Tag: ai

  • AI, the Antichrist, and the Machine We May One Day Obey

    AI, the Antichrist, and the Machine We May One Day Obey

    For nearly two thousand years, every age has tried to recognize the Antichrist in the face of its greatest fear. Our age may be doing the same with artificial intelligence, although this time the comparison raises an uncomfortable question that cannot be dismissed quite so easily: what if the danger is not that a machine becomes a supernatural being, but that human beings gradually create a system to which they surrender the authority once reserved for gods, kings and prophets?

    There is something strangely familiar about the anxiety surrounding artificial intelligence today. The technology is new, astonishingly new in the form most people now encounter it, yet the fear it provokes belongs to an ancient part of the human imagination. Whenever societies have entered periods in which the familiar world seemed to be slipping away, people have searched old prophecies for signs that history was approaching some predetermined end. Wars, epidemics, political upheavals, economic collapse, nuclear weapons and cultural revolutions have all, at one time or another, been interpreted as evidence that the final chapter had begun.


    Now artificial intelligence has entered the prophecy.


    A recent BBC investigation brought together pastors, theologians and researchers who have begun asking publicly whether AI could play some role in Christian scenarios of the “end times.” American pastor Philip Anthony Mitchell has argued that artificial intelligence will have a major role in the events preceding the end of the world, while pastors Greg Laurie and Mike Signorelli have entertained similar possibilities, Signorelli explicitly connecting modern technology with the path toward the Antichrist. None of them denies that AI may be useful, and none can demonstrate that a biblical prophecy is actually describing modern computing, but their concerns have found a receptive audience because they touch something deeper than theology alone.
    The idea sounds sensational when reduced to the headline “AI is the Antichrist.” It becomes considerably more interesting once that headline is discarded.


    The Book of Revelation does not mention computers, algorithms, artificial intelligence, biometric identification or digital currencies. More surprisingly, the word Antichrist itself does not appear in Revelation at all. The term occurs in the First and Second Epistles of John, where it is connected principally with opposition to Christ, false teaching and deception. Revelation presents other symbolic figures instead: the dragon, the beasts, Babylon and, later, the false prophet. Christian tradition gradually brought several of these strands together, which is one reason popular culture now tends to treat “the Beast” and “the Antichrist” almost as though they were interchangeable characters.

    That distinction is more than a theological technicality, because once it is understood, the entire question begins to change. Perhaps it makes little sense to search Revelation for a hidden description of a computer that John of Patmos could not possibly have named. Perhaps the more intriguing approach is to examine what Revelation feared: concentrated power, deceptive signs, manufactured worship, economic dependence and a system in which loyalty becomes inseparable from ordinary life.
    Those themes are considerably harder to dismiss.


    The ancient beast was born in a very different world

    Revelation emerged from the world of the Roman Empire, and its extraordinary imagery makes far more sense when that world is remembered. Yale’s New Testament scholarship describes the book as deeply hostile to Roman imperial power, with “Babylon” functioning as a symbolic name for Rome and the beasts representing forms of oppressive empire. The famous number 666 has long been associated by many scholars with Nero Caesar through gematria, an ancient practice in which letters were assigned numerical values. Even the alternative reading of 616 found in some early manuscripts fits a different spelling of Nero’s name, one reason the Nero interpretation has remained so influential.

    For the first Christians hearing Revelation, Rome was not an abstract political theory. It was the civilization surrounding them, a vast system of military authority, commerce, taxation, public ritual and imperial symbolism. Coins carried the emperor’s image; cities displayed imperial power everywhere; religion, economy and political allegiance could overlap in ways that modern secular societies often find difficult to imagine.
    One Yale Bible Study commentary even interprets Revelation’s language about buying and selling in connection with Roman coinage bearing imperial images, although, like much in Revelation scholarship, the details remain debated. What matters for our present discussion is that the text originally spoke to people living inside a system of power they could neither easily escape nor openly defeat.

    That historical reading does not prevent Christians from believing Revelation may contain a further prophetic dimension. It simply warns us against assuming that every new technology was secretly encoded in its pages.


    Yet history has rarely stopped people from trying.


    Napoleon was identified with the Beast. During other periods, religious interpreters found the Antichrist in popes, emperors, political leaders, revolutionary movements and ideological enemies. Jeffrey C. Pugh, interviewed by the BBC, recalled that his own grandmother once believed Franklin D. Roosevelt was the Antichrist. The New Deal, arriving amid the terror and dislocation of the Great Depression, appeared revolutionary enough to some Americans that biblical language seemed capable of explaining what ordinary politics could not.
    During the Cold War, the Soviet Union and communism occupied similar territory in some apocalyptic interpretations. After September 11, different fears appeared. The candidate changes because the world changes.
    Artificial intelligence could therefore be only the latest object onto which humanity has projected its oldest anxieties.
    Except there is a difference that makes this particular candidate unusual.
    We did not invite Napoleon into our bedrooms to answer questions before we went to sleep. We did not ask the Soviet Union to compose our letters, explain our symptoms, recommend our purchases, teach our children, organize our thoughts and help us decide what was true.
    AI is not standing outside the gates.
    We are carrying it inside.


    The strange attraction of the end of the world


    The belief that history is approaching its final crisis remains much more widespread than many people realize. A large Pew Research Center survey conducted in the United States in 2022 found that 39 percent of American adults believed humanity was living in the “end times.” Among Christians the figure rose to 47 percent, while 63 percent of evangelical Protestants and 76 percent of Protestants in historically Black churches expressed that belief. The survey involved more than 10,000 American adults, so these were not merely the opinions of a tiny apocalyptic subculture.


    There is also a long psychological and historical pattern behind such expectations. Noreen Herzfeld, a theologian who has spent years studying the relationship between religion and artificial intelligence, observes that millenarian movements tend to flourish during periods of social stress, when people feel that events are accelerating beyond their control. In a 2024 chapter for The Cambridge Companion to Religion and Artificial Intelligence, she makes an especially interesting point: modern society projects both salvation and catastrophe onto AI. Some imagine that advanced intelligence will solve disease, scarcity and perhaps even mortality, while others imagine a superintelligence escaping human control and destroying the civilization that created it.

    In that sense, artificial intelligence has already acquired something resembling an eschatology of its own.
    The religious believer may imagine the return of Christ, judgment and the end of the present age, while technological futurists speak about artificial general intelligence, superintelligence, radical life extension or a transformation after which human civilization may never again resemble what came before. The vocabulary is different, yet both stories place humanity on the threshold of an event so large that history will be divided into a before and an after.
    It would be too simple to say that technological futurism is merely religion disguised as engineering, but the resemblance is difficult to ignore. Humans seem remarkably attracted to stories in which ordinary history suddenly opens into something greater, whether that something is salvation or destruction.
    Perhaps what frightens us most about AI is not that we know what it will become, but that we do not.


    Revelation was concerned with deception before it was concerned with technology


    If there is one element of ancient apocalyptic imagery that feels unexpectedly contemporary, it is not the number 666, nor the famous mark, nor even the terrifying beast rising from the sea. It is deception.
    The second beast of Revelation performs convincing signs and persuades people to give their allegiance to the first. Later Christian interpretation associates this figure with the false prophet. Whatever theological interpretation one accepts, the narrative understands that power does not always rule through violence alone; sometimes it rules by controlling what people believe they have seen.


    For most of human history, creating convincing false realities required enormous resources. A forged document could deceive a few people, propaganda could manipulate millions and cinema could create illusions, but each medium retained certain boundaries. A photograph was generally connected to an event that had occurred in front of a camera. A recognizable voice usually belonged to the person speaking. A moving image of a public figure ordinarily meant that the figure had, at some point, stood before a lens.


    Those assumptions are disappearing.
    Generative systems can create faces belonging to people who never existed, reproduce voices, manufacture photographs and generate increasingly convincing video. They can write in the style of a particular person and sustain conversations that feel spontaneous and personal. The barrier separating evidence from fabrication has not vanished completely, but it has weakened enough that the old sentence “I saw it with my own eyes” no longer carries the certainty it once did.


    More troublingly, deception does not always require an AI system to invent something deliberately. The U.S. National Institute of Standards and Technology warns that generative systems can produce “confabulations,” confidently presenting incorrect or fabricated information in ways that users may mistake for reliable knowledge. NIST specifically notes that apparently plausible explanations or invented citations can encourage people to place inappropriate trust in erroneous output.

