Since 2006 the U.S. Department of Defense and Homeland Security have been working on a decidedly Orwellian computer simulation called the Sentient World Simulation (SWS). This virtual world, a kind of digital twin, is designed to mirror the real world with the aim of predicting various hypothetical scenarios in the future.
The SWS is comprehensive in its virtual model of human society, encompassing everything from political dynamics and military operations to complex global events and their potential outcomes. For instance, the system could predict the consequences of disrupting a nation's water supply or simulating a military coup in a given country with near perfect accuracy.
Unlike traditional simulations of the bygone past, the SWS doesn't just model static scenarios; it leverages AI dynamically to real-world events as they unfold, incorporating new data to continually refine its eerie, soothsaying predictions.
Where does the data come from?
Burgeoning technology in the area of knowledge discovery has matured so that Web crawlers and spiders are now used in research and industry. Applying this technology to news portals, blogs, and other internet sources enables large amounts of data to be gathered and processed in a short amount of time. By considering all available data, automated data mining provides an unbiased means of incorporating data originating from multiple sources, and therefore, data from multiple perspectives. Additionally, interesting outliers are discovered through text, video, and transaction analytics. Believability and reliability metrics are applied to weight the influence of data from different sources depending on the type of source, experience with data from the source, and the type of data. The believability and reliability are then taken into account when incorporating the data into the SWS synthetic world. The discovery technology is coupled with a semantic engine that extracts semantics from the data. The semantics are used to prepare the gathered data for use by the simulations and to relate the data to knowledge already in the synthetic world.
The official documentation for the SWS also reveals goals to create an accurate virtual avatar for every individual on the globe. These digital doppelgangers are currently being sourced from data collected in both private, internal government records and public internet social media sources.
SWS AI algorithms draw on the psychological theories of Martin Seligman. Seligman is known for his work on learned helplessness, a concept developed through controversial animal experiments in the 1960s:
“Learned Helplessness is a phenomenon where repeated exposure to uncontrollable stressors results in people failinaaaag to use any methods to control their response to those stressors that are at their disposal in the future. Essentially, those experiencing learned helplessness are said to learn that they lack behavioral control over the events in their environment, which, in turn, undermines their motivation to make changes or attempt to alter situations.”
Although its unclear if SWS or a successor program is active today, the reason we may see so much fake news today is to try and keep people in a state of learned helplessness. The constant barrage of uncertainty, violence, and instability makes you feel powerless: a society that believes itself to be helpless in the face of power is considerably more easy to monitor and control.
Thankfully, the work of German sociologist Niklas Luhmann offers a potent counterpoint to this artifically induced feeling of learned helplessness, designed to lull the masses into perfect obedience of their technocratic overlords.
Luhmann posited that human behavior emerges from a intricate web of influences, creating a level of complexity that defies precise or easy prediction. In his view, our actions are shaped by countless interconnected factors beyond psychology, including personal experiences, cultural norms, immediate circumstances, and subconscious impulses. This multilayered complexity, Luhmann argued, makes it fundamentally impossible to forecast human behavior with any absolute accuracy. [1]
Luhmann's work reminds us to be cautious and critical about the predictive power of technology like the SWS. The future, shaped by the collective actions of billions of complex individuals, may always retain an element of fundamental uncertainty—even chaos—that even the most advanced simulations cannot fully overcome.
The ability to simulate and manipulate complex societal systems combined with Palantir’s predictive policing tools will continue to redefine social engineering and naturally escalate the coming precrime apparatus on an unprecedented scale. The need and legal requirement of technological tools that defend your privacy privacy from the coming pre-crime apparatus becomes more pressing with each day.
Avoiding A Neo-Feudal Society
Social media platforms track public sentiment and behavior. Mainstream smartphones log our movements and communications. IoT devices monitor our homes and habits. Financial systems record every transaction. Surveillance cameras watch our cities. Health records detail our well-being. E-commerce platforms know even our most intimate preferences.
The list goes on, painting a picture of a world where privacy seems increasingly elusive.
It's not far-fetched to speculate that larger tech companies, especially those with ties to institutional investors, might be more likely to participate in a system like SWS. Their vast user bases and diverse data collection points make them valuable potential contributors, willingly or under pressure.
But what alternatives do we have? One intriguing possibility is the use of local, small software companies. Ideally these companies would have reduced data consolidation and increased oversight and community accountability.
The concept of neo-feudalism might provide a sobering framework for understanding the sociological impact of technology like the SWS and its attempts to induce artificial learned helplessness in the global population. In our currently dystopian world, Neo-feudalism is a simple evolution of medieval feudalism, particularly in terms of power distribution and social stratification.
In this context, large corporations, tech giants, and powerful government agencies can be seen as the new "lords," wielding significant control over data, resources, and decision-making processes. To further extend the metaphor, that would make us common people the lowly peasants.
Just as medieval lords had access to information and resources that peasants lacked, entities with access to SWS-like technologies possess a significant advantage in predicting and manipulating society at large. This furthers the already stark divide between those who can harness the power of big data analytics and those who cannot.
If you’re not interested in the political elite creating a perfect digital doppelganger of you trained on your private data, we recommend checking out Above Book and Above Phone. These powerful, degoogled open source tools make 0 connections to Big Tech and protect you from the following kinds of invasive tracking:
✦ App tracking
✦ Cellular attacks
✦ Internet Traffic surveillance
✦ Communications surveillance
The promise of technology should be to liberate and empower, not to control and stratify. Don’t be a peasant to the “lords” of Big Data.
Sources
[1] Niklas Luhmann, Introduction to Systems Theory, trans. Peter Gilgen (Cambridge, UK: Polity, 2013).
https://cointelegraph.com/news/us-govt-develops-a-matrix-like-world-simulating-the-virtual-you
AI Surveillance & Pre-Crime: On the Sentient World Simulation