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In the early 1800s, philosopher Henri Saint-Simon, the ideological father of Technocracy, wrote, “A scientist, my dear friends, is a man who foresees; it is because science provides the means to predict that it is useful, and the scientists are superior to all other men.” All predictive science is based on this. Today, the military and intel agencies are leading the charge. ⁃ Patrick Wood, Editor.
The CDC’s Center for Forecasting and Outbreak Analytics (CFA) has partnered with the CIA-linked Palantir to cement the public-private model of invasive surveillance in “public health,” all while pushing the U.S. national security state and Silicon Valley even closer together.
The Pentagon and Silicon Valley are in the midst of cultivating an even closer relationship as the Department of Defense (DoD) and Big Tech companies seek to jointly transform the American healthcare system into one that is “artificial intelligence (AI)-driven.” The alleged advantages of such a system, espoused by the Army itself, Big Tech and Pharma executives as well as intelligence officers, would be unleashed by the rapidly developing power of so-called “predictive medicine,” or “a branch of medicine that aims to identify patients at risk of developing a disease, thereby enabling either prevention or early treatment of that disease.”
This will apparently be achieved via mass interagency data sharing between the DoD, the Department of Health and Human Services (HHS) and the private sector. In other words, the military and intelligence communities, as well as the public and private sector elements of the US healthcare system, are working closely with Big Tech to “predict” diseases and treat them before they occur (and even before symptoms are felt) for the purported purpose of improving civilian and military healthcare.
This cross-sector team plans to deliver this transformation of the healthcare system by first utilizing and sharing the DoD’s healthcare dataset, which is the most “comprehensive…in the world.” It seems, however, based on the programs that already utilize this predictive approach and the necessity for “machine learning” in the development of AI technology, that this partnership would also massively expand the breadth of this healthcare dataset through an array of technologies, methods and sources.
Yet, if the actors and institutions involved in lobbying for and implementing this system indicate anything, it appears that another—if not primary—purpose of this push towards a predictive AI-healthcare infrastructure is the resurrection of a Defense Advanced Research Projects Agency (DARPA)-managed and Central Intelligence Agency (CIA)-supported program that Congress officially “shelved” decades ago. That program, Total Information Awareness (TIA), was a post 9/11 “pre-crime” operation which sought to use mass surveillance to stop terrorists before they committed any crimes through collaborative data mining efforts between the public and private sector.
While the “pre-crime” aspect of TIA is the best known component of the program, it also included a component that sought to use public and private health and financial data to “predict” bioterror events and pandemics before they emerge. This was TIA’s “Bio-Surveillance” program, which aimed to develop “necessary information technologies and a resulting prototype capable of detecting the covert release of a biological pathogen automatically, and significantly earlier than traditional approaches.” Its architects argued it would achieve this by “monitoring non-traditional data sources” including “pre-diagnostic medical data” and “behavioral indicators.” While ostensibly created to thwart “bioterror” events, the program also sought to create algorithms for identifying “normal” disease outbreaks, essentially seeking to automate the early detection of either biological attacks or natural pathogen outbreaks, ranging from pandemics to presumably other, less severe disease events.
Bio-Surveillance graph from TIA
As previously reported by Unlimited Hangout, after TIA was terminated by Congress, it largely survived by privatizing its projects into the company known as Palantir, founded by Paypal co-founder Peter Thiel and some of his associates from his time at Stanford University. Notably, the initial software used to create Palantir’s first product was Paypal’s anti-fraud algorithm. While Palantir, for most of its history, has not overtly sought to resurrect the TIA Bio-surveillance program, that has now changed in the wake of the Covid-19 crisis.
In late 2022, Palantir announced that it and the Centers for Disease Control and Prevention (CDC) would continue their ongoing work to “plan, manage and respond to future outbreaks and public health incidents” by streamlining its existing biosurveillance programs “into a singular, efficient vehicle” to support the CDC’s “Common Operating Picture.” This “Common Operating Picture” aims to secure “strong collaboration across the federal government, jurisdictional health departments, private sector entities, and other key health partners.”
The CDC and Palantir publicized this partnership just months after the CDC announced the creation of the its Center for Forecasting and Outbreak Analytics (CFA). This office now plans to expand biosurveillance infrastructure via public-private partnerships across the country to ensure that local communities constantly supply federal agencies with a steady stream of bio-data to develop AI-generated pandemic “forecasts,” or viral outbreak predictions, that will inform pandemic policy measures during pandemics and before they even occur, theoretically before even a single person dies of a particular contagion.