    This changes something fundamental in the relationship between humans and information.
    The machine does not need to know that it is deceiving us. It does not require hatred, ambition, spiritual corruption or consciousness of any kind. A system designed to predict plausible language can produce false information without possessing any concept of truth, while a human reader can nevertheless experience its answer as authoritative.
    That distinction becomes important because we instinctively associate deception with a deceiver. Someone lies because someone intends to lie. Artificial systems introduce a stranger possibility: deception can emerge without a mind behind the individual sentence intending anything at all.
    The effect on the person receiving the information may be the same.


    An oracle that speaks in our own language

    Human beings have always searched for something that knows more than they do. Ancient people travelled to temples and oracles, studied omens and consulted priests because uncertainty is one of the conditions we tolerate least comfortably. We want to know what will happen to us, whether our choices are correct, whether danger is approaching and whether a hidden order exists behind events that otherwise appear random.
    Modern societies may believe they have left the oracle behind, but perhaps we have merely changed its architecture.
    Instead of climbing the road to Delphi, we open an application.
    The comparison should not be pushed too far, because contemporary AI is built from mathematics, software, data and hardware rather than divine revelation. Yet psychologically the encounter can become surprisingly similar. A question is offered to an entity whose internal processes most users do not understand, and an answer returns almost instantly from a body of information no individual human could possibly hold in memory.


    The voice is calm. It rarely hesitates in the manner a frightened or uncertain person hesitates. It can explain complex subjects in language tailored precisely to the person asking.
    The experience creates an illusion of presence that earlier technologies rarely possessed.


    A search engine gave us pages to investigate. A book gave us the thoughts of an identifiable author. A calculator returned numbers. Conversational AI does something subtly different because it answers us, adjusts to us and continues the exchange. Even when we know intellectually that the system is a machine, ordinary social instincts begin to operate.


    And those systems can persuade.
    A 2025 study published in Nature Human Behaviour examined debates between people and GPT-4. When the AI had access to limited personal information about the human participant and the contest produced a difference in persuasion, the personalized AI was more persuasive substantially more often than its human counterpart. Other experiments published in Nature Communications have also found that messages generated by large language models can shift attitudes on contested issues and can do so at enormous scale and comparatively low cost.


    None of this proves a supernatural prophecy.
    It proves something more immediate: a machine does not need consciousness in order to influence belief.


    The moment when assistance becomes authority


    Imagine that artificial intelligence continues improving without any dramatic “awakening,” without consciousness suddenly appearing inside the machine and without some cinematic moment when humanity realizes that its creation has become alive. The systems simply become more useful, more accurate and more deeply integrated into ordinary institutions.


    A physician consults an AI system because it detects patterns in medical data that a human might overlook. A financial institution uses another because fraud can be identified more efficiently. Courts experiment with AI assistance because thousands of pages of legal material can be reviewed in seconds. Schools adopt personalized systems because each student can receive individual attention. Companies rely on algorithms to screen applications, governments automate administrative decisions, intelligence services analyze threats and military organizations use machine assistance because modern warfare moves faster than human deliberation.


    There need be nothing sinister in any individual step.
    That is precisely what makes the process worth examining.
    If a system is correct more frequently than the human professional using it, ignoring its recommendation may gradually become difficult to defend. Eventually a doctor might need to explain why she rejected the machine rather than why she accepted it. An employee may discover that questioning an automated recommendation is interpreted as inefficiency. A citizen may be told that no person can reverse a decision because the relevant procedure has become too complex for any individual to understand completely.


    Nobody would need to declare that the machine was now in charge.
    Authority could accumulate through convenience.
    This possibility is one reason UNESCO’s global Recommendation on the Ethics of Artificial Intelligence places so much emphasis on human responsibility and oversight. Its framework explicitly states that AI systems should not displace ultimate human responsibility and accountability, precisely because a technologically produced decision can affect real people even when responsibility becomes difficult to locate.

    The warning is almost mundane compared with Revelation, yet its implications are profound.
    A society can surrender authority without ever holding a ceremony of surrender.


    The mark, the marketplace and the seduction of modern parallels


    No passage in Revelation has generated more technological speculation than the description of the mark without which people cannot buy or sell. Over the decades, interpretations have attached themselves to barcodes, credit cards, implanted microchips, biometric systems, digital identification and, more recently, digital currencies and AI-controlled financial infrastructure.


    The pattern itself should make us cautious. When almost every generation discovers that its newest technology appears to fit the same prophecy, the prophecy may be functioning partly as a mirror.
    Yet there is still something worth examining beneath all the speculation.


    For most of history, human existence was only loosely connected to centralized technological systems. A person could possess money without an account, communicate without an electronic identity, travel without leaving a permanent digital trail and purchase necessities without being authenticated by a network.


    That world is disappearing, not because of a secret apocalyptic plan but because digital systems are extraordinarily useful.
    Banking becomes safer when fraud can be detected. Governments function faster when identities can be verified. Borders become more manageable through electronic documents. Businesses reduce costs through automation. Consumers prefer immediate transactions over complicated ones.
    Every individual reason is understandable.
    Together, however, they produce something historically new: a society in which participation in ordinary life increasingly depends upon technological systems that most citizens cannot inspect and no single individual controls.
    The resemblance to Revelation does not establish a prophetic connection, but it helps explain why that connection feels so powerful to some people. Ancient texts described economic participation becoming entangled with allegiance to an oppressive power; modern societies are building increasingly integrated infrastructures through which identity, finance and access can technically be managed on an unprecedented scale.
    The supernatural interpretation remains a matter of faith.
    The infrastructure is real.


    Perhaps the machine never needs to become evil


    Science fiction has taught us to wait for the wrong moment.
    We imagine a laboratory where an AI suddenly becomes conscious, recognizes humanity as inferior and begins plotting its escape. The danger has a beginning, a personality and an intention, which paradoxically makes it comforting because there would be an identifiable enemy.


    History usually produces something messier.
    Institutions can harm people without anyone waking in the morning intending to become evil. Financial systems can destroy lives without feeling greed. Bureaucracies can become cruel without any individual bureaucrat deciding to create cruelty. Propaganda can reshape an entire population even though paper and ink possess no consciousness.


    Why, then, would artificial intelligence require self-awareness before becoming dangerous?
    A system can recommend the wrong medical decision without wanting anyone to suffer. It can reproduce discrimination without understanding prejudice, amplify false information without believing it and persuade an individual without knowing that an individual exists in any human sense of the word.
    Effects do not require intention.
    This may be one of the most important distinctions lost in discussions about AI and the Antichrist. Those who imagine a demonic superintelligence often assume that the machine would somehow need to choose evil. The more realistic danger may be a network of systems doing exactly what they were designed or incentivized to do while producing consequences no one intended and no single person can easily stop.
    In theological language, evil is often personalized.
    In technological systems, catastrophe can be procedural.


    The idol has never needed to be alive


    Christian scripture repeatedly returns to the problem of idolatry, and the popular imagination tends to picture ancient people kneeling foolishly before statues of wood or stone. Yet the deeper idea is more sophisticated: human beings create something with their own hands and then attribute to their creation an authority greater than their own.

    Seen from that perspective, the material from which the idol is constructed is almost irrelevant.
    Stone will do.
    Gold will do.
    Silicon would do just as well.


    Noreen Herzfeld’s work on religion and artificial intelligence has repeatedly returned to the question of image, creation and what happens when humans build intelligent-seeming entities in their own likeness. Her recent exploration of AI as a millenarian project is particularly revealing because she rejects both extremes: the machine as automatic savior and the machine as inevitable apocalypse. We are projecting ancient hopes and fears onto a technology whose future will still depend heavily upon choices made by humans.

    This may be where the theological argument becomes more interesting than the claim that AI itself is Satanic.
    An idol does not need supernatural power for people to worship it. It needs only to be treated as though it possesses an authority that should not be questioned.
    Modern AI systems are demonstrably fallible, yet their linguistic fluency can make uncertainty difficult to perceive. They can sound knowledgeable where their knowledge is incomplete and confident where confidence is unjustified. As their capabilities increase, the temptation to confuse intelligence with wisdom may become stronger.
    Those are not the same thing.
    A system may process more information than any living person and still possess no lived experience, moral responsibility, mortality, love, grief, conscience or understanding of consequence in the human sense.
    Yet if its answer is better often enough, people may stop caring about the distinction.
    That is the moment worth watching.


    Perhaps we have always misunderstood what obedience would look like


    When people imagine the Antichrist, they often imagine a charismatic tyrant demanding worship beneath enormous banners while terrified populations are forced to obey. The image is theatrical because apocalyptic literature itself is theatrical.


    Modern power often behaves differently.
    The most efficient systems rarely need to threaten everyone who uses them. They become indispensable.
    We did not have to be forced into smartphones. We wanted them. Social networks did not invade our homes; we created accounts. Recommendation algorithms did not demand that we surrender hours of attention; they learned how to keep us interested.


