The lab leak theory is dominating the news cycle again following a contested Senate hearing and subsequent media discussion over the origins of SARS-CoV-2.

They say history might not repeat itself exactly, but it certainly rhymes. If we are indeed living in a simulation, somebody clearly messed up the copy paste. Unfortunately, our reality seems no less scripted sometimes. Anxieties and gain-of-function fearmongering of the past years are once again culminating in a recent - and very visually appealing, not gonna lie - op-ed by Dr. Alina Chan. It appears the lab leak influencer has once again been asked by the Grey Lady for another spin around the lab leak ballroom.

Since 2020, the lab leak idea in its many iterations of inconsistent allegations and speculations has become a staple of public and elite imagination, despite a complete absence of any recognizable evidence justifying such strong belief. Not to mention a large and growing scientific body of work and consensus strongly in contradiction with the idea of a research-related origin.

Just typing yet again this contextualizing paragraph about the current status of the “origin controversy” makes me cringe. Nothing has changed on this assessment in years. It is literally old news. Let me state it plainly:

The weight of scientific evidence for a zoonotic origin is extremely unlikely to be overturned at this point. It is in fact consolidating into a scientific consensus as key publications and new information or analyses are slowly diffusing through, mulled over, and unsuccessfully challenged by the wider scientific community. That includes Dr. Chan, who has long given up trying to bring her arguments to scientific journals and rather brings them to willing newspapers and politicians instead.

So instead of explaining (like many others did at length and in detail) why Dr. Chan’s various assertions in her previous New York Times op-ed are not getting any fresher despite a new NYT paint job, I wanted to add something new to the stale and repetitive lab leak discourse in 2026.

I will share results from my newest investigation into two different, and maybe more relevant origin questions that I have been chasing recently.

1. Can a scientifically coherent lab leak hypothesis still be formulated in 2026?

2. Has the lab leak theory been censored or was zoonosis the preferred narrative in the media?

Answering these questions will not only contextualize what to think about Dr. Chan’s recent New York Times opinion piece, but how we, as democratic citizens, have to prepare ourselves against being manipulated by those in power.

Sounds good? Let’s head in.

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1) Can a scientifically coherent lab leak hypothesis still be formulated?

Let us get one thing out first: Whether SARS-CoV-2 originated in nature or in a lab is a scientifically testable question.

It is not a question of individual belief, human testimony, mystical explanations, secret intelligence, moral judgement or “other ways of knowing”. It is a question addressable within the domain of the physical world, where scientific evidence and inquiry are the only reliable method we have to test our hypotheses and not fool ourselves about objective reality.

That does not mean that we necessarily have sufficient evidence to prove or disprove a particular hypothesis. In science, proving the negative, that something did not happen, is usually tricky. On top of that, in outbreak investigations, one often operates with imperfect knowledge and data.

What makes a hypothesis scientific?

Scientists commonly think about it this way:

- How well does a proposed theory explain evidence and observations we already have?

- How well does a proposed theory predict the outcome of experiments and new observations?

A scientific theory also needs to observe parsimony. Which basically means that you reject unevidenced and unnecessary assumptions to make your "theory" or data fit.

The “lab leak theory” is commonly discussed as though it were a single hypothesis.

In reality, it is an amalgamation of origin claims that differ in mechanism, emergence route, in what would count as evidence for or against them, and in prior plausibility: deliberate construction of a bioweapon; de-novo genome assembly, gain-of-function research with genetic engineering or serial-passage adaptation of a bat virus; in vitro cultivation of a bat virus that escaped containment; or infection of a fieldworker or laboratory worker who then carried the virus to the city.

Some lab leak scenarios even propose researchers would have brought the virus from the lab specifically to the Huanan market, either directly or via discarded lab animals, making SARS-CoV-2 emergence from the market scientifically almost indistinguishable from zoonotic spillover from wildlife at the market brought in from vendors sourcing from the wildlife trading industry. Some propose wildly off timelines of emergence to, from military games in October or viral database takedowns in September to apparently many months earlier, as lab leak debater Peter Miller points out:

Given the diversity of lab leak “hypotheses", many proponents of the lab leak theory either hold mutually contradictory view, decline to specify what they believe, or simply hope their claims are not taken through to their necessary implications where they would meet the body of known scientific evidence. Let’s illustrate with an example.