On the surface level, such a mission might sound as though it would serve public health; if government and private institutions can collaborate to prevent pandemics before they happen, well then, why not? Yet, again, the origins of Palantir demonstrate that these “healthcare” surveillance policy measures actually work completely in tandem with the deeper, aforementioned “pre-crime” national security goal of TIA, which powerful forces have been slowly implementing for decades. The ultimate goal it seems, is to usher in a new, even more invasive surveillance paradigm where both the external environment and the public’s internal environment (i.e. our bodies) are monitored for “errant” signals.
Palantir’s founder and largest shareholder, Peter Thiel, incorporated the company in the immediate aftermath of Total Information Awareness’s (TIA) shut down—which resulted from prominent media and political criticism—with significant funding from the CIA’s venture capital arm, In-Q-Tel, as well as direct guidance from the CIA on its product development. As Unlimited Hangout detailed in its investigation into Donald Trump’s 2024 running-mate J.D. Vance and his rise to MAGA stardom, Thiel and Palantir co-founder Alex Karp met with the head of TIA at DARPA, John Poindexter, shortly after Palantir’s incorporation.
The middleman between the tech entrepreneurs and Poindexter was Poindexter’s old pal and key architect of the Iraq War, Richard Perle, who called the TIA-head to tell him that he wanted him to meet “a couple of Silicon Valley entrepreneurs who were starting a software company.” Poindexter, according to a report in New York Magazine, “was precisely the person” with whom Thiel and Karp wanted to meet, mainly because “their new company was similar in ambition to what Poindexter had tried to create at the Pentagon [that is, TIA], and they wanted to pick the brain of the man now widely viewed as the godfather of modern surveillance.” Since then, Palantir has been implementing the “pre-crime” initiatives of TIA under the cover of the “free market,” enabled by its position as a private company.
This story, along with the CIA’s intimate collaboration in developing Palantir’s early software, the CIA’s unique status as Palantir’s only client for its first several years as a company and Palantir co-founders’ statements about the company’s original intent (e.g. Alex Karp – CIA analysts were always the intended clients of Palantir), demonstrate that the company was founded to privatize the TIA programs in collaboration with the military and intelligence communities to which Palantir is a major contractor. Notably, TIA’s survival was actually enabled by its alleged killer, the US Congress, as lawmakers included a classified annex that preserved funding for TIA’s programs in the same bill that ostensibly “killed” the operation.
Yet while it appears that the national security apparatus plans to use the coming AI healthcare system for “pre-crime” and mass surveillance of American citizens, this “predictive” approach to healthcare will also inform significant policy shifts for the next pandemic. Specifically, the next pandemic will likely utilize the currently expanding biosurveillance infrastructure and AI disease forecasting software to develop “targeted” policy measures for specific communities and potentially individuals during future pandemics.
While Palantir stands at the forefront of this technocratic transformation of healthcare, the national security apparatus in collaboration with Big Healthcare and Big Tech at large are all contributing to weaving this lesser known “bioterror” component of TIA into private business schemes that covertly carry on the duties of the officially “shelved” program. This network of institutions consistently and conveniently omits the origins of its predictive biosurveillance healthcare approach — but the special interests tied to their efforts, as well as the striking similarities between their alleged public health solutions, and the decades-old biowarfare responses / surveillance programs of the Pentagon, reveal the ulterior motive of this public-private collaboration.
This investigation will examine how the CDC’s Center for Forecasting and Outbreak Analytics (CFA) signifies a major step towards the “AI-driven healthcare system,” how Palantir’s management of the program’s data strongly suggests that this partnership is the latest multi-sector implementation of the “pre-crime” agenda of TIA and what frightening possibilities the “AI-driven healthcare system” could enable in a future pandemic and healthcare in general. This revolutionary system ultimately pushes society further into the sights of a digital panopticon that seeks surveillance and control of all that the makes up the average citizen—from outside their bodies, to within.
What Does the CDC Center for Forecasting and Outbreak Analytics (CFA) do?
The CFA demonstrates that the AI healthcare and pandemic prevention industry is being materially (and quietly) implemented into public life in a significant way. Its policy measures massively expand invasive surveillance measures and, through sweeping biodata collection, will transform the way that public health policy policy is developed and enacted during pandemics and healthcare in general.
Based on the CFA and related developments in the public sector and amongst government contractors, American public health agencies are poised to utilize the mass collection of biosurveillance data to fuel: 1) targeted vaccine development and distribution of pathogens with “pandemic potential,” 2) curated policy and targeted lockdowns of specific communities and/or groups based on their “risk levels” and 3) medical prioritization of patients based on their AI-determined “needs” and AI hospital management.
