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.
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.
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.
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.
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 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…”
From there, Izaguirre traveled to Google’s headquarters where she and the tech experts discussed how Google’s “AI, machine learning, and cloud computing capabilities” could assist the Army’s healthcare ambitions. She also thanked Google for helping veterans “find their footing” after their time in the military, acknowledging the role that the company’s “SkillBridge” program plays in aiding soldiers in their transitions “into civilian careers”—which provides a convenient funnel from the military into Silicon Valley for lucky servicemen. The article concluded by remarking that through its collaboration with “leaders in academia and technology, the Army aims to equip its soldiers with the best tools and support for the challenges ahead.” Notably Google also shares a $9 billion cloud computing contract, along with Amazon Web Services (AWS), Microsoft and Oracle, with the Pentagon for the military’s Joint Warfighting Cloud Capability system (JWCC).
This meeting, along with the ever-growing partnerships between Big Tech and the Pentagon, obviously do not occur in a vacuum, but instead represent a natural culmination of years-long industry plans to merge Silicon Valley data with military data. In March 2019, for example, co-authors Dr. Ryan Kappedal, a former intelligence officer whose job pedigree summarily includes — lead product manager for the Pentagon’s Defense Innovation Unit (DIU), data scientist at Johnson & Johnson, and currently a lead manager at Google — and Dr. Niels Olson, a US Navy Commander and the Laboratory Director at US Naval Hospital Guam, wrote an article for the Pentagon-funded neoconservative think tank, Center for New American Security (CNAS), titled “Predictive Medicine: Where the Pentagon and Silicon Valley Could Build a Bridge in Artificial Intelligence,” in which they fantasized about the merging of these industries that Kappedal hails from:
“[With] the Department of Veterans Affairs (VA) healthcare system, the federal government has the largest healthcare system in the world. In the era of machine learning, this translates to the most comprehensive healthcare dataset in the world. The vastness of the DoD’s dataset combined with the department’s commitment to basic biological surveillance yields a unique opportunity to create the best artificial intelligence–driven healthcare system in the world. (emphasis added)”
While the CNAS authors claim that the Pentagon and Silicon Valley merely aim to improve civilian and military healthcare through this AI healthcare system, this technocratic evolution of healthcare importantly presents a mutually beneficial opportunity for each of these institutions. For the private sector, as the CNAS article states, the DoD possesses a plethora of data with “intrinsic commercial value.” For the Pentagon, such a relationship with Silicon Valley would expand its data mining efforts into the body, allowing for a wider array of valuable data to use for national security purposes.
Further, implementing a predictive medicine infrastructure provides both sectors with the pretext to amass more health data, and to continuously do so, in order to train the predictive AI technology. This has already granted the Pentagon the pretext to increase data-collection efforts in the name of creating this AI healthcare system, potentially explaining the creation of predictive health programs such as ARPA-H and AI forecasting infrastructure like the CDC’s CFA. Importantly, the biosurveillance field’s biggest advocates also have a long history of stressing the importance of mass interagency data sharing, including between the public and private sectors — highlighting again the cross-sectoral commitment to utilizing this data for both profit and national security.
II. Big Pharma
While the CNAS authors wrote their “Predictive Medicine” article before the Covid-19 pandemic, the most prominent institutions in the pandemic preparedness / biosurveillance field have already begun selling the “predictive” approach to public health as the solution to the “next pandemic.” One of the most prominent aspects of predictive health involves using biosurveillance data to fuel the research and distribution of medical countermeasures—a policy that the CDC’s CFA is pursuing:
“[The Analytics Response Branch] works with key partners to inform decisions on medical countermeasures during an active outbreak.”
This policy unsurprisingly has the backing of the industry that most clearly stands to gain the most from it—Big Pharma. In 2023, scientists from Pfizer’s mRNA Commercial Strategy & Innovation department (one of whom hails from John Hopkins Bloomberg School of Public Health) wrote an article titled “Outlook of pandemic preparedness in a post-COVID-19 world” in which they pushed for the utilization of predictive AI technology to inform real-time policy during the “next pandemic.” The scientists pitched AI-informed policy decisions as the solution to the downsides of universal pandemic policies, specifically through a more “targeted” approach to pandemic policy.
The paper advocates for the development of preemptive vaccines, which are vaccines developed for viruses that do not yet spread prominently in human populations. Surveillance data of pathogens with pandemic potential fuels this research, as the paper notes that vaccination benefits have “continued to progress” due to the power of constant biosurveillance and accelerated manufacturing, demonstrated by the development of “updated vaccines for evolving variants of SARS-CoV-2.”
Similarly, the authors tout the abilities of these preemptive vaccines to be quickly dispersed to protect populations from outbreaks of pathogens with pandemic potential if the pathogen “closely aligns” with a preemptively developed vaccine stockpile. These preemptive vaccines, however, would only offer temporary protection until “more tailored interventions” were developed, if deemed necessary.