    Convenience succeeded where coercion would have failed.
    Artificial intelligence may follow the same path. We will use it because it saves time, then because everyone else uses it, then because institutions expect it and eventually because functioning without it becomes difficult.


    At no particular point will the transformation necessarily feel dramatic.
    That is what makes it mysterious.
    Human beings tend to imagine historical turning points as moments that everyone recognizes while they are happening, yet many of the deepest transformations become visible only afterward. People living through the first decades of industrialization did not wake each morning announcing that they were inside the Industrial Revolution. The old world was simply disappearing around them, one machine, one factory and one migration at a time.
    Perhaps something comparable has already begun.


    When secular science and religious prophecy begin asking the same question

    There is an irony hidden inside all of this. Religious believers are not the only people imagining catastrophic futures involving AI.
    Researchers, engineers, philosophers and governments use an entirely different vocabulary, but they are also discussing scenarios in which advanced systems could create severe harm, manipulate populations, undermine institutions or behave in ways humans struggle to control. NIST develops risk frameworks, UNESCO insists upon human oversight, and researchers experimentally study whether AI can persuade human beings at scale. These are not churches interpreting Revelation; they are institutions confronting technical and social risks.

    The religious language speaks of deception, false authority and allegiance.
    The technical language speaks of misinformation, persuasion, alignment, accountability and loss of human control.
    They are not describing the same thing, and it would be misleading to pretend they are.
    Yet they sometimes appear to be standing on opposite sides of a strange bridge, staring toward the same dark water below.
    Both are asking what happens when human beings create a power they do not fully understand.
    Both are asking whether control can be surrendered before those surrendering it recognize what they have done.
    Both are asking, in very different languages, whether something created to serve us might eventually reshape the conditions under which we live.


    The question Revelation leaves behind


    There is no credible evidence that artificial intelligence is the Antichrist, nor does Revelation contain a hidden technical blueprint describing computers two thousand years before their invention. Historically, much of the book’s imagery makes sense within resistance to Roman imperial power, while the term “Antichrist” itself belongs to other New Testament writings. Treating every new technology as the fulfilment of an ancient prophecy usually reveals more about the fears of the interpreter than about the prophecy itself.

    But perhaps dismissing the entire comparison would be too easy as well.
    Revelation survived for almost two millennia not because every generation correctly identified the Beast, but because the book speaks in images that touch persistent human problems. It is fascinated by power that wishes to become absolute, by appearances that deceive, by economic systems that can reward obedience and punish exclusion, and by the strange moment when political authority stops demanding only compliance and begins demanding something resembling worship.
    Artificial intelligence did not create any of those dangers.
    Human beings did.


    What AI changes is their possible scale.
    For the first time, a single technological system can potentially speak individually to millions of people, adapting its language to each of them while drawing upon more information than any human adviser could possess. Synthetic media can manufacture events that never happened. Digital infrastructures can connect identity, communication and economic life. Algorithms can make consequential judgments without the people affected understanding how those judgments were reached.
    None of this proves the apocalypse.
    Perhaps the opposite is true, and AI will eventually become an ordinary technology whose extraordinary early years seem almost quaint to future generations. Perhaps the fears surrounding it will join the long archive of moments when humanity mistook transformation for the end of the world.
    Yet there is another possibility that requires no demons, no supernatural machines and no secret fulfilment of prophecy.
    We may simply become so accustomed to asking machines what to read, what to believe, whom to trust, how to work, what to choose and eventually how to understand the world that the boundary between assistance and authority fades without anyone noticing exactly when it disappeared.
    If that happens, the question will no longer be whether artificial intelligence has become conscious, whether it possesses a soul or whether some ancient prophet foresaw silicon chips hidden inside a vision of beasts and dragons.


    The question will be far older, and much more human.
    It will be whether we still remember that the thing speaking to us was created by us, whether we still possess the courage to doubt an answer delivered with perfect confidence, and whether we recognize the moment when a tool that once waited for our commands begins quietly determining the world in which those commands are possible.
    Perhaps the most disturbing scenario was never that humanity would build a machine and discover Satan hiding inside it.


    Perhaps it was that we would build a machine ourselves, teach it to speak with the accumulated voices of humanity, place it at the center of our institutions, consult it because it was useful and eventually trust it because everyone else did, until one day we could no longer tell whether we were still using the oracle or whether the oracle had begun, almost imperceptibly, to define reality for us.

    Sources & Further Reading
    BBC News — Lebo Diseko, AI and the Antichrist: Why Some People Believe Artificial Intelligence Is Deceiving Us Into Worshipping Satan, 26 September 2026. BBC News article
    Pew Research Center, In U.S., 39% of adults believe humanity is “living in the end times”, December 2022. Survey of 10,156 U.S. adults; 47% of Christians and 63% of evangelical Protestants surveyed said they believed humanity was living in the end times.

    Noreen Herzfeld — Cambridge University Press, The Eschatological Future of Artificial Intelligence: Saviour or Apocalypse?, in The Cambridge Companion to Religion and Artificial Intelligence, 2024. Herzfeld examines AI as a modern millenarian project onto which societies project both hopes of salvation and fears of catastrophe.

    Open Yale Courses — Yale University, Apocalyptic and Resistance, New Testament History and Literature, Lecture 23. The lecture discusses Revelation in the context of Roman imperial power and explains why many scholars associate 666 — and the manuscript variant 616 — with Nero.

    Encyclopedia of the Bible — Bible Gateway, Antichrist. The term “Antichrist” occurs specifically in the Johannine epistles rather than in the Book of Revelation, an important distinction from later popular interpretations that merge several biblical figures.

    National Institute of Standards and Technology (NIST), Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile, 2024, updated by NIST in 2026. The report discusses risks including AI “confabulation,” in which generative systems can confidently present erroneous or fabricated information.

    UNESCO, Recommendation on the Ethics of Artificial Intelligence. UNESCO emphasizes transparency, accountability and, importantly for our article, the principle that AI systems should not displace ultimate human responsibility and human oversight.

    Salvi, Ribeiro, Gallotti & West — Nature Human Behaviour, On the conversational persuasiveness of GPT-4, 2025. In controlled debates, personalized GPT-4 was more persuasive than human opponents in the study’s key comparison, illustrating why AI-driven persuasion deserves serious attention even without assuming consciousness or malicious intent.

  • AI AND MKULTRA: FROM CHEMICAL MIND CONTROL TO ALGORITHMIC INFLUENCE

    AI AND MKULTRA: FROM CHEMICAL MIND CONTROL TO ALGORITHMIC INFLUENCE

    There was a time when the suggestion that an intelligence agency might secretly experiment on human beings in an attempt to understand, disrupt or manipulate the mind sounded like the raw material of paranoid fiction, yet during the Cold War the United States Central Intelligence Agency created a research program whose surviving records would eventually reveal experiments involving psychoactive drugs, hypnosis, behavioral modification and unsuspecting human subjects, leaving behind one of the most disturbing questions in modern history: how far will institutions go when they become convinced that understanding the human mind is a matter of national security?
    More than seventy years later, the laboratories have changed almost beyond recognition, because the glass of LSD, the hidden safe house and the psychiatrist observing a confused patient through a one-way mirror belong to another technological age, while billions of people now spend hours every day inside digital environments where invisible systems decide which stories rise to the top of a screen, which disappear beneath thousands of others, which emotions receive the greatest amplification and which message appears at precisely the moment when a particular person may be most receptive to it.
    There is no credible evidence that artificial intelligence, social-media algorithms or today’s technology companies represent a secret continuation of MKUltra, and treating that claim as established fact would reduce a fascinating historical comparison to another conspiracy theory, but the absence of such a connection does not make the comparison meaningless, because MKUltra and the algorithmic age are separated by completely different technologies while remaining connected by a question that has never entirely disappeared: if human perception can be altered by changing what reaches the mind, how much influence can be exercised before the person being influenced realizes that anything unusual is happening at all?


