When Seeing Is No Longer Believing: Deepfakes as a Public Health Crisis
December 3, 2025
As deepfake technology makes it impossible to trust what we see and hear, the implications extend far beyond fraud into mental health, emergency response, and the very foundation of public health communication. The erosion of reality itself has become a health crisis.
When Seeing Is No Longer Believing: Deepfakes as a Public Health Crisis
On a January morning in 2024, a finance worker in Hong Kong joined what appeared to be a routine video call with her company's chief financial officer. The face on the screen was familiar, the voice reassuring, the request straightforward: authorize a $25 million transaction. She complied without hesitation. The person she trusted was, after all, right there on her screen—or so she thought. Within hours, the devastating truth emerged: every face on that call, every voice, every reassuring gesture had been fabricated using deepfake technology. The $25 million was gone, transferred to criminals who had weaponized artificial intelligence to manufacture reality itself.
This is the world we live in now. The fraud was stunning, but it is the implications beyond it—into medicine, public health, and the basic architecture of trust—that should concern us.
From Infodemic to Manufactured Reality
When Dr. François Marquis, chief of intensive care at Maisonneuve-Rosemont Hospital in Montreal, discovered his face and voice being used to sell fraudulent health products online, his first thought wasn't about his own reputation. "My primary worry is for the individuals who trust me," he explained to reporters. "It's putting a lot of damage on all physicians in Quebec and in Canada." Dr. Marquis had become an unwitting participant in a new frontier of health misinformation—one where artificial intelligence doesn't just spread false information, but manufactures credible spokespersons to deliver it.
His experience is far from isolated. Dr. Alain Vadeboncoeur of the Montreal Heart Institute found himself digitally cloned across multiple deepfake videos discussing urology, prostate cancer, and sexual dysfunction—subjects entirely outside his medical specialty. "The danger is you don't know what it is that they're taking," Dr. Marquis warned, highlighting how even seemingly harmless supplements could trigger adverse reactions or, worse, convince patients to abandon proven treatments like insulin or anticoagulants for counterfeit alternatives.
Both cases follow the same logic: fabricated credibility, deployed to undermine medical decisions. During the COVID-19 pandemic, the World Health Organization warned of an "infodemic"—too much information, accurate and false alike, making it hard to find trustworthy guidance. Deepfakes are something different. They don't just spread misinformation. They manufacture the authoritative messengers who deliver it.
The Mental Health Crisis Hidden in Plain Sight
Deepfakes harm health in ways that go well beyond bad medical decisions. The psychological consequences documented in clinical research rival physical assault in severity and duration.
Consider the mental health outcomes reported by victims of image-based sexual abuse using deepfake technology. Research consistently documents rates of depression, anxiety, and post-traumatic stress disorder comparable to those seen in survivors of physical violence. "Being victimized through deepfakes can erase your sense of reality," explains therapist Francesca Rossi, who specializes in treating survivors of this form of abuse. The dissonance between knowing the imagery is fabricated while watching it look utterly convincing creates a profound psychological rupture.
For children and adolescents, the stakes are even higher. The American Academy of Pediatrics reports that young victims of deepfake pornography experience humiliation, shame, violation, and self-blame that can lead to immediate emotional distress, withdrawal from school and family, and in severe cases, self-harm and suicidal ideation. One in six minors who experience potentially harmful online sexual interactions never disclose it to anyone, with boys even less likely to seek help—intensifying their isolation and suffering.
The trauma extends to healthcare workers themselves. A study of Romanian frontline medical staff during the COVID-19 pandemic found that clinicians who reported being affected by false news in their professional activities experienced significantly higher levels of stress, anxiety, and insomnia than their colleagues who felt insulated from the infodemic. These healthcare workers described feeling emotionally overwhelmed by fake news and reported that misinformation damaged the doctor-patient relationship, with patients increasingly distrusting their physicians.
The Equity Crisis Hiding in the Technology
The threat deepfakes pose to public health extends beyond individual psychological trauma to systemic failures in emergency response and community health. During the COVID-19 pandemic, health misinformation about vaccines, treatments, and preventive measures spread with viral efficiency across social media platforms. Analysis of Facebook posts found that approximately 46.6% of vaccine-related content contained misinformation, while fact-checking posts represented only 47.4% of the conversation—and 28.5% of those fact-checks actually repeated the false claims they were trying to correct.
