Macro-Criminal Networks
Powerful computation today boosts our capacity to perceive and understand the world. The more data we process, analyze, and visualize, the more natural and social phenomena we discover and understand.
Computational capacities allow us processing and visualizing massive data produced by microscopes, telescopes, and satellites. As a result, today we perceive, understand, and forecast “new” natural objects and characteristics, from nano-bots to distant galaxies and climates.
In the same sense, processing massive social data reveals global trends. For instance, visualizing and analyzing massive judicial information with current computational tools reveal a whole new and complex social phenomenon: Macro-criminal networks.
Our brain only makes sense of social networks in which approximately 150 – 200 individuals participate. Known as the “Dunbar’s number,” this is an approximation of the social network’s size that we can interact with; it’s almost impossible for our brains to understand social networks articulated by several hundreds or thousands of individuals.
Therefore, macro-criminal networks are complex social structures that cannot be perceived or analyzed without computational power, algorithms, and the right concepts of social complexity.
Unfortunately, these global, resilient, and decentralized structures, characterized by messy hierarchies and various types of leaders, bring bad news: we, as a society, lack tools, legislation, and enforcement mechanisms to confront them.
Macro-criminal networks overwhelm most judicial and enforcement agents who still fight crime searching for “criminal organizations” with simple hierarchies, articulated by “full time” criminals, and commanded by a single boss. This classic idea of “organized crime” is outdated and doesn’t reflect the complexity of macro-criminal networks that are being discovered.
Since crime in most countries is analyzed and confronted through outdated legislation, methodologies, and concepts, these huge criminal networks are usually omitted. The outdated approach restricts judicial systems and enforcement agencies to observe a tiny part of crime.
Investigating and prosecuting crime today without the right concepts and without computational tools for processing, analyzing, and visualizing massive data, is like studying galaxies with 17th century telescopes and without computers. In this sense, the hardest challenge when confronting macro-criminal networks is not adopting powerful computers or applying deep learning but modifying that mindset of scholars, investigators, prosecutors and judges.
For instance, legislation focused on one victim and one victimizer, conducts to wrong analysis and insufficient enforcement of systemic crimes, such as massive corruption observed in Latin America and West Africa, human trafficking observed in Eastern Europe, and massive forced displacement observed in Central Africa. As a consequence, structures supporting those crimes worldwide are overlooked.
Crime in its various expression is always news. From corruption to terrorism and several types of trafficking activities, crime affects our way of life while hampering development in various countries. However, computational power today reveals the—bad—news of huge, resilient, and decentralized criminal macro-structures. Understanding this phenomenon and its related concepts and consequences, is critical for achieving global security in years to come. It is important to commit and allocate the right scientific, institutional, and economic resources to deal with this transnational phenomenon that we just recently understand, although it today underlies the evolution of various countries.