This echoes the long calls of other global health institutions to develop preemptive vaccines. As a previous Unlimited Hangout investigation reported, the WHO’s 2014 CEPI-partnered program, Research and Development Blueprint for Emerging Pathogens (R&D Blueprint) aims to “reduce the time” that vaccines can get to market after the declaration of a pandemic. It does this, however, not only through conducting R&D on pathogens that already reach pandemic status, but also by conducting R&D on diseases that “are likely to cause epidemics in the future.” CEPI itself—started with investments from the Bill & Melinda Gates Foundation and the Wellcome Trust—was founded to develop “vaccines against known infectious disease threats that could be deployed rapidly to contain outbreaks, before they become global health emergencies.”
CEPI is currently assisting in building up an apparatus of research and private companies pursuing predictive vaccine development, who may up end being some of the “key partners” that the CFA plans to work with to “inform decisions on medical countermeasures during an active outbreak,” given CEPI’s close partnership with the Gates Foundation via the Gates Foundation’s Gavi, the Gates Foundation’s history of funding the CDC and Gates’ potential influence within CFA (demonstrated later in this article). CEPI made these investments to further its “100 Days Mission” that aims to “accelerate the time taken to develop safe, effective, globally accessible vaccines against emerging disease outbreaks to within 100 days.”
Interestingly, CEPI claims that the construction of a “Global Vaccine Library” is crucial to the success of its 100 Days Mission. The Library plans to utilize AI technology to predict how “viral threats could mutate to evade our immune systems” in order to identify specific “vaccine targets.” Richard Hatchett, the CEO of CEPI (formerly of the US Biomedical Advanced Research and Development Authority (BARDA)) stated that building the Global Vaccine Library will require “coordinated investments in countermeasure development and, in outbreak situations, rapid data sharing.” Perhaps the datasets that the CFA will utilize and expand could assist in creating this Global Vaccine Library by making possible the “rapid data sharing” that CEPI requires.
III. Building on Tiberius
Another element of informing medical countermeasure policy through data is distribution—something that Palantir gained direct experience with during the COVID-19 pandemic. The CFA now plans to utilize its data and analytical tools to inform its “key partners” on “decisions on medical countermeasures during an active outbreak.”
During COVID-19, the Pentagon–run Operation Warp Speed initiated its vaccine distribution policy in direct collaboration with Palantir through the Palantir program “Tiberius,” which the CDC has since pledged to unite with other Palantir biosurveillance programs as part of its “Common Operating Picture.” Tiberius uses a Palantir software product called Gotham that also manages another Palantir-run government program called Health and Human Services (HHS) Protect, “a secretive database that hoards information related to the spread of COVID-19 gathered from ‘more than 225 data sets, including demographic statistics, community-based tests, and a wide range of state-provided data.’” The database notably includes protected health information, which led Democratic senators and representatives to warn of the program’s “serious privacy concerns”:
“Neither HHS nor Palantir has publicly detailed what it plans to do with this PHI, or what privacy safeguards have been put in place, if any. We are concerned that, without any safeguards, data in HHS Protect could be used by other federal agencies in unexpected, unregulated, and potentially harmful ways, such as in the law and immigration enforcement context.”
During the pandemic, Tiberius drew on this health data so that it could “help identify high-priority populations at highest risk of infection.” Tiberius identified the risk levels of these populations in order to develop “[vaccine] delivery timetables and locations” to prioritize vaccines in specific “at risk” populations. Most often these populations were minority communities and notably, the COVID-19 vaccines are associated with an excess risk of serious adverse effects, and can cause fatal myocarditis.
Further, as noted in a previous Unlimited Hangout investigation, intelligence agencies and law enforcement agencies, such as the Los Angeles and New Orleans police departments, also use Gotham for “predictive policing,” or pre-crime initiatives which disproportionately affect minority communities (ICE also used Palantir’s digital profiling tech to apprehend and deport illegal immigrants). The US Army Research Laboratory also found Gotham useful, as evidenced by its $91 million contract with Palantir “‘to accelerate and enhance’ the Army’s research work.” More recently, Palantir teamed up with Microsoft to provide national security leaders with an opportunity to exploit a “first-of-its-kind, integrated suite of technology,” including its Gotham software, among other products, for “mission-planning” purposes (the military also uses Gotham for “targeting enemies” through its “AI-powered kill chain”). These lucrative contracts with the intelligence/military state highlight the dual-use nature of the technology behind the “AI-healthcare” revolution, and thus raise the question: will Palantir and other government agencies utilize the health data that CFA can access for “dual-use,” national security purposes?
The Digitization of Healthcare: Kinsa, Palantir and the ‘Targeted’ Nature of Future Pandemic Response
Notably, some prominent institutions within the biosecurity apparatus have already begun pitching “targeted” pandemic policy as a solution to the now widely recognized failings of the more universal non-pharmaceutical intervention (NPI) policies of COVID-19, such as lockdowns, social distancing and school closures, which unleashed economic devastation, physical death and mental health decline upon many populations.