Deepfakes threaten to exponentially amplify this problem. While traditional misinformation could be produced and shared by anyone, deepfakes carry the manufactured authority of trusted experts. Imagine a deepfake video of a public health leader promoting unproven treatments or discouraging vaccination, distributed during a critical phase of pandemic response. The consequences could be catastrophic.
Vulnerable populations bear disproportionate risk. Research on deepfakes in resource-limited communities reveals critical knowledge gaps and a lack of effective detection tools. Marginalized communities, already facing systemic barriers to healthcare and experiencing lower levels of institutional trust due to historical discrimination, may be particularly susceptible to deepfake-enabled health misinformation. The elderly, who reported $3.4 billion in fraud losses in 2023, face special vulnerability to sophisticated AI-generated scams.
With deepfake incidents increasing from just 22 between 2017-2022 to 179 in the first quarter of 2025 alone—a 19% increase over all of 2024—we are witnessing an acceleration that outpaces nearly every other threat to information integrity.
When Reality Becomes Infrastructure
Security experts call this "cognitive security"—protecting human judgment from manipulation, and keeping information ecosystems reliable enough to act on. In healthcare, where people make decisions about their bodies based on what they're told, that protection isn't abstract. When deepfakes proliferate, they don't just spread false information. They corrode the foundation that public health communication is built on.
The effects cascade. Canadian physicians report that health misinformation leads patients to refuse established treatments, resulting in severe consequences including preventable deaths. During COVID-19, vaccine hesitancy driven by misinformation was directly linked to thousands of preventable hospitalizations and deaths. Now imagine that same dynamic amplified by the manufactured credibility of deepfake technology.
Building Defense at Multiple Levels
Fixing this means working across technology, policy, education, and clinical practice at the same time. What once required expensive computing infrastructure can now be done with tools available for under $400 a month. The accessibility of these technologies means that malicious actors—from individual scammers to state-sponsored disinformation campaigns—can produce convincing deepfakes at scale.
At the technological level, researchers are developing detection systems using the same AI techniques that create deepfakes. Modern deepfakes are created using Generative Adversarial Networks (GANs)—where one neural network generates fake content while another tries to detect it. Through millions of iterations, the generator becomes increasingly skilled at fooling the discriminator. But this same dynamic can be reversed, with detection algorithms learning to identify the subtle artifacts that even the most sophisticated deepfakes leave behind.
Yet technology alone cannot solve this problem. Research tracking deepfake technology in 2024 found that many academic detection systems have become outdated, unable to identify the latest manipulation techniques circulating on social media. The arms race between creation and detection tools is ongoing, and detection will likely always lag behind the cutting edge of synthesis technology.
At the policy level, governments and platforms are beginning to act. Regulatory frameworks are emerging that require disclosure of AI-generated content, criminalize non-consensual deepfakes, and establish liability for platforms that host harmful synthetic media. But policy implementation varies widely across jurisdictions, creating gaps that bad actors can exploit.
Media literacy also needs updating. "Seeing is believing" never accounted for a world where any image, any voice, any video can be fabricated convincingly. New habits around verification, new norms about what counts as evidence, and new institutional mechanisms for establishing credibility are all overdue.
The Window for Thoughtful Action
The decisions we make now about detection systems, regulation, and public education will determine whether information integrity in public health can be preserved.
This requires frameworks that embed equity considerations from the start. Detection tools must work across languages and cultural contexts. Educational initiatives must reach vulnerable populations most at risk of exploitation. Policy responses must protect privacy and free expression while preventing harm. Clinical practice must evolve to help patients navigate an information landscape where manufactured reality is increasingly indistinguishable from the authentic.
The communities most likely to be harmed by deepfakes—those already marginalized, already facing barriers to healthcare, already experiencing lower levels of institutional trust—are the same ones least likely to have access to detection tools and least likely to be included in the design of solutions. This pattern, familiar from every previous wave of health technology, cannot be allowed to repeat.
Deepfakes have already changed how health information travels. The question now is whether we can build the detection, policy, and educational infrastructure fast enough to protect the people least able to defend themselves against it — before the verification habits and trust norms we need become impossible to establish.
This article draws on insights from reporting by CNN and CBC on deepfake fraud cases, research from the American Academy of Pediatrics and European Parliament on mental health impacts, and analysis from the World Economic Forum on emerging threats to information integrity.