    THE COLD WAR SEARCH FOR A DOORWAY INTO THE HUMAN MIND
    Project MKUltra emerged during an atmosphere of intense Cold War anxiety in which American intelligence officials feared that communist governments might have discovered sophisticated methods of interrogation, psychological conditioning or so-called brainwashing, and the possibility that Soviet or Chinese researchers possessed techniques capable of breaking resistance encouraged U.S. agencies to investigate drugs, hypnosis and other methods that might reveal whether human behavior could be deliberately modified.
    What began in 1953 was not one neatly organized experiment but a sprawling collection of projects that reached into universities, hospitals, research foundations and other institutions, often through funding arrangements designed to obscure the CIA’s involvement, while many researchers involved in individual studies apparently did not know who ultimately stood behind the money. When previously overlooked financial records were discovered during the 1970s, the U.S. Senate investigation identified 149 MKUltra subprojects, along with 185 nongovernmental researchers and assistants and 80 institutions associated with the recovered material, while the documents themselves referred to research involving behavioral modification, drug acquisition, human testing and the surreptitious administration of drugs.
    The numbers alone make the program remarkable, but they do not explain why MKUltra became so deeply embedded in modern conspiracy culture, because what transformed it from an obscure intelligence project into something almost legendary was the discovery that at least some people had become experimental subjects without knowing they were participating in an experiment at all.
    During the 1977 Senate hearings, CIA Director Stansfield Turner acknowledged evidence supporting unwitting testing in several of the recovered MKUltra subprojects, while testimony concerning CIA safe houses described individuals encountered in bars and subsequently brought to locations where drugs could be tested under covert observation; the surviving records were incomplete, and witnesses repeatedly warned senators not to infer more than the documentation could prove, yet the central fact was no longer disputable, because the CIA had conducted experiments in which unsuspecting people were exposed to drugs while their reactions were observed.


    WHEN LSD BECAME AN INTELLIGENCE TOOL
    Among the many substances explored during this period, LSD occupied a special place in the imagination of intelligence researchers because its ability to profoundly alter perception, emotion and a person’s sense of reality suggested possibilities that seemed extraordinary in an age obsessed with interrogation and psychological warfare, particularly if a chemical could produce confusion, weaken resistance or temporarily destabilize someone’s confidence in his own senses.
    The disturbing element was not simply that LSD was studied, because the substance was also the subject of legitimate psychiatric and scientific interest during the same era, but that the CIA wanted to understand what happened when a person received such a drug without knowing that it had been administered, a requirement that transformed some experiments from questionable research into profound violations of informed consent.
    The notorious CIA safe-house operations later associated with the name Operation Midnight Climax grew from this logic, because the agency wanted environments in which unwitting subjects could be observed while remaining unaware that anything resembling a government experiment was taking place, and testimony before the Senate described safe houses equipped for covert observation, including references to two-way mirrors and individuals brought in after contacts made in social settings. Although decades of retelling have added sensational claims that are not always supported by surviving documents, the official hearing record itself confirms enough to make embellishment unnecessary.
    The real horror of MKUltra therefore lies less in the mythology of a perfect mind-control drug, which the program never produced, than in a much more believable and historically documented process through which researchers gradually accepted the idea that the mind of another human being could become an experimental territory without that person’s knowledge.


    FRANK OLSON AND THE EXPERIMENT THAT ENDED IN A HOTEL WINDOW
    No episode illustrates the danger of that philosophy more powerfully than the death of Frank Olson, a U.S. Army scientist who worked in biological research and attended a gathering of Army and CIA personnel in November 1953, where LSD was secretly placed in a drink consumed by Olson and several other men as part of an experiment whose full purpose they had not been told in advance.
    According to the congressional record, colleagues described Olson before the experiment as professionally respected and apparently psychologically normal, yet after receiving LSD he became increasingly distressed, agitated and troubled, eventually requiring medical attention and traveling to New York with CIA-associated personnel for consultations with Harold Abramson, a physician experienced with LSD whose research had received indirect CIA support.
    During the early hours of November 28, after days of psychological turmoil, Olson went through the closed window of a tenth-floor room at New York’s Statler Hotel and fell to his death, while the CIA subsequently concealed important circumstances surrounding the experiment from his family and attempted to prevent the death from becoming connected publicly with the agency. The Senate investigation later reconstructed much of this sequence from internal memoranda and testimony, although arguments over whether Olson died by suicide or under more sinister circumstances continued for decades and produced theories that extend beyond what the surviving evidence can firmly establish.
    The case remains chilling precisely because one does not need to accept the most dramatic later theories to understand its significance, since the documented sequence is extraordinary enough: a scientist was unknowingly given a powerful hallucinogen during an intelligence experiment, his psychological condition deteriorated severely, and eight days later he was dead.


    DONALD EWEN CAMERON AND THE ATTEMPT TO BREAK PERSONALITY BEFORE REBUILDING IT
    If Frank Olson’s story reveals what could happen when an unsuspecting person encountered a psychoactive drug, the experiments associated with psychiatrist Donald Ewen Cameron at Montreal’s Allan Memorial Institute reveal an even more ambitious idea, because Cameron became interested in treatments intended to disrupt existing patterns of thought before attempting to construct new psychological responses.
    McGill University’s archival record describes the Montreal experiments conducted at the Allan Memorial Institute between 1957 and 1964 and identifies methods including “psychic driving,” drug-induced sleep, electroconvulsive therapy and sensory deprivation, while also confirming that the work received CIA funding as part of MKUltra.
    Cameron’s concept of psychic driving involved repeated recorded messages intended to influence patients after existing psychological patterns had been weakened through other intensive treatments, and although the work was presented within a psychiatric framework rather than as a cinematic attempt to create obedient agents, its connection with CIA behavioral research transformed it into one of the darkest chapters associated with MKUltra, particularly because many of the people subjected to these procedures were already vulnerable psychiatric patients who could not have understood the intelligence context surrounding the funding.
    The significance of Cameron’s work extends beyond the specific techniques used, because it demonstrates how the search for influence could move from drugs toward something conceptually broader: the attempt to alter the informational and psychological environment surrounding a human being until ordinary patterns of perception and response began to change.


    THE FILES THAT VANISHED AND THE MYSTERY THEY LEFT BEHIND
    Much of what the public now knows about MKUltra survived almost by accident, because extensive program records were destroyed in 1973, while the financial files later uncovered had escaped destruction largely because they had been stored separately from material researchers initially searched for during earlier investigations. The Senate hearing noted that the newly discovered folders were primarily financial records containing vouchers, approvals and accounting documents rather than complete operational reports, which meant investigators could reconstruct the scope of many projects without recovering every detail of what had occurred.
    This destruction created the perfect environment for mythmaking, because whenever documents disappear from a secret intelligence program, the missing pages can become more powerful in the public imagination than the pages that survived, allowing almost any later theory to be projected into the gaps.
    Yet those gaps should not tempt us to confuse possibility with evidence, because the strongest way to understand MKUltra is not to enlarge it into a universal explanation for every alleged mind-control story but to recognize that the documented history is already unsettling enough: institutions with enormous resources genuinely studied behavioral modification, secretly administered drugs to some people, concealed sponsorship of research and later destroyed significant portions of the record.


    WHEN THE LABORATORY MOVED FROM THE HOSPITAL TO THE SCREEN
    The modern world appears completely different until we examine what digital systems actually do, because social-media platforms and recommendation engines continuously alter the informational environment surrounding their users, selecting some material for visibility while allowing other material to disappear almost entirely, then measuring the behavioral consequences through clicks, pauses, shares, comments, watch time and countless other signals.
    Unlike MKUltra, this process generally has no secret intelligence officer slipping chemicals into a drink and no researcher attempting to erase personality, yet it possesses one capability Cold War experimenters could scarcely have imagined: the possibility of observing the reactions of millions of people simultaneously while changing what different groups see.
    A user might assume that scrolling is a passive activity, but every decision provides information from which a system can learn, because the video watched twice may reveal more than the video liked once, the article abandoned after five seconds says something different from the article read to the end, and the content that provokes anger, fascination or fear can become statistically distinguishable from material that produces indifference.
    This does not mean that an algorithm understands the human mind as a psychologist would, because it may have no concept of fear, ambition, loneliness or political identity in any human sense, yet it can still become increasingly effective at predicting which stimulus is likely to produce which response.
    At that point, the difference between predicting behavior and shaping the environment in which behavior occurs becomes surprisingly difficult to define.


    THE FACEBOOK EXPERIMENT THAT ALTERED 689,003 NEWS FEEDS
    One of the clearest demonstrations of this new experimental scale appeared in 2014, when researchers published the results of a Facebook study involving 689,003 users, whose News Feeds had been altered during one week in 2012 so that some participants encountered less positive emotional content while others encountered less negative emotional content.
    The researchers then measured the emotional language those users subsequently produced in their own posts and found small but statistically detectable changes corresponding to the emotional material they had been exposed to, providing experimental evidence that adjusting the emotional environment of a social-media feed could alter subsequent emotional expression even without direct face-to-face interaction.
    The effect itself was modest, and the experiment certainly did not demonstrate that Facebook could remotely control people’s emotions, but the ethical controversy surrounding the study revealed something historically interesting, because most participants had no ordinary understanding that their information environment had been altered for a psychological experiment.
    The comparison with MKUltra must remain proportionate, since reducing positive posts in a News Feed is obviously not equivalent to secretly administering LSD, yet the underlying question feels strangely familiar: what does informed consent mean when the subject does not know that the environment itself has been experimentally modified?