For instance, the Pfizer paper, “Outlook of pandemic preparedness in a post-COVID-19 world”, mentioned earlier, surmises that the negative effects of NPIs such as school closures, lockdowns and hospital policies may be felt years into the future and even be shown to increase in severity with further studies. Lockdowns in particular, the authors note, “resulted in significant economic, social, and health costs,” and they even state that “the effect of social distancing on the mental health of children and adolescents [continues] to be difficult to measure.” From a bureaucratic perspective, the paper also admits that consistent and long-term use of NPIs can be “challenging because people grow tired and apathetic toward them.”
The solution that the Pfizer scientists offer is “early action” being used to “leverage all available interventions as soon as possible in pandemic response,” and importantly, “geographically specific and informed NPI policies.” It appears that at least one of the solutions the paper puts forth, to both implement “early action” and “geographically specific” policies, is to “have a gradient of warnings that separate dangerous pandemics from more manageable outbreaks…” This proposed policy recalls the CFA measure that analyzes “disease spread through existing data sources to identify key populations/settings at highest risk” (emphasis added).
The paper goes on:
“In healthcare settings, an artificial intelligence platform could help prioritize patients based on their medical needs, effectively managing resources during triage situations. Similarly, a gradient-based warning system for pandemics could initiate appropriate responses at different levels of threat, with each level tied to specific actions. An early warning or Level 1 may involve increased surveillance and information sharing, while higher levels could trigger more drastic measures like regional shutdowns or global travel restrictions.” (emphasis added)
A system of surveillance this vast, importantly, could only be achieved through the “the facilitation and coordination” of all biosurveillance activities—from the local to federal levels of government and healthcare entities— that the CFA will carry out.
Other Pharma-backed organizations have also called for targeted pandemic response policy, such as the Committee to Unleash Prosperity which stated “identifying the most vulnerable groups and focusing resources on their protection will always be critical to any sensible crisis response.” The Committee to Unleash Prosperity is funded by the Pharmaceutical Research and Manufacturers of America, whose members include Pfizer, Johnson & Johnson, Glaxosmithkline, Merck, and Sanofi among other Big Pharma companies. The group was also notably co-founded by Larry Kudlow, formerly one of Trump’s top economic advisors and directors of the National Economic Council during his first term, who—during Covid-19—was part of the group that decided to effectively outsource the U.S. fiscal response to the crisis to Larry Fink’s BlackRock.
The push for such “targeted” measures are furthermore indicative of an even greater systemic transformation taking place in the healthcare system. The calls to “help prioritize patients based on their medical needs” in order to “effectively manage resources during triage situations” allude to the industry effort to digitize hospital management, resource allocation and patient care, and, in doing so, expand the health datasets of the biosecurity apparatus. Private companies including Palantir, among others, it turns out, are already playing crucial roles in this AI-hospital revolution.
Meanwhile, the CFA codifies the push towards this AI-system through multiple policies:
“[The Predict Division] assists with tabletop exercises to match policies and resources with forecasts”
“[The Office of Management Services] provides direction, strategy, analysis, and operational support in all aspects of human capital management, including workforce and career development and human resources operations”
The first company involved in this shift worth noting is Kinsa Health—a company that “uses internet-connected thermometers to predict the spread of the flu”—which is carrying out the kind of data mining that would enable this kind of predictive and targeted pandemic policy that CFA seeks to carry out. According to the The New York Times, Kinsa is “uniquely positioned to identify unusual clusters of fever because they have years of data for expected flu cases in each ZIP code.” During the COVID-19 pandemic, Kinsa was allegedly able to forecast which locations would become “COVID-19 epicenters” before more traditional surveillance systems could.
The thermometers supply data by connecting “to a cellphone app that instantly transmits their readings to the company.” Interestingly, “Users can also enter other symptoms they feel. The app then gives them general advice on when to seek medical attention.”
In the aftermath of the COVID-19 pandemic, Kinsa has emerged as a rising star within the predictive health industry, as it has secured a significant deal with healthcare company Highmark Health to “predict health care utilization, recognize staffing needs, and plan emergency department and ICU bed capacity when infectious diseases like COVID-19 and influenza spike.” The initiative is “the first health delivery system to utilize Kinsa’s early warning system to model staffing needs and bed capacity”—signifying Kinsa’s increasing role in this healthcare shift.
This preceded health technology company Healthy Together’s 2024 acquisition of Kinsa, which marked a significant step for the thermometer company, as the acquisition signifies the expansion of Kinsa’s predictive powers and datasets into the public sector. The announcement proclaimed that “the synergy between the two companies will empower pharmaceutical companies, healthcare providers, Medicaid agencies, insurance companies, and public health departments with AI-driven tools to proactively respond to and address illness.” The bold vision here is perhaps unsurprising—that is, only when Healthy Together’s peculiar ties to government and Thiel-connected figures, and its larger vision, are understood.
