Mining of the future: New technologies and artificial intelligence, human rights

AI is a key element in improving mining efficiency. Thanks to its ability to analyze large volumes of data—from the initial exploration phase to final mineral processing—intelligent systems can identify complex patterns and predict outcomes with unprecedented accuracy. This allows mining companies to make more informed decisions, optimize transportation routes, adjust production in real time, and ultimately significantly reduce operating costs. Mining becomes more agile and adaptive, responding more effectively to changing market and subsurface conditions.

One of the greatest benefits of AI is its application in predictive maintenance. Sensors installed on mining equipment constantly collect data, which is then processed by AI algorithms to predict potential failures before they occur. This allows for proactive maintenance scheduling, avoiding costly unplanned downtime and extending the lifespan of machinery. Furthermore, AI is the brain behind autonomous operations. Trucks, drills, and other equipment can operate independently, navigating complex terrain and performing critical tasks without direct human intervention. This not only increases operational efficiency but also dramatically reduces risks to workers by removing them from hazardous environments.

Worker safety is a key priority in mining, and new technologies are making revolutionary contributions in this field. Advanced sensors, drones, and AI-powered machine vision systems can constantly monitor conditions in real time, detecting hazards such as ground instability, the presence of toxic gases, or proximity to hazardous areas. These systems can alert workers instantly, enabling evacuation or the implementation of preventive measures. The automation of dangerous and repetitive tasks also reduces human exposure to accidents, creating a much safer and healthier work environment.

The mining industry of the future is actively seeking to minimize its ecological footprint, and AI is a vital tool in this effort. By optimizing operational processes, AI helps reduce energy and water consumption, two critical resources in mining. Algorithms can manage the use of explosives for more efficient fragmentation, reducing waste. Furthermore, AI facilitates real-time monitoring of key environmental indicators, such as water quality in tailings, atmospheric emissions, and the stability of tailings dams. This enables a rapid response to any deviation and contributes to more responsible management of environmental impacts, driving mining toward more sustainable and planet-friendly practices.

One of the most pressing challenges is labor displacement. The automation of critical tasks, which previously relied on large numbers of workers, can lead to massive job losses in mining communities. This not only affects the local economy but also the social fabric and people's dignity. Therefore, it is essential that companies and governments invest heavily in retraining and vocational training programs. These programs must prepare workers for roles that require new skills, such as supervising automated systems, analyzing data, or maintaining robots. The transition must be fair and ensure that no one is left behind.

The mining industry of the future will generate and use massive volumes of data, much of which will be personal, collected through sensors, monitoring devices, and AI systems. This includes information on workers' location, performance, health, and even behavioral patterns. The privacy and protection of this data therefore become a central concern. It is vital to establish robust legal and ethical frameworks that regulate the collection, storage, and use of this information. Workers must have control over their data and know how it is used, avoiding any form of excessive surveillance or discrimination based on AI-generated profiles.

AI algorithms learn from the data they are trained with. If this data contains historical or systemic biases (for example, in hiring or performance evaluation), the algorithm will not only replicate those biases, but could amplify them. This could lead to discriminatory practices in task assignments, promotion opportunities, or even termination decisions. Ensuring that AI systems are fair, transparent, and free of bias is an ethical imperative. Regular audits and conscious design are needed to prevent the technology from perpetuating or exacerbating existing inequalities.

As AI makes more autonomous decisions in mining, a crucial question arises: who is responsible when something goes wrong? While automated systems can improve safety and efficiency, the consequences of an algorithmic error or system failure can be devastating. It is essential that, no matter how advanced the AI, there is always effective human oversight and a clear chain of responsibility. AI decisions must be understandable (explainable) to humans, allowing for clear accountability and the possibility of intervention when necessary. Technological autonomy should not mean an abdication of human responsibility.

The expansion of mining, even with advanced technologies, often entails the occupation of lands and the use of resources that are vital to local communities and Indigenous peoples. Despite technological advances, concerns persist regarding access to water, environmental pollution, and the disruption of traditional livelihoods. The right to free, prior, and informed consent (FPIC) of these communities is essential before initiating any project. Technology should be a means to mitigate negative impacts and promote sustainable development in consultation with communities, not to ignore their rights and needs.

Finally, there is a risk that the benefits of highly technological mining will not be distributed equitably. Large corporations with vast resources could monopolize these technologies, leaving behind smaller companies, vulnerable communities, or developing countries with less investment capacity. This could widen economic and social gaps, concentrating power and wealth in a few hands. It is crucial to foster policies that promote technology transfer, local capacity development, and more equitable access to these innovations to ensure that the mining industry of the future benefits a broader spectrum of society.

In a world where AI algorithms make increasingly complex decisions, from process optimization to safety management, transparency and explainability are critical. This means that AI systems cannot be "black boxes." We must be able to understand how they work, what data they use for their decisions, and why they reach certain conclusions. This clarity allows us to assess their fairness, detect potential biases, and ensure that their operations align with ethical values and human rights. If an AI decision affects a worker or community, there must be a comprehensible explanation and a mechanism for challenging it.

Safety has always been a priority in mining, but the introduction of AI and robotics redefines its scope. It is not only about the physical safety of workers and equipment, but also the cybersecurity of autonomous systems and environmental protection against technological failures. It is imperative to implement rigorous risk assessment procedures to identify and mitigate potential harm, both human and ecological. This includes creating emergency protocols for automated systems and investing in resilient infrastructure that can withstand cyberattacks or unexpected failures, thus protecting people and the environment.

With the increasing autonomy of machines, a critical question arises: who is responsible when an AI system makes a mistake or causes harm? It is vital to establish a clear definition of legal and ethical responsibilities at every stage of automated mining operations. This involves outlining the obligations of software developers, equipment manufacturers, mine operators, and human supervisors. Responsibility cannot be diluted in technological complexity; it must be attributable to entities or individuals, thus ensuring accountability and the possibility of redress in the event of incidents.

Ultimately, technology must serve humanity, not the other way around. A human-centered approach to future mining means that the design and implementation of new technologies must prioritize the well-being of workers, local communities, and the environment. This involves ensuring that automation frees humans from dangerous and monotonous tasks, allowing them to develop new skills and roles with greater added value. It also means actively involving communities in decisions that affect their lives and resources, and ensuring that the economic benefits of mining are shared fairly and equitably. Innovation must go hand in hand with empathy and social justice.