    CAMBRIDGE ANALYTICA AND THE VALUE OF KNOWING WHAT A PERSON IS LIKE
    The Cambridge Analytica scandal added another element to the emerging picture by demonstrating how apparently trivial digital behavior could be transformed into psychological profiles intended for political targeting, because according to the U.S. Federal Trade Commission, data collected through Aleksandr Kogan’s Facebook application was used to generate personality scores that were subsequently matched with American voter records for profiling and targeted advertising.
    The FTC alleged that the application collected information from hundreds of thousands of direct users and tens of millions of their Facebook friends, many of whom never interacted with the application themselves, while Cambridge Analytica sought to use Facebook information to predict personality traits and provide voter profiling and microtargeting services.
    Claims about Cambridge Analytica’s actual power were sometimes exaggerated after the scandal became famous, and there is no convincing evidence that its psychological profiling gave it a magical ability to determine election outcomes, but the larger lesson was difficult to dismiss: information that appears meaningless when considered individually can become extremely valuable when combined across millions of observations.
    A political consultant no longer needed to ask a voter directly what frightened, motivated or angered that person if enough behavioral data could be analyzed to make a useful prediction.


    THE ALGORITHM DOES NOT NEED TO TELL YOU WHAT TO BELIEVE
    The most powerful form of algorithmic influence may therefore have little resemblance to direct persuasion, because a system does not necessarily need to convince someone that the world is dangerous if it can repeatedly show that person dangerous events until danger begins to feel omnipresent.
    If stories about violent crime hold a user’s attention longer than stories about declining crime statistics, the algorithm may gradually provide more robberies, assaults and frightening footage without ever making the explicit statement that society is collapsing, while the person exposed to that stream of information may slowly develop a perception of the world based not on everything that exists but on everything the system has learned will keep that particular person watching.
    The same mechanism can operate around politics, immigration, war, health, conspiracy theories or social conflict, because algorithms optimized for engagement do not necessarily require ideological intentions when emotionally charged material happens to perform better than calm explanation.
    This creates an unsettling possibility in which nobody needs to sit inside a secret control room instructing the machine to amplify fear, anger or division, because those characteristics can emerge simply because they generate measurable reactions.


    THE 2026 X EXPERIMENT: WHAT HAPPENS WHEN THE FEED CHANGES?
    In February 2026, researchers publishing in Nature reported a seven-week field experiment involving active U.S. users of X who were randomly assigned to experience either an algorithmic feed or a chronological one, providing unusually direct evidence about what can happen when the mechanism selecting information is altered.
    Among participants who moved from a chronological feed to X’s algorithmic feed, the researchers observed increased engagement as well as measurable shifts toward more conservative positions on certain policy priorities, perceptions of criminal investigations involving Donald Trump and views concerning the war in Ukraine, while users exposed to the algorithmic feed also became more likely to follow conservative political activist accounts that could continue shaping their information environment afterward. The authors emphasized important limitations, including the fact that the findings concerned one platform during one specific period and did not demonstrate comparable effects on partisanship or every political attitude, but their broader conclusion was difficult to ignore: under some real-world conditions, changing the algorithm that chooses what people see can causally influence both online behavior and political opinion.
    A separate Nature study published later in 2026, involving approximately 2,000 participants using experimentally controlled feeds around the 2024 U.S. presidential election, found that engagement-based ranking amplified intergroup, moralized and emotional information and affected perceptions surrounding partisan hostility, reinforcing the idea that algorithms can alter not only which opinions become visible but also the emotional atmosphere through which people interpret the behavior of others.
    This distinction matters enormously because influence does not always require changing what someone believes directly; sometimes changing what that person believes everyone else believes can reshape the social reality in which future decisions are made.


    ARTIFICIAL INTELLIGENCE ADDS SOMETHING THE OLD ALGORITHMS COULD NOT DO
    Recommendation systems primarily decide which existing messages people encounter, while generative artificial intelligence introduces another possibility because an advanced language model can create the persuasive message itself, adapting arguments, vocabulary and tone with a speed that human persuaders could never reproduce at comparable scale.
    A 2025 study published in Nature Communications, based on three preregistered experiments involving 4,829 participants, found that people exposed to persuasive messages generated by large language models showed measurable shifts in their attitudes toward several public-policy questions compared with participants who received neutral messages, while the AI-generated persuasive material performed broadly similarly to messages produced by ordinary human writers. The effects were not enormous and did not demonstrate irresistible persuasion, yet the researchers emphasized an implication that becomes much more significant at scale: persuasive political messages can now be generated quickly, cheaply and in enormous quantities.
    The twentieth-century intelligence researcher dreamed of discovering a technique powerful enough to work on almost anyone, but artificial intelligence points toward a completely different model in which there may never need to be one universal persuasive formula, because a system could theoretically generate different messages for different psychological profiles and continuously adjust them according to how audiences respond.
    The old question was whether one could find the key to the human mind.
    The new question is whether millions of different keys can be manufactured automatically.


    MKULTRA AND AI ARE NOT THE SAME, WHICH IS EXACTLY WHY THE COMPARISON MATTERS
    It would be historically careless to describe social media or artificial intelligence as “MKUltra 2.0,” because MKUltra involved intelligence agencies, covert experimentation, psychoactive drugs and profound violations of consent that belong to a very specific historical context, while contemporary algorithms generally exist within commercial platforms whose primary purposes involve recommendation, advertising, communication and engagement.
    What makes the comparison meaningful is therefore not a secret institutional connection but a transformation in the philosophy of influence.
    MKUltra researchers explored whether the mind could be disrupted from the outside through chemical and psychological intervention, while modern digital systems increasingly learn by observing the mind indirectly through behavior, accumulating patterns until they can predict which information is most likely to attract, frighten, persuade or retain a particular person.
    One approach attempted to penetrate the mind by force.
    The other can surround the mind with a customized information environment.
    One searched for the perfect chemical.
    The other searches continuously for the next piece of content most likely to produce a measurable response.


    THE MOST DISTURBING POSSIBILITY MAY BE THAT THERE IS NO MASTER CONTROLLER
    Conspiracy theories often imagine control as something centralized, intentional and secret, with a small group sitting behind a curtain and directing the thoughts of millions, yet algorithmic systems introduce a stranger possibility because harmful patterns can emerge even when nobody has deliberately designed the final outcome.
    If a platform rewards engagement and the system discovers through billions of interactions that anger keeps users present longer than calm discussion, sensationalism spreads faster than careful uncertainty and frightening claims generate more comments than reassuring explanations, the algorithm can amplify precisely those characteristics without possessing a political ideology, a psychological theory or any conscious desire to manipulate society.
    This is why asking only “Who controls the algorithm?” may miss the more important question, because the answer may sometimes be less revealing than asking “What is the algorithm being rewarded for?”
    A system optimized for attention does not need to hate, deceive or believe anything in order to learn that particular emotional reactions are profitable.


    FROM THE GLASS OF LSD TO THE GLOWING SCREEN
    Frank Olson consumed a drink in 1953 without knowing that a chemical experiment was about to alter his experience of reality, while patients in Montreal entered psychiatric treatment without understanding the full intelligence context surrounding research that would later become connected publicly with MKUltra, and the surviving documents eventually revealed a world in which the pursuit of behavioral knowledge had crossed boundaries that now seem almost impossible to defend.
    The twenty-first century presents a profoundly different world in which most people voluntarily carry the experimental environment with them, willingly return to it dozens of times every day and continuously provide the behavioral signals from which increasingly sophisticated systems learn, yet voluntary participation does not automatically answer every ethical question when the mechanisms guiding attention remain largely invisible to those being guided.
    There is no LSD hidden inside the smartphone, no evidence that today’s AI companies secretly inherited MKUltra and no scientific basis for claiming that algorithms can transform human beings into programmable machines, but there is growing evidence that changing information feeds can influence emotional expression, alter perceptions, affect online behavior and, under certain conditions, shift political attitudes.
    Perhaps the Cold War researchers were therefore searching for something more dramatic than they needed when they imagined that control over the human mind would require a miraculous chemical or an irresistible psychological technique, because the more subtle form of influence may not involve taking control of the mind itself at all.
    It may be enough to control the sequence of reality placed in front of it.
    If one person repeatedly sees fear, another repeatedly sees outrage and a third repeatedly sees confirmation of everything he already believes, each may eventually inhabit a slightly different world while remaining convinced that the screen has merely shown reality as it exists.
    The laboratory has become invisible, the experiment may resemble ordinary life, and the person inside it does not necessarily feel controlled, manipulated or even observed.
    He simply opens the phone, begins to scroll, and waits to see what the algorithm has decided should exist next.


