participating in how observations are integrated, interpretations are developed, assumptions are reinforced or challenged, and institutional knowledge is preserved and communicated. Stewardship must therefore address not only what decisions are made, but also how understanding itself is created, maintained, questioned, and renewed. This paper proposes adaptive stewardship as a framework for governing an evolving ecology of understanding throughout the mine life cycle and beyond closure. The framework distinguishes understanding from observation, examines the lifecycle of assumptions, introduces the concepts of time windows of understanding and observation boundaries, and argues that governance must preserve the conditions under which understanding can continue to improve across generations. Within this ecology, artificial intelligence is treated not as an autonomous decision-maker but as an evolving participant whose value depends upon transparent governance that maintains visibility of assumptions, uncertainty, evidence, and human judgment. The paper concludes that the long-term objective of stewardship is not to preserve today's knowledge, but to preserve society's continuing capacity to develop better understanding as mining systems, environmental conditions, technologies, institutions, and societal expectations evolve.