Healthy Together is a Software as a Service (SaaS), or a service that “allows users to connect to and use cloud-based apps over the Internet.” It prides itself on unifying “the objectives of government programs and the needs of residents into a single platform.” The way it does this is through its “One Door” approach, or rather—its mission to make available one’s health records and immunization history “all in one place,” that place being their proprietary app. Indeed, Healthy Together has already partnered with the Department of Veterans Affairs (VA) Lighthouse program to access veteran’s health data ranging from immunization records, “test results, allergy records, clinical vitals, medical conditions and appointment records.” This connectivity was achieved via the VA’s application programming interface (API), as veterans using the Healthy Together app access their medical records through the VA API, which connects different computer programs together. This serves as a small-scale example of the growing harmonization between military and Big Tech data.
In addition to health data, the company also aims to link welfare data and access to its app—a particularly concerning feature given that some US health experts tied to the CIA’s In-Q-Tel and official government Covid-19 response policy previously pitched linking welfare benefits to vaccination status during the Covid-19 crisis.
When Healthy Together partnered with Amazon Web Services (AWS) to join its AWS Partner Network (APN), it created a program that achieves this linkage of welfare data with its app. It was called the “Women, Infants, and Children (WIC) Management Information System (MIS),” or Luna MIS. WIC is a United States Department of Agriculture (USDA) federal assistance program that provides low-income pregnant women and children under the age of five with services such as EBT cards to help them afford food. Luna MIS apparently streamlines “the management of WIC benefits, from application and enrollment to benefit issuance and redemption,” meaning it transfers users’ entire interaction with WIC benefits, from registration to allocation, into the Healthy Together app. The company further supports this “One Door” approach for eligibility, enrollment and recertification for other social programs such as “Medicaid, SNAP, TANF…as well as behavioral health, disease surveillance, vital records, child welfare and more.”
Whether or not data collected via technology such as Kinsa thermometers or health records, such as immunization status, might informs one’s eligibility or enrollment for social programs in the future remains to be seen. Either way, the company already works directly on welfare benefits with the Florida Department of Agriculture and Consumer Services , the Chickasaw Nation in Oklahoma, Missouri Department of Social Services, Maryland Market Money and Maryland Department of Agriculture and more. Given that the company already collects vast amounts of medical data, including vaccination records, linking such data to welfare benefits would likely prove an easy task for the company.
While there is not much public information available about Healthy Together’s board or funding, it appears that the “One Door” service was born out of another app—which is no longer available—called Twenty (as a significant number of Healthy Together’s co-founders/CEOs apparently still work at Twenty, and hold the exact same positions at each company).
According to the Salt Lake Tribune, Healthy Together was developed in the early days of the pandemic when the state of Utah “contracted with mobile app developer Twenty to launch Healthy Together” in order to track the residents of Utah’s “movements” and, for those that fell ill, equip public health workers with a digital contact tracing tool to discover “where they crossed paths with other users.” The Tribune reported that Utah provided Twenty with a $1.75 million contract, along with an additional “$1 million to further develop [Healthy Together].” In other words, Healthy Together was built as a public-private “contact tracing” (i.e. surveillance) app.
Twenty, according to its LinkedIn, was an app that aimed “to drive more human connection” by making it easier for friends to meet up and make plans. It does this, however, by allowing users to see the locations of nearby friends, even cluing them into their friends’ later plans and pinning events for people to meet up at. While Healthy Together and Twenty are separate apps, it appears that the seemingly social location-based tracking technology used for Twenty was swiftly repurposed to create the contact-tracing and health-focused app Healthy Together, as the co-founder and co-CEO of Twenty and Healthy Together, Jared Allgood, stated:
“…at the start of the pandemic, we were contacted by some state governments who are interested in using some of the mobile platform technology that we had built previously, to create a link between the health department and residents in their state…” (emphasis added)
The Salt Lake Tribune explained the contact tracing process that the repurposed technology of Healthy Together helped the state achieve:
“the app uses Bluetooth and location tracing services to record when its users are in close proximity. When a user begins to feel ill, he or she can enter symptoms on the app, which provides directions for testing.
State epidemiologist Angela Dunn further explained the process…‘So if you choose to share your data with our contact tracers’ by using the app, she said, ‘they’ll be able to know about the places that you’ve been while you were infectious, and it’ll also provide our contact tracers with a snapshot of other app users who you had significant contact with and potentially exposed with COVID-19 as well’…. ‘that will allow contact tracers to follow up directly with those people and provide them information about how to protect themselves and others,’ she said.”
Now, the goals and functions of Healthy Together seem to have expanded into AI viral forecasting and hospital management with its acquisition of Kinsa, making the private company a potential asset for the CDC CFA, as its experience in working with health data would seemingly make it a fitting “existing data source” for the program.