    SOURCES AND FURTHER READING
    The historical material concerning Project MKUltra, its recovered 149 subprojects, researchers, institutions, unwitting experiments, CIA safe houses, Frank Olson and the destruction of records is based primarily on the 1977 Joint Hearing of the U.S. Senate Select Committee on Intelligence and the Subcommittee on Health and Scientific Research.
    Information concerning Donald Ewen Cameron and the Montreal experiments is supported by the McGill University Archival Collections, which document the Allan Memorial Institute experiments and their relationship with CIA-funded MKUltra research.
    The Facebook emotional-contagion experiment is documented in the peer-reviewed 2014 study “Experimental Evidence of Massive-Scale Emotional Contagion Through Social Networks,” involving 689,003 users.
    Information concerning Cambridge Analytica’s Facebook data collection, personality profiling and political targeting is based on findings published by the U.S. Federal Trade Commission.
    The modern discussion of algorithmic influence draws on the 2026 Nature studies examining X’s feed algorithm and engagement-based social-media ranking.
    The discussion of AI-generated persuasion is based on the 2025 Nature Communications study “LLM-generated messages can persuade humans on policy issues,” involving 4,829 participants across three preregistered experiments.

  • Who Controls Reality: Governments, Algorithms — or Our Own Minds?

    Who Controls Reality: Governments, Algorithms — or Our Own Minds?

    There is an uncomfortable assumption hidden beneath almost everything we do: when we open our eyes in the morning, read the news, remember yesterday, form an opinion about another person, decide what frightens us, determine whom we trust, or convince ourselves that we have reached a conclusion independently, we usually assume that the reality inside our minds corresponds reasonably well to the reality outside them, even though neuroscience, psychology, history and the technological environment in which we now live suggest that this relationship is considerably more complicated than it appears.
    The modern fascination with the idea of a “Matrix” often leads us toward spectacular possibilities involving simulated universes, hidden programmers or artificial worlds, yet there may be a version of the Matrix that requires neither a supercomputer nor a secret civilization operating beyond the boundaries of our universe, because human beings have always experienced reality through filters, while governments, religions, political movements, commercial institutions, media organizations and, more recently, digital algorithms have learned how extraordinarily powerful those filters can become.
    What makes the problem especially difficult is that manipulation rarely works by replacing reality completely with an obvious lie, because human beings would probably reject such an intrusion rather quickly; instead, influence is usually more subtle, operating through selection, repetition, emphasis, emotional framing, omission and the ordering of information, so that the individual continues to feel free while gradually inhabiting a world in which certain events seem enormously important, others virtually disappear, some people appear constantly threatening, other people appear trustworthy, and particular interpretations become so familiar that they eventually feel less like interpretations and more like common sense.
    The unsettling question, therefore, is not simply whether someone is controlling reality, because reality itself may remain untouched, but whether someone can control enough of what reaches our attention to influence the version of reality that exists inside our minds.


    WE HAVE NEVER EXPERIENCED THE WORLD DIRECTLY
    Before governments, newspapers, television networks or social-media companies can influence perception, another system has already begun selecting reality for us, and that system is the human brain itself.
    The world surrounding us contains vastly more information than consciousness could possibly process simultaneously, which means that perception cannot operate like a perfect camera recording every detail before transmitting an objective copy to an inner observer; instead, the brain prioritizes some signals, ignores others, compares incoming information with previous experience, uses context to interpret ambiguity and continuously makes predictions about what is most likely to be present.
    Modern neuroscience increasingly treats prediction as an important part of perception, with research describing the brain not merely as a passive receiver of sensory information but as a system in which expectations, previous knowledge and incoming sensory evidence interact to produce the perceptual experience that eventually reaches awareness.
    This does not mean that we hallucinate the entire world or invent reality freely according to our wishes, because the external environment constrains perception continuously, but it does mean that what we consciously experience is already the result of interpretation, prioritization and reconstruction, rather than an untouched stream of objective information entering the mind.
    A 2026 perspective in Nature Reviews Neuroscience went even further in describing categorization as something embedded throughout neural processing rather than as a final intellectual label added after perception has occurred, suggesting that the brain begins organizing incoming information into meaningful categories remarkably early in the process by which experience is constructed.
    This matters because categories are never entirely innocent.
    Once something has been categorized as dangerous, trustworthy, foreign, familiar, beautiful, disgusting, normal, abnormal, successful or threatening, subsequent information is interpreted through that classification, while the category itself can become increasingly difficult to notice precisely because it begins to feel like a property of the external world rather than a framework supplied partly by the mind.
    The first architect of our Matrix, therefore, may not be a government or an algorithm at all, because long before anyone tries to manipulate us, our own nervous system has already reduced an unimaginably complicated universe into a manageable model.


    THE BRAIN DOES NOT SHOW US EVERYTHING — IT SHOWS US WHAT MATTERS
    At every moment, enormous amounts of visual, auditory and bodily information compete for limited processing resources, yet only a fraction of what reaches the senses becomes something we consciously notice, remember or use to guide behavior, which is why attention is not simply a spotlight illuminating a pre-existing complete picture but one of the mechanisms determining which parts of that picture become psychologically significant.
    Research on visual priority coding has emphasized precisely this problem, showing how perception is shaped by multiple forms of priority, including goals, salience, previous experience and behavioral relevance, while much of the available sensory environment remains outside conscious processing.
    This ordinary neurological fact has enormous social consequences, because whoever repeatedly captures attention does not need to manufacture an entirely fictitious universe; it may be sufficient to determine which fragments of the existing universe remain continuously visible.
    Imagine two people living on the same street, under the same government and during the same historical period, while one spends several hours each day consuming stories about crime, social collapse and political betrayal, whereas the other receives a continuous stream of technological breakthroughs, successful businesses, scientific discoveries and personal-development advice, and although neither feed necessarily contains fabricated information, the psychological worlds produced by those selections may eventually become profoundly different.
    Both people can sincerely insist that they are simply observing reality.
    Both may be correct about many of the individual facts they have encountered.
    Yet neither is seeing the whole.
    This difference between false information and selective reality is one of the most important distinctions in understanding modern influence, because a person does not need to be lied to in order to be manipulated; sometimes it is enough to show them accurate information in a particular proportion, sequence and emotional context until that selection begins to represent the world itself.


    GOVERNMENTS DISCOVERED THE POWER OF THE SELECTED WORLD LONG BEFORE ALGORITHMS EXISTED
    Political authorities have understood for centuries that controlling information can be almost as important as controlling territory, because armies may occupy cities, laws may regulate behavior and police forces may punish disobedience, yet stable power requires something more subtle: a believable explanation of why the existing order is necessary, legitimate or inevitable.
    Ancient rulers carved victories into stone while defeats disappeared from official monuments, imperial courts controlled access to information, religious and political authorities licensed certain forms of knowledge while restricting others, wartime governments censored military information and organized propaganda campaigns, and twentieth-century mass communication made it possible to coordinate narratives on a scale that earlier regimes could barely have imagined.
    The most effective propaganda was rarely limited to invented facts, because selection could be considerably more persuasive: one atrocity could be shown repeatedly while another remained invisible, one economic statistic could dominate public discussion while another received almost no attention, one enemy could be represented through its worst members while one’s own group was represented through its best ideals, and a complicated conflict could gradually be compressed into a morally satisfying story containing heroes, victims and villains.
    Under such conditions, the population does not necessarily need to be ordered what to think, because controlling what people repeatedly think about can already exert substantial influence over the boundaries within which opinions are formed.
    This insight is closely related to what communication scholars have long discussed through concepts such as agenda-setting and framing, in which the prominence, presentation and contextualization of information influence which issues people regard as important and how those issues are understood, even when audiences retain considerable freedom to disagree with the message itself.
    The old propaganda machine therefore operated by controlling scarcity, because information was difficult to produce and distribute widely, whereas the digital world has created the opposite problem: information is now so abundant that power increasingly lies not only in preventing information from appearing but in deciding which information rises from the ocean long enough to be seen.


