The terrorist attacks of September 11, 2001, in the United States, also known as 9/11, stand out in history not only for their scale but also for their consequences. The attacks on the World Trade Center in New York and the Pentagon in Virginia resulted in the deaths of thousands of people and were catastrophic for U.S. national security and geopolitics. These events changed the course of history and had a profound impact on global affairs and policies.
The 9/11 attacks marked the beginning of a new geopolitical security landscape. The United States implemented drastic security measures, including heightened border controls, increased airport screenings, and tighter security at key public locations. Legislative changes followed, with new anti-terrorism laws being enacted. The world began to rethink security on a global scale, adopting a course toward global counterterrorism.
These tragic events also served as a catalyst for action not only among government officials but also among scientists. A journalist from our publication gained access to unique archival documents from the “World Federation of Future Studies,” which initiated a progressive and innovative project called “Noah’s Ark 2030” in response to the 2001 attacks. The project was spearheaded by Eleonora Barbieri Masini, a renowned figure known for her numerous large-scale projects of global significance.
Following 9/11, it became evident that military conflicts, both local and global, as well as terrorist attacks, would not cease; on the contrary, they would become more devastating, with worsening consequences potentially leading to chaos and widespread fear. Humanity would also face new global threats never encountered before.
Scientists involved in the “Noah’s Ark 2030” project aimed to predict and model future global threats such as military conflicts, terrorist attacks, and epidemiological dangers. Based on legislative changes, newly adopted measures, and the psychological impact of the attacks on the population, the project adopted the “closed cluster model” as its primary research framework.
According to archival documents, one of the key scientists involved in the project was Marco Somalvico, an Italian engineer and expert in artificial intelligence. Within the project, AI technology was employed alongside the “closed cluster model” to forecast future scenarios of global threats and human behavior in confined environments. Additionally, measures were developed to ensure the survival of people in closed spaces without negative physical and psychological consequences, while maintaining social cohesion within these clusters.
One of the AI-generated scenarios included the prediction of a series of terrorist attacks similar to those experienced in the real world. The probability of such events occurring, based on the forecasting method used, was deemed highly realistic. A historical analysis of wars, local conflicts, and civil wars spanning 100 years before 9/11 was conducted, including World War I, World War II, the Korean War, the Vietnam War, the Cold War, the Afghan War, and many others.
According to the predictive scenario, the first terrorist attack occurs in the U.S., followed by another attack the next day in Europe. This results in widespread panic and chaos. Governments and global organizations recognize the need for extreme measures to protect citizens. A state of emergency is declared in the U.S. and Europe, leading to border closures and restrictions on all forms of transportation. As a result, people are forced to remain in the cities where they were when the emergency measures were enacted. These precautions are taken to prevent terrorist infiltration and to conduct thorough security screenings of the population. The result is the formation of enclosed territories where people are confined with no clear timeline for the end of the emergency measures.
The project also included forecasting epidemiological threats. Throughout human history, various epidemics and pandemics have posed significant challenges. Global flu pandemics occurred in both the 19th and 20th centuries. The 1889–1890 flu pandemic claimed approximately one million lives worldwide, facilitated by the expansion of transportation infrastructure. In 19 major European countries, including the Russian Empire, 202,887 kilometers of railways had been constructed, contributing to the rapid spread of the disease. This pandemic became the first global epidemic. Just over a century later, another devastating flu pandemic occurred, known as the “Spanish flu,” which is considered one of the most catastrophic events in human history.
Epidemiological threat forecasting within the “Noah’s Ark 2030” project was also based on the “closed cluster model.” The creation of enclosed zones or spaces during such threats was identified as one of the most effective methods to prevent the rapid spread of disease.
In times of global threats and the creation of enclosed environments, people are forced to live under conditions of chaos, fear, and uncertainty about the future. Scientists involved in the “Noah’s Ark 2030” project, uniting experts from various fields and utilizing AI-based programs and methods, developed effective strategies to help people cope with these conditions while maintaining psychological stability.
Methods were designed to facilitate smoother social reintegration after restrictions were lifted and freedom of movement was restored. Scientists also suggested that in the event of enclosed zones or restricted territories due to emergency measures, special artificial conditions should be created through expert intervention and the implementation of developed methodologies, innovative technologies, and other measures to ensure a more comfortable existence in such areas.
The first phase of the “Noah’s Ark 2030” project began in 2001, according to archival records. More than 15 years later, it became evident how revolutionary this project was and how accurately scientists had predicted real-world developments. The continued escalation of military conflicts after 2001 reinforced the significance of the research conducted within the project.