The people behind these companies too, however, make Kinsa and Healthy Together not too far removed from CFA’s other private sector partners. Healthy Together was funded by SV Angel, the venture capital firm founded by “The Godfather of Silicon Valley,” Ron Conway, who was an early investor in the Elon Musk-and-Peter Thiel-founded Paypal and also in the Peter Thiel-backed Facebook (Thiel and Conway were among the earliest backers of the social network).
Another co-founder and co-CEO of Healthy Together and Twenty, Diesel Peltz, boasts interesting ties to the incoming Trump administration via his father, billionaire and chairman emeritus of the Wendy’s Company, Nelson Peltz. The Nelson Peltz claims responsibility for re-connecting Elon Musk and Trump, which led to Musk financially and very publicly back the 2024 Trump campaign. Since the election, Musk’s outsized role in setting incoming government policy has become both obvious and controversial. Variety reported the following about the Peltz family role in uniting Musk with Trump:
“[Peltz] said Musk, together with Peltz’s son Diesel…‘had a breakfast at the house, we invited Donald for breakfast, and they [Musk and Trump] sort of reunited again… I hope it’s good, you know. I was a matchmaker.’” (emphasis added)
Importantly, both Thiel and Musk played critical roles in successfully lobbying for the appointment of Thiel protege JD Vance as Trump’s vice presidential nominee. Now, Musk is set to head Trump’s Department of Government Efficiency advisory group, along with the founder of the biotech company Roivant (which has created subsidiary biotech companies with Pfizer, and has invested deeply in mRNA technology), Vivek Ramaswamy, to “dismantle government bureaucracy, slash excess regulations, cut wasteful expenditures and restructure federal agencies.”
The meeting between the two Peltz men, Musk and the President Elect took place in the late Spring, and it was only a few months later that Palantir and Wendy’s Supply Chain Co-op announced a partnership to “bring [the co-op] towards a fully integrated Supply Chain Network with opportunities for AI-driven, automated workflows,” by moving its supply chain onto Palantir’s Artificial Intelligence Platform. The platform is, familiarly, “designed to connect disparate data sources into a single common operating picture…” Wendy’s will eventually use Palantir to manage its supply chain and waste prevention, including through “Demand Deviation and Allocation.” All of this will push the fast-food company with an otherwise folksy aesthetic, personified through its ginger-haired freckled mascot, Wendy, towards the increasingly technocratic new age—and the Peltz family closer to the Thiel-verse.
Also worth noting is Arianna Huffington’s seat on the board of Twenty. Huffington’s appointment warrants mentioning only because of her relationship with another protege of Peter Thiel, CEO of OpenAI, Sam Altman. The media mogul and tech entrepreneur recently teamed up to create the fitness app Thrive AI Health, which gives users a “hyper-personalized” AI health coach.
Thiel has been described as Altman’s “longtime mentor,” and apparently at the beginning of Altman’s career, “Thiel…saw in Altman a magentic figure who could expand the tech sector’s approach across the world.” Thiel’s rosy view of the OpenAI CEO is evidenced by the mutually beneficial relationship that matured between the two after Altman sold his company Loopt, and Thiel raised the bulk of the $21 million dollars that Altman later gathered for his own venture capital firm, Hydrazine Capital, according to the The Washington Post. Soon after, “Altman’s bond with Thiel blossomed: He helped Thiel’s venture firm, Founder’s Fund, get access to hot start-ups, and the men sometimes traveled together to speak at events.”
Recently, Palantir and another Thiel-backed company, Anduril, have partnered on behalf of the Pentagon to “unlock the full potential of AI for national security,” specifically by retaining data at the “tactical edge” of the battlefield, data that is usually “never retained.” Apparently, this new partnership will make the collection of this “tactical edge” data possible, and be used to train AI models and “deliver the U.S. an advantage over adversaries.” It will also enable “collaboration with leading AI developers, including [Sam Altman’s] OpenAI” (emphasis added).
It now seems that Thiel, through the aforementioned relationships, is not too distant in proximity from (though not directly intertwined with) Healthy Together and Kinsa, all while Palantir further entrenches its relationship with the CDC (as well as the DoD) and positions itself as a health data empire.
Kinsa’s Connections to Bill Gates
Notably, the CEO and founder of Kinsa, Inder Singh, hails from the Clinton Health Access Initiative (CHAI) where he formerly served as the Executive Vice President. CHAI was controversially created with significant involvement from Jeffrey Epstein, the now infamous pedophile, sex trafficker and intelligence asset, and Epstein was simultaneously involved with Bill Gates during that same period, including the Gates’ family philanthropy (Epstein was notably an advocate for transhumanism and eugenics, which informed much of his “philanthropic” activities and funding of prominent scientists). Unsuprisingly, CHAI has been funded by none other than the Bill & Melinda Gates Foundation to the tune of tens of millions of dollars (see here and here), and also shares a nearly identical goal of vaccinating “as many children as possible” with its partner Bill Gates’ Gavi, the Vaccine Alliance, by “creating dramatic and sustainable improvements to vaccine markets and national immunization programs.” The Gates Foundation notably envisions AI as central to its global health objectives, as it funded a United States Agency for International Development (USAID)—an organization that often acts as a CIA front—effort to push for the global implementation of AI in healthcare.