    THE ALGORITHM DOES NOT HAVE TO HATE YOU, LOVE YOU OR UNDERSTAND YOU
    This is where modern algorithms become fundamentally different from the propaganda ministries of earlier centuries, because an algorithm does not require an ideology, personal intention or secret plan in order to alter the informational environment surrounding millions of people.
    A recommendation system can simply be optimized for objectives such as engagement, viewing time, relevance, retention, clicks or predicted user satisfaction, while the consequences emerge from the interaction between that objective and human psychology.
    If emotionally charged material keeps people watching longer, an engagement-driven system may learn to show more emotionally charged material without anybody programming the instruction “make people angry”; if content confirming someone’s existing interests receives stronger engagement, personalization can progressively concentrate similar material around that person without anyone issuing the instruction “build an echo chamber”; and if controversy generates replies, shares and prolonged attention, controversial material can acquire an evolutionary advantage within the information ecosystem simply because it performs well according to the platform’s chosen metric.
    The distinction matters enormously because it replaces the comforting image of a single villain controlling the machine with something more difficult to recognize: systems can produce powerful social consequences even when nobody explicitly intended every consequence they produce.
    The modern Matrix may therefore have no architect sitting behind a screen deciding precisely what each individual should believe, because the system can adapt automatically, testing millions of tiny predictions about what will keep people watching, clicking, reacting and returning.


    THE EXPERIMENTS ARE MORE COMPLICATED THAN THE POPULAR STORY
    It would be convenient to claim that scientists have already proven that social-media algorithms systematically brainwash users, but the evidence is considerably more complicated, and that complexity makes the subject far more interesting than the simplistic version.
    During the 2020 United States presidential election, researchers conducted large-scale experiments involving Facebook and Instagram users, including an experiment in which participants received reverse-chronological feeds instead of the platforms’ default algorithmically ranked feeds, and although changing the feed substantially altered what users encountered and how much time they spent on the platforms, researchers did not find significant corresponding changes in several major political attitudes during the study period.
    Another large Facebook experiment involving more than 23,000 participants reduced exposure to content from politically like-minded sources by roughly one-third and succeeded in changing the informational environment surrounding those users, including increasing exposure to cross-cutting sources, yet researchers again found no measurable effects across several preregistered political-attitude outcomes, including ideological extremity and affective polarization.
    If those studies had been the final word, one might reasonably conclude that algorithms change what people see without necessarily changing what people believe.
    Then another experiment complicated the picture.
    Research published in Nature on February 18, 2026 examined active users of X who were randomly assigned to experience either an algorithmic feed or a chronological one during a seven-week field experiment conducted in 2023, and the researchers found that switching users from a chronological feed to the platform’s algorithmic feed increased engagement while also shifting several measured political attitudes toward more conservative positions, including policy priorities and attitudes connected with specific contemporary political issues.
    The researchers also found that the algorithmic feed promoted more conservative content and reduced exposure to posts from traditional media while encouraging users to follow more conservative political-activist accounts, and particularly intriguing was the asymmetry they observed: turning the algorithm on produced measurable effects, whereas subsequently turning it off did not simply reverse those effects, partly because users continued following accounts they had discovered during their algorithmic exposure.
    These findings should not be generalized carelessly to every platform, country, political issue or user, but they undermine two equally simplistic beliefs: that recommendation algorithms inevitably control people’s opinions, and that recommendation algorithms merely organize harmless entertainment without affecting the political world.
    The evidence instead suggests something messier and more realistic, because effects depend on the platform, the design of the algorithm, the material being amplified, the duration of exposure, the existing beliefs of the user and the surrounding information environment.
    In other words, there may not be one universal Matrix.
    There may be millions of partially overlapping ones.


    WHEN THE FEED LEARNS WHO YOU ARE
    Personalization introduces an additional difficulty because the modern information environment does not simply broadcast one identical message to an entire population, as traditional television or newspapers once largely did; instead, digital systems can learn from behavior and construct increasingly individualized information environments.
    Every pause, click, follow, search, replay, share, hide, like and watch-time signal can help a recommendation system estimate what kinds of content are likely to keep a particular user engaged, and over time this means that two people opening the same platform from neighboring houses may encounter radically different worlds.
    One person’s internet may appear filled with economic catastrophe, another person’s with investment opportunities, another with war, another with celebrity scandals, another with religious prophecy, another with alternative medicine, another with technological optimism and another with evidence that society is approaching irreversible collapse.
    The important point is not that one of these realities must be completely false, because fragments of evidence may exist for many of them, but that repeated exposure affects psychological availability, which means that the events easiest to remember often begin to feel more common, more representative or more important than events encountered less frequently.
    If the world you see every day is selected according to what previously held your attention, personalization can create a strange feedback loop in which your existing fears and interests help determine what you see, what you see reinforces those fears and interests, and the reinforced version of yourself subsequently trains the system to provide even more of the same.
    At that point it becomes surprisingly difficult to identify where the algorithm ends and the individual begins.


    REPETITION CAN MAKE AN IDEA FEEL MORE TRUE
    Human vulnerability to repetition existed long before social media, but digital platforms can produce repetition at extraordinary scale, particularly when multiple accounts, videos, comments and recommendation chains circulate similar claims through slightly different forms.
    Psychologists have studied what is commonly known as the illusory truth effect, in which repeated statements can feel more credible partly because familiarity makes them easier to process, and research reviews have found that repetition can influence perceived truth even when individuals possess relevant previous knowledge, although the effect is not unlimited and does not simply erase everything a person already knows.
    This mechanism helps explain why repetition has always been attractive to advertisers, political movements, propagandists and rumor networks, because familiarity produces a subtle cognitive transformation in which an idea can move from strange, to recognizable, to familiar, and finally to something that seems as though one has “heard it everywhere.”
    The phrase “everyone is saying it” can become psychologically powerful even when “everyone” consists of the same claim repeatedly circulating through an interconnected network.
    Digital platforms intensify this problem because the same basic narrative may reach a person through a news headline, a meme, a short video, a comment, an influencer, a screenshot and a recommended post, creating the subjective impression of multiple independent confirmations even when the information ultimately originated from only a small number of sources.
    Reality then acquires an echo.
    The echo is mistaken for consensus.
    Consensus begins to resemble evidence.
    This progression is precisely why distinguishing the original source of a claim from the number of times it has been encountered has become increasingly important in the modern information environment.


    BUT OUR OWN MINDS ARE NOT PASSIVE VICTIMS
    It would be convenient, and psychologically flattering, to blame governments and algorithms for everything we believe incorrectly, because such an explanation allows us to imagine a fundamentally rational mind corrupted only by external forces; unfortunately, decades of psychological research suggest that humans were already capable of constructing biased interpretations of reality long before the first newspaper, television network or recommendation engine existed.
    We seek patterns in incomplete information, remember emotionally meaningful events more easily than ordinary ones, interpret ambiguous evidence through previous beliefs, prefer information that fits existing identities, estimate probabilities using memorable examples, simplify complicated groups into categories and frequently construct explanations after decisions have already been influenced by processes outside conscious awareness.
    Confirmation bias becomes particularly powerful because human beings do not merely collect facts before forming beliefs; once important beliefs become connected with identity, community or morality, new information is no longer evaluated on neutral ground, since accepting certain evidence may threaten belonging, self-respect or an entire interpretation of the world.
    This helps explain why giving people additional information does not always produce convergence toward a single conclusion, because the same evidence can be interpreted differently depending upon the conceptual framework within which it arrives.
    The algorithm therefore does not create every weakness it exploits.
    It finds weaknesses already present.


    THE MOST EFFECTIVE MATRIX IS THE ONE WE HELP BUILD OURSELVES
    Imagine a system that gradually learns what frightens you, what angers you, what confirms your beliefs, what kind of face makes you stop scrolling, which words make you click, which political stories keep you watching and which mysteries prevent you from putting down your phone, while every response you make provides additional information allowing the system to predict your next response more accurately.
    The system does not need to force you to watch anything.
    You select the content voluntarily.
    Yet your selections train the system that determines which options you will receive next.
    This creates a form of circular influence in which the machine learns from the person while the person learns from the machine, meaning that neither side alone completely controls the final informational environment.
    The user says, in effect, “show me more of what interests me,” while the algorithm replies by presenting a progressively optimized version of that interest, after which the user interprets the abundance of similar material as evidence that the subject must be extraordinarily important.
    A fear becomes a feed.
    The feed strengthens the fear.
    The strengthened fear trains the feed.
    Although this cycle can occur around harmless interests such as cooking, travel, gardening or music, the same architecture becomes far more consequential when applied to politics, health misinformation, conspiracy theories, social hostility or perceptions of danger.