The CFA’s mission is to “advance U.S. forecasting, outbreak analytics, and surveillance capacities related to disease outbreaks, epidemics, and pandemics to support public health response and preparedness.” It plans to achieve this mission through multiple methods, but the data aggregation accumulated via Palantir programs within the CDC’s “Common Operating Picture”, and the way this data will manifest into policy, bind all these strategies together.
CFA’s mission and vision statements, and four supporting goals
I. Your Data For All
Crucial to this effort is the CFA’s goal (arguably its primary goal) of creating a concrete digital infrastructure that will provide multiple sectors and jurisdictions of government with the ability to share, access and implement the biodata they collect. One duty assigned to the program’s Office of Director summarizes this strategy succinctly; it is tasked with guiding “the facilitation and coordination” of all biosurveillance activities, ranging from disease modeling to viral forecasting and the data extraction and collection necessary to support these activities—from the local to federal levels of government and healthcare entities. In simpler terms, the Office of Director will ensure that the institutions that make up the CFA (and partner with it) see that the program’s intention to create multi-sector, interagency, collaborative data sharing infrastructure is carried out.
Several other codified aims of the program make clear how crucial this element of mass data sharing is to the overall mission of CFA. For example, the Inform Division is tasked with sharing “timely, actionable” data with the federal government, local leaders, the public and even international leaders. It also coordinates real-time surveillance activities between CDC experts and US government agencies, and maintains “liaison” with CDC officials and staff, other US government departments and private sector partners.
Similarly, the Predict Division will develop “scientific collaborations to harmonize analytic approaches and develop tools,” which likely implies the importance of interoperability in collecting/sharing this data. Interoperability, or “harmonized” analytical approaches and tools, is a necessary component of creating the multi-sector collaborative data mining infrastructure that the CFA aims to cultivate. Through making data and its collection tools interoperable, different vendors and institutions gain the ability to seamlessly work together by enabling the exchange of data between different sources, whether they be military, hospitals, academic centers or anything else. In essence, interoperability centralizes a seemingly decentralized network of different vendors and institutions, all of whom are collecting and analyzing data plucked from various sources.
Likewise, the Office of the Director is tasked with maintaining “strategic relationships with academic, private sector, and interagency partners” as well as procuring “opportunities with industry partners.” And finally, the Innovate Branch will collaborate “with academic, private sector, and interagency partners” as part of its goal to create “products, tools and enterprise enhancements” in order to make pandemic data analysis “flexible, fast, and scalable for CFA customers including federal, state, tribal, local, or territorial authorities” (emphasis added). In other words, the Innovate Branch will engage in cross-sector collaboration for the direct purpose of creating and improving technology that makes mass data sharing more vast, rapid and simple for both government authorities and “customers.”
In fact, in 2023 this goal materialized with the creation of the CFA’s Insight Net. It contains more than “100 total network participants” and spans “24 states and 35 public health departments.” Its vast network has expanded the CFA’s reach to influence “many critical public health decisions” made at the state and local levels, and it boasts that its network is integrated and unifying, “leveraging connections with state, local, private, public, and academic partners to create a consortium of collaborators.” This collaboration that Insight Net facilitates between the public and private sector manifests in the lives of citizens through the policy it informs—a central part of the program.
A static image that shows all of Insight Net’s partner
II. When Data Becomes Policy
The CFA plans to utilize this vast array of data to inform real-time policy decisions related to future pandemic planning and response. Multiple divisions within the CFA will contribute to this strategy of creating policy through the implementation of data into policy decision making.
The Office of the Director will oversee the general direction of this aim, as it defines “goals and objectives for policy formation, scientific oversight, and guidance in program planning and development…” The Office of Policy and Communications will then presumably work to implement these objectives into concrete policies and regulations, as it is responsible for “review[ing], coordinat[ing], and prepar[ing] legislation, briefing documents, Congressional testimony, and other legislative matters” as well as coordinating the “development, review, and approval of federal regulations,” presumably surrounding pandemic policy, surveillance, data and response efforts.
The Predict Division will play a crucial role in informing the specifics of these policies, as it generates “forecasts and analyses to support outbreak preparedness and response efforts”, and collaborates with partners from the local to federal to international level “on performing analytics to support decision-making.” It will also perform tabletop simulations to “match policies and resources with [its AI-generated] forecasts,” leaving the fate of communities, relating to their freedom as well as access to medical care, in the hands of algorithms and datasets.