As a previous Unlimited Hangout investigation noted, Gavi’s stated goal is to create “‘healthy markets’ for vaccines by ‘encourag[ing] manufacturers to lower vaccine prices for the poorest countries in return for long-term, high-volume and predictable demand for those countries.’”
And to bring these relationships full circle once again, Palantir joined “The Trinity Challenge” in 2020, “a global coalition of prominent academic institutions and foundations as well as leading technology, health and insurance companies with the aim of increasing the world’s resilience against the pandemics of the future by harnessing the power of data, analytics.” Its members included Google, Microsoft, Facebook, McKinsey & Company and—the Gates Foundation. The Trinity Challenge has been criticized for framing invasive surveillance and neo-Malthusian policies as “solutions” to the “next” pandemic and as beneficial for global public health.
Indeed, the influence of Gates may have navigated its way into CFA itself, with the CFA director, Dylan George, previously serving as vice-president of biotech firm Ginkgo Bioworks. Ginkgo Bioworks, a partner of the World Economic Forum, was heavily funded by Cascade Investment when the company went public, an investment firm controlled by Bill Gates. By utilizing a “constellation” of shell companies that all connect back to Cascade, Gates also accumulated enough property to make himself the largest farmland owner in the United States during the Covid-era. Cascade is still the largest shareholder of Ginkgo Bioworks.
It should also be noted that Gates supports the United Nation’s (UN) efforts to implement a universal Digital ID as a “human right,” or in reality, a pre-condition for accessing other human rights, for the entire global population by 2030 through the UN’s Sustainable Development Goal 16.9. Previously, the EU Digital Covid Certificate enabled governments to, as the Pfizer “Outlook” paper advocates, “restrict global travel” based on a form of digital ID, that importantly had health data attached to it (in this case, only COVID-19 immunization status, testing results and records of previous infections.). Multiple groups seeking to impose digital ID infrastructure globally were intimately involved in digital vaccine passport production during the Covid-19 crisis.
It is important to remember that local travel restrictions, or “decisions surrounding community migration,” during the COVID-19 pandemic were enforced using both physical and digital proof-of-vaccination—a form of ID that attaches “health data” to the ID, with that “health data” then being utilized to determine one’s accessibility to certain human rights (such as entry into certain businesses/events or job access).
Gates’ funding of the CDC, as well as his connection to the CFA and Palantir and the program’s stated policy aims of analyzing disease spread to identify the “highest risk” key populations and utilizing data to influence “community migration” rights raises an important question: will CFA data be attached to a digital ID, and how might that data be used to determine one’s human rights (such as community migration, for example) during a declared, or anticipated, public heath crisis?
AI Hospitals
While Palantir’s recent transition into AI hospital management is not an exact illustration of life with digital ID, some of its features suggest what a future managed by constant surveillance and AI decision-making might look like—not only in healthcare, but the workplace in general.
According to its website’s “Hospitals for Palantir” page, Palantir is already “powering nurse scheduling, nurse staffing, transfer center optimization, discharge management, and other critical workflows” for more than 15% of US hospitals. Palantir’s “healthcare engineers” work “directly alongside caregivers and hospital operators to build and tailor workflows — prioritizing speed, effectiveness, and usability.”
The tech company has “deployed a first of its kind application that takes into account nurse preferences, granular patient demand forecasts, staff competencies, and existing staff information to automatically generate AI-driven, optimal nursing schedules,” a seemingly innocent project. Yet, the degree of influence that this “first of its kind” application already appears to wield in American hospitals spells a troubling precedent for humanity in the workplace—specifically, by dehumanizing the logistical and bureaucratic nature of hospitals through AI substitutes under the auspices of “objective” machine decision-making.
Palantir’s Foundry is already forecasting “the patient census for a hospital based on data from the emergency department, operating rooms, transfers, discharges, and more.” The tech systems also keep track of the skills and information for every nurse in a hospital, “including (but not limited to) competencies, languages, skills, certifications, tenure, and other talent profile information.” Both kinds of data apparently generate the prime nursing schedule for the entire hospital, down to any given “unit, floor, department, [or] facility.”