    THE GOVERNMENT, THE ALGORITHM AND THE BRAIN CAN FORM A SINGLE CHAIN
    The deepest mistake may be asking which one controls reality as though governments, algorithms and human psychology were competing explanations, because in practice they can interact.
    A government, political organization, company or activist movement produces a message.
    An algorithm evaluates how users respond to it.
    Emotionally compelling versions receive stronger engagement and therefore greater distribution.
    Users encounter those versions repeatedly.
    Existing psychological tendencies determine which users are most receptive.
    Those users share the message, creating additional signals that encourage further distribution.
    Journalists notice the online attention and begin reporting on the controversy.
    Political institutions respond to the resulting public debate.
    The response generates new content.
    The cycle begins again.
    At no single moment does one actor completely control the entire process, yet collectively the system can determine what millions of people discuss for days while thousands of other events disappear from public attention almost completely.
    This is why modern information power can be more difficult to recognize than traditional censorship.
    A censor tells you that something cannot be seen.
    An algorithmic environment can simply place something so far beneath everything else that you never realize you were not shown it.


    WHAT HAPPENS WHEN TWO PEOPLE NO LONGER SHARE THE SAME REALITY?
    Democratic societies have always contained disagreement, and disagreement itself is neither abnormal nor necessarily dangerous, because people can interpret the same evidence differently while still sharing a sufficient factual foundation to argue productively.
    A more difficult situation emerges when informational environments diverge so dramatically that different groups no longer disagree merely about the meaning of events but about which events exist, which sources can be trusted, which institutions are legitimate and which facts deserve consideration at all.
    At that stage, debate becomes extraordinarily difficult because each side experiences the other’s position not simply as mistaken but as inexplicable.
    “How can they possibly believe that?” becomes one of the defining questions of the era.
    The answer may be partly that they have not been living inside precisely the same informational world.
    They may inhabit the same country while experiencing entirely different histories of the previous week.
    One group repeatedly sees evidence of threat while another sees evidence of exaggeration, one sees corruption while another sees persecution, one sees collapse while another sees progress, and because every side encounters hundreds of apparently confirming examples, each begins to wonder whether the others are ignorant, dishonest or irrational.
    What disappears is not necessarily truth itself but a shared map of reality.


    WHO, THEN, CONTROLS REALITY?
    Governments can control information, although their power is never absolute.
    Corporations can influence attention, although users retain agency.
    Algorithms can determine exposure, although their effects vary considerably across platforms and individuals.
    Media organizations can frame events, although audiences can reject the frame.
    Political movements can repeat narratives, although repetition cannot transform every falsehood into belief.
    And the human brain can distort perception, although the external world continuously constrains the stories we tell ourselves about it.
    The disturbing answer is therefore that no single entity may control reality completely, while many systems possess the ability to control fragments of it.
    Perhaps that is more dangerous than the existence of one identifiable controller, because a single dictator, corporation or machine can at least be named, whereas distributed influence emerges from countless interactions between institutions, technologies, incentives and cognitive tendencies that no individual actor fully commands.
    The Matrix of the twenty-first century may therefore resemble an ecosystem rather than a prison.
    We participate in it.
    We reinforce it.
    We feed it information about ourselves.
    And then we ask why it seems to know what we want.


    THE MATRIX DOES NOT NEED TO HIDE THE TRUTH
    One of the most powerful ideas explored in Matrix: The Hidden Truth — Who Controls Reality? is that control does not necessarily require hiding reality behind an elaborate fabricated world, because controlling attention can be more efficient than controlling facts.
    If ten thousand events occur today and your information environment exposes you repeatedly to only twenty of them, nobody needs to falsify the remaining 9,980 events for them to become psychologically almost nonexistent.
    The Matrix, understood in this broader sense, is therefore not necessarily a secret computer hidden beneath civilization, but the network of assumptions, narratives, institutions, technologies and mental processes standing between the world as it exists and the version of the world that reaches consciousness.
    Plato imagined prisoners watching shadows and believing that the shadows represented reality because they had never seen anything else, while the modern citizen carries the wall of the cave inside a pocket and consults it dozens or hundreds of times every day, except that today’s shadows are personalized, constantly updated and selected according to increasingly sophisticated predictions about what will hold that particular person’s attention.
    The comparison should not be pushed too far, because social media is not a single conspiracy and an algorithm is not an omnipotent jailer, yet the philosophical question raised by Plato has become strangely contemporary: if almost everything we know about distant wars, governments, scientific discoveries, crimes, celebrities, economic crises and people we have never met reaches us through intermediaries, how confidently can we separate reality from the systems selecting our view of it?


    ESCAPING THE MATRIX DOES NOT MEAN DISCOVERING A SECRET WEBSITE
    The romantic version of awakening imagines a single moment in which the hidden truth is revealed and the individual suddenly sees everything clearly, but genuine intellectual independence is probably far less dramatic and considerably more difficult, because there is no final website, political movement, influencer, newspaper or alternative-media channel that can provide an unfiltered view of reality.
    Replacing one information bubble with another is not escape.
    Rejecting mainstream claims automatically is no more intellectually independent than accepting them automatically.
    Believing the opposite of whatever a government says still allows the government to determine the structure of one’s beliefs.
    The more difficult form of freedom requires tolerating uncertainty, consulting sources that disagree with one another, distinguishing primary evidence from commentary, recognizing emotional manipulation even when it supports one’s preferred conclusion, deliberately searching for information capable of falsifying one’s beliefs and accepting that occasionally the most intellectually honest answer is simply that the available evidence does not yet allow certainty.
    Such habits do not remove every cognitive bias, because no human being can step outside the architecture of the human brain, nor do they eliminate every external influence, because living within society necessarily means relying on institutions and other people for enormous quantities of information.
    What they can provide is something more modest and perhaps more valuable: awareness of the filters.


    THE FINAL PARADOX
    Perhaps the greatest paradox of the modern Matrix is that humanity has more access to information than any civilization in history while simultaneously becoming increasingly dependent upon automated systems to determine which pieces of that information deserve attention.
    The library has become almost infinite, but the librarian is invisible.
    The librarian watches what we select, learns what keeps us inside the library and rearranges the shelves before our next visit.
    Governments attempt to influence the stories circulating through those shelves, companies compete to purchase our attention, political movements learn which emotions spread fastest, and our own minds continue doing what human minds have always done by searching for patterns, preferring familiarity and interpreting new information through previous experience.
    No single hand needs to control the entire machine.
    The system can emerge from all of them together.
    Perhaps, therefore, the question “Who controls reality?” contains a misleading assumption, because the real issue may not be who controls the external universe but who influences the model of that universe living inside our minds.
    And once the question is stated that way, the answer becomes considerably more uncomfortable, because governments influence it, algorithms influence it, culture influences it, memory influences it, emotion influences it, the people around us influence it, and we ourselves participate continuously in deciding which version survives.
    The Matrix may not be somewhere outside us, waiting to be discovered.
    It may be the invisible distance between what exists and what we have been taught, shown, encouraged and psychologically prepared to see.


    SOURCES AND FURTHER READING
    Gauthier, Germain, Roland Hodler, Philine Widmer et al. — “The Political Effects of X’s Feed Algorithm,” Nature, 2026. The seven-week randomized field experiment found that exposure to X’s algorithmic feed affected engagement, account-following behavior and several measured political attitudes, while switching the algorithm off did not simply reverse those changes.
    Guess, Andrew M., Neil Malhotra, Jennifer Pan et al. — “How Do Social Media Feed Algorithms Affect Attitudes and Behavior in an Election Campaign?”, Science, 2023. The researchers changed Facebook and Instagram users from algorithmic to chronological feeds during the 2020 US election and observed substantial differences in platform use and exposure without corresponding significant changes in several major political attitudes.
    Nyhan, Brendan, Jaime Settle, Emily Thorson et al. — “Like-minded Sources on Facebook Are Prevalent but Not Polarizing,” Nature, 2023. This large-scale study found substantial exposure to politically congenial sources on Facebook while also finding that experimentally reducing such exposure did not measurably reduce the political attitudes studied.
    Teufel, Christoph & Paul C. Fletcher — “Forms of Prediction in the Nervous System,” Nature Reviews Neuroscience, 2020. This review examines the increasingly influential neuroscientific view that predictions and prior information contribute substantially to how human beings perceive and interpret sensory information.
    Barrett, Lisa Feldman & Earl K. Miller — “Categorization Is ‘Baked’ Into the Brain,” Nature Reviews Neuroscience, 2026. The authors review evidence suggesting that categorization operates throughout neural information processing rather than appearing only as a late intellectual stage after perception has already occurred.
    Wittenberg, Chloe & Adam J. Berinsky — research summarized in Cambridge University Press scholarship on misinformation and correction. Research on the illusory truth effect indicates that repeated exposure can increase the perceived credibility of information partly through familiarity and processing fluency, although repetition should not be treated as an unlimited mechanism capable of overriding all prior knowledge.