Illustration of CFA’s partners working to detect and control an infectious disease outbreak
Importantly, the CFA will not only utilize this data in long-term preparation or research, but in critical, high-pressure moments. Specifically, the Predict Division’s data sets and models will be used “to address questions that arise with short latency.”
During outbreaks, such questions that may arise with “short latency” would likely relate to containment efforts, and thus, lockdown policy. The Analytics Response Branch of the CFA, which uses its “analytical tools” to aid “decision making for key partners” both during a potential or ongoing outbreak, is also responsible for analyzing “disease spread through existing data sources to identify key populations/settings at highest risk” and correspondingly providing “essential information to key partners in decisions surrounding community migration” (emphasis added).
This sentence, though somewhat vague, suggests that AI-informed policy will subject certain communities/individuals to an extraordinary level of intrusion. Specifically, beyond more general, overarching pandemic policy, it appears that AI-generated forecasts and “risk levels” will dictate policy on the local, or perhaps even individual, level—directly controlling the movement, or “migration,” of communities.
Indeed, the CFA’s cooperative agreement states that the ability to apply data-driven, “mathematical” methods to tackle health equity problems in the face of disease outbreaks is “of great interest to the CFA.” Key to this objective is the collection of data “on the social determinants of health” to utilize in disease forecasting. These “social determinants” include “geography (rural/urban), household crowding, employment status, occupation, income, and mobility/access to transportation,” as well as race, so long as race is not recognized as an “independent exposure variable” but instead is seen as a “proxy” for other social determinants.
While on the surface level, this “targeted” approach may seem to provide a solution to the previously implemented universal pandemic policy, the digitization of lockdowns still raises the potential to seriously threaten individual and communal autonomy—only this time, under the auspices of “objective” data, accumulated and interpreted by AI technology.
Who’s Behind the AI-Healthcare Push?
The tentacles of the biosecurity apparatus spread across multiple sectors of government and business, transcending the heavily blurred and essentially illusory lines between the public and private sector and Big Tech and Big Pharma. Military officials, tech operatives and global public health institutions all play a significant role in the lobbying for and implementation of this emerging healthcare industry.
I. The Military
While the idea of developing preemptive vaccines to treat novel infectious pathogens dates back to the Reagan-era, these ideas initially focused on developing preemptive vaccines for diseases that emerged in a human population via a bioweapon, making the strategy rooted in national security as opposed to traditional disease response. Yet in the modern era, this militarized approach to public health has become the dominant ideology in establishment public health sectors—demonstrated by the core ideology that the CFA is built on.
The CFA’s Office of the Director ensures that “the CFA strategy is executed by the Predict Division and aligned with overall CDC goals” (emphasis added). While the vagueness of this passage omits the exact intentions of the referenced “CDC goals”—the CDC’s national biosurveillance strategy for human health, however, sheds light on the hidden agenda here.
The strategy is cemented in “U.S. laws and Presidential Directives, including Homeland Security Presidential Directive-21 (HSPD-21), ‘Public Health and Medical Preparedness.’” HSPD-21 is a Bush-era Department of Homeland Security directive made to “guide…efforts to defend a bioterrorist attack” that are also “applicable to a broad array of natural and manmade public health and medical challenges.” The directive aimed to predict disease outbreaks—natural or bioweapon-induced—via “early warning” and “early detection” of “health events.” Strikingly similar to the TIA “Bio-Surveillance” objectives, these values appear to have been placed in good hands at the CFA, as the Center’s director, Dylan George, previously served as vice-president of In-Q-Tel, the venture capital arm of the CIA.
A wargame at the US Naval War College in 1958, using the newly installed Navy Electronic Warfare Simulator
A recent trip that US Army officials made to Silicon Valley illustrates how the ideology behind this strategy has manifested through the relationship between Silicon Valley, academia and the Pentagon. In this “pivotal visit” to the San Francisco Bay Area in Aug. 2024, the US Army’s surgeon general, Mary K. Izaguirre, met with scientists at Stanford University and Google to further “the Army’s efforts to integrate cutting-edge technology and build stronger ties with civilian sectors.” Izaguirre rendezvoused with Civilian Aides to the Secretary of the Army (CASAs) and Army Reserve Ambassadors to discuss “their efforts to bridge the gap between the Army and the civilian community.”
When she met with Stanford scientists, who have “a long history of collaboration with the military, particularly through research initiatives that contribute to national defense and public health,” the scientists briefed her on advancements made in AI allegedly capable of “[revolutionizing] emergency medicine.” This tech was part of Stanford’s, and presumably the military’s and Big Tech’s, “broader mission to integrate AI into various aspects of health care…”
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