While these systems project the image of an altruistic product aimed at providing a more seamless experience for patients and hospital workers alike, critical media scholar Dr. Nolan Higdon, co-author of the book “Surveillance Education” which explores the invasive nature of surveillance technologies in schools (as well as the intersection between Big Tech and the military industrial complex), told Unlimited Hangout that Big Tech companies recycle this altruism-pitch time and time again as a way to mask their ulterior motives:
“Whenever these companies employ data collection mechanisms under the auspices of improving the lives of customers, it ultimately ends up being a scheme to make more money, and at the expense of labor and the customer.
What we’ve seen consistently over and over again is whatever readout they get of the data ends up being an excuse to cut jobs, to overwork individuals, to minimize services and access to services as a way to cut costs…So it’s: if we collect data, how much more work can we throw on the back of this nurse? Can we throw enough work on the back of this nurse where patients will complain and we can cut another job or two? Those are the kind of questions that this data is trying to help folks make.”
Yet Higdon fears that this goal of increasing profits could also enable even more vicious price gouging of patients that the healthcare industry already engages in with little transparency. Palantir claims that its tech can recommend in real time where a hospital should place incoming patients based on “patient-specific criteria” and “current and upcoming [hospital] capacity,” which obviously would require access to a breadth of patient data. Higdon wonders whether or not insurance providers might weaponize this data against patients by raising their premiums based on life decisions of the patient:
“Not everybody is totally honest with their insurer about maybe how much they sleep or how much they drink or how much they party or whatever, right? These tools can be a way to surveil people to find that information out to set premiums that are aimed at maximizing the amount of money you get from customers and save the amount of money for the insurance company.
The more they know about your life, the more justifications they can make about setting premiums. Maybe in their algorithmic counts, if you sleep six hours a night instead of eight hours a night, you’re more likely to have these health outcomes. So they’re going to charge you more money now until your sleep patterns change. Or maybe you eat X amount of processed food and that’s been associated with this outcome. So they’re going to charge more on this premium.
There’s so [much] ‘in the weeds’ evidence that can be used against folks, and you don’t have any recourse. Because again, they go back to, ‘well the objective algorithm has given us this readout.’”
While Palantir vows that it keeps “patient privacy and information governance a top priority,” promises like these simply provide tech companies smokescreens to obfuscate the vast amount of data sharing they engage in. Higdon claims that while many companies, like Palantir, promise users that they do not sell client data, those companies still share it between institutions they’ve entered agreements with. On Palantir’s Medium Blog, for example, it vows to readers that it does not sell or share its data with other customers…that is, “except where those specific clients have entered into an agreement with each other.”
However, whether or not this applies specifically to Palantir’s first and longest-running client, the CIA, remains doubtful. Many tech companies, particularly social media giants and search engines, were revealed in past years to illegally share user data with US intelligence to facilitate vast, post-9/11 surveillance programs of dubious legality. Importantly, at Palantir’s origins its founders collaborated with the intelligence state to resurrect a DARPA-CIA surveillance program that sought to merge existing databases into one “virtual, centralized, grand database.” Given this, it seems more than plausible that Palantir allows US intelligence to access more of the data the company handles than they publicly acknowledge.
Palantir also creates profiles of American citizens for the CIA based on their online activities (and other activities that are surveillable). If Higdon’s concerns of data sharing do indeed apply to Palantir, then Palantir could easily fold its trove of American health data into such profiles. In fact, the CFA requires organizations applying to become partners of the program to describe how they plan to leverage novel data sources “to create new analytic products.” An example they provide for applicants involves using “data fusion techniques” to merge data extracted from the internet with “existing public health data streams” in order to create detailed forecasts of present (or future) events that “reduce latency.”
This is particularly troubling given Palantir’s role in implementing “predictive policing”, i.e. pre-crime, in the United States and that law enforcement and intelligence agencies could weaponize mental health data in particular in the context of preventing crimes before they occur. While some may deem this scenario far-fetched, it is worth considering that the previous Trump administration closely considered a policy to use AI to analyze innocent Americans’ social media profiles for posts that could indicate “early warning signs of neuro-psychiatric violence” as a means of preventing mass shootings before they occur. Per that program, the government would subject Americans flagged by the AI to various mandated mental health interventions or preventive house arrest. A scenario in which law enforcement utilizes mental health data from healthcare settings tied to Palantir in lieu of, or in combination with, social media posts is not difficult to envision.
Further, while Palantir claims to make patient privacy a “top priority,” regulatory bodies have yet to enact any meaningful oversight of the company to prevent it from sharing this data with other organizations, much less itself and thus the other branches of government it actively works with. This lack of transparency creates a “hall of mirrors” that blurs the lines between organizations, and therefore who owns what data, covertly eliminating any rights to privacy while at the same time enabling the corporate construction of a digitized global consciousness made up of the data of unknowing civilians—in this case, all in the name of “public health.”
The Hall of Mirrors
The CDC CFA’s alleged commitment to utilize groundbreaking methods to better public health remains to be seen. Yet, what this article definitively illustrates is that the CFA further entrenches both the public and private wings of the public health apparatus into the “hall of mirrors” of intelligence agency-connected corporations and public institutions. Behind these organizations sit some of the most influential kingmakers of Washington, hailing from Silicon Valley, seemingly committed to utilizing any industry or catastrophe to expand their surveillance of human bodies, equipping them with the capital to become the robber barons of the digital age.
Importantly, however, the CFA does not signify a shift in public health policy, but rather a firm step forward in a years-long effort to drive the entire public health apparatus into the hands of hawkish national security ideologues and their oligarchic, technocratic benefactors. For normal people, the implications of such policy pursuits may be significant. During the “future pandemics” that this entire industry is already spending billions of dollars preparing for—with expected returns in mind—the CFA’s surveillance may dictate the average civilians’ global travel rights, even their ability to traverse their own communities, what medicines they take/have access to and whether they are deemed “high risk” or not.
The actors behind this system are unsurprisingly the same ones that planned, directed and carried out the COVID-19, halfway-digitized, iterations of similar biosecurity policy. The fingerprints of figures like Gates, with the head of the CFA hailing from the Gates-funded Gingko Bioworks, and those of Big Pharma and the Pentagon are plastered all over the program’s doctrine.
Critically, the program’s existence should be considered within the context of the coming Trump administration, which boasts deep ties to its most prominent figures. The Thiel-verse have exerted their influence over D.C. politics wisely, demonstrated not only by the plethora of government contracts won by Thiel-connected companies across agencies, but by the infiltration of Thiel proxies like Founders Fund alumnus J.D. Vance into Trump’s cabinet.
As Stavroula Pabst recently noted in Responsible Statecraft, Thiel “bankrolled fellow venture capitalist and now-VP elect J.D. Vance’s successful 2022 Senate Campaign in Ohio to the tune of $15 million — the most anyone has given to a Senate candidate. Thiel and Vance are in fact long term associates, where Thiel previously assisted Vance’s own venture capital career.” While Trump ended up picking the billionaire national security contractor billionaire Stephen Feinberg as his Deputy Secretary of Defense, he was eyeballing Trae Stephens for the position, formerly of Palantir and a “longtime partner at Thiel’s Founders Fund and co-founder and Executive Chairman at Anduril,” further demonstrating that the relationship between Thiel and Trump continues to endure. In addition, another Thiel proxy – Jim O’Neill, who boasts deep ties to mRNA tech – has been nominated to be the No. 2 at HHS and will likely serve as HHS Secretary if the Senate rejects the confirmation of Robert F. Kennedy Jr. O’Neill’s upcoming role at HHS heralds not only a continuation but a likely deepening of Palantir’s involvement at HHS sub-agencies like the CDC.
Companies such as Kinsa and Healthy Together stand as well-positioned potential benefactors of this Thiel-friendly relationship with the coming Trump administration, not only because of the connections Diesel Peltz boasts to PayPal Mafia member Elon Musk, Trump himself and early PayPal investor Ron Conway, but because its products have made it a prominent data-miner at the intersection of healthcare and Big Tech. From this perspective, a myriad of other companies including defense contractors Amazon Web Services, Microsoft and Google, sit in a similar position.
Exactly which companies will be tasked to fulfill certain responsibilities remains to be seen, but the agenda-at-large remains the same; massively increase the surveillance powers of this biosurveillance apparatus, and then utilize these powers to influence public policy, increase control of civilian movement and access to rights, secure deregulated markets for biotechnology and, most importantly, make everything about the individual civilian subject to the surveillance, and scrutiny, of the shadowy organizations occupying the watchtower of the digital panopticon.
The privatization, and thus on-the-surface “decentralization” of this program grants it the appearance of the natural evolution of the free market. Yet Palantir’s origins in the DARPA/CIA Total Information Awareness (TIA) program, as well as the merging of all three of these sectors and the clear gains all stand to achieve, suggest a more organized and cynical pursuit of the policies that CFA appears to be making reality. Together, these industries form a technocratic iteration of the Mighty Wurlitzer. Playing specified tunes to targeted audiences, whether they be the altruistic notions of public health, the frightening potentials of unchecked domestic terrorism or bioterrorism, the catastrophe of global pandemics or even simple workplace efficiency, each melody this apparatus plays serves to manufacture consent for their ability to conduct ever-expanding surveillance of everyone. This obviously makes the declared “public health” purposes of the biosurveillance apparatus at large highly questionable.
After all, the AI-healthcare system promises a more efficient, convenient and effective healthcare system—yet the means by which this system is meant to lead the public to a predictive-health utopia involve the elimination of privacy and the dehumanization of healthcare itself. Left to algorithms controlled by corporate sharks and national security hawks, profits, surveillance and top-down influence are an all but guaranteed outcome, but what will the digitization of care do to the physical, mental and spiritual health of everyone else? Perhaps those people—beyond the data that corporations can extract from them—are an afterthought of those behind the AI-healthcare revolution.