Did Dr. Fauci cause the pandemic?

This failure of taking a lab leak allegation to their necessary implications has been especially blatant recently, as US Senator Rand Paul (and as we will see, Dr. Alina Chan as well) are once again weaponizing lab leak allegations against retired public health servant Dr. Anthony Fauci; whom he accuses of having been involved in the creation of SARS-CoV-2 via gain-of-function research.

For Fauci to have any culpability in the origins of the pandemic, Senator Rand Pauls specific lab leak hypothesis necessitates two auxiliary assumptions:

• First, that SARS-CoV-2 is not a natural virus, but was somehow intentionally manipulated and came about through a gain-of-function research program.

• Second, that Dr. Fauci is somehow causally implicated in said research program, either through funding, knowledge of or outsourcing it to Wuhan.

Despite years of digging through official and private records, there is no evidence of any misconduct or culpability of Dr. Fauci. And yet, the problem Rand Paul’s allegations face do not just lie with the latter.

SARS-CoV-2 has nothing to do with gain-of-function research or genetic engineering. We know this because any lab origin hypothesis that stipulates a non-natural or modified virus has very hard scientific evidence against it.

All engineering scenarios fail already at scientific analysis of the uncontested SARS-CoV-2 genome sequence itself that we have sequenced all around the world from millions of patients.

• SARS-CoV-2’s genome is a recombinant mosaic that could not be assembled in a lab.

• It houses a novel RBD motif that was found in bats only after the pandemic.

• It includes an FCS that is an out-of-frame insertion of a non-canonical motif, and with a superfluous, non-motif proline addition

• Mechanistic studies performed in 2022 discovered a new cleavage synergy with a proximal glycosylation and sequence motif, a hallmark of evolution, not design.

Neither gain-of-function research, nor genetic engineering, can credibly produce a virus with these features in any laboratory setup. The “gain-of-function research introducing an FCS via genetic engineering” hypothesis is among the weakest lab leak scenarios, albeit the most politically salient.

Now one problem I have with most journalists covering this origin topic is that they are always eager to cover the high-profile dispute, parse whether they can find any substantiation of Rand Paul’s allegations in selectively disclosed and quote-mined documents; but that they never bother to even differentiate what lab leak scenario these proponents actually endorse.

This is journalistic malpractice.

There are other lab leak hypotheses that can account for some of the genetic and mechanistic features that any engineering hypothesis can not. For example, a natural bat virus could have been collected and cultured that already had the right genetic setup to infect humans. Or a serial passage experiment in susceptible animals was performed on such a natural virus (which does not make any sense to perform on a novel, unknown virus; but just for arguments sake).

Now of course, other lines of evidence exist that have been collected by independent researchers, methodologies and studies that make these lab leak hypotheses also hard, if not impossible, to square with the body of verified scientific evidence; such as case and spatial epidemiology, phylogenetic analyses and lineage tracing, and metagenomics of environmental samples taken from the Huanan market. Below I created a constraint sieve chart visualizing how accumulated evidence over the years makes it actually quite impossible to formulate a lab leak hypothesis that can explain the totality of independent evidence we possess today, from genomic features and mechanistic studies bearing hallmarks of evolution, to phylogenetic history showing two introductions, to case and spatial epidemiology centered around the Huanan market, to metagenomics and transcriptomic samples placing SARS-CoV-2 susceptible and sick animals inside the market.

The power of the zoonotic origin theory does not rely on a particular piece of evidence or study, nor does a single line of evidence or inquiry have the power to disprove any and all lab leak hypothesis.

The reality is that given the available evidence today, one is strained to even formulate any new lab leak hypothesis that is scientific in the operative sense that it can explain the available data and maintain parsimony.

We outlined that a scientific theory not only needs to be able to accommodate existing evidence parsimoniously, but ideally have predictive value that can be confirmed via new discovery or experimentation.

But we are not just starting the discussion now, the lab leak theory in its many iterations has been around ever since the virus took Wuhan, and then the rest of the world, by storm.

What was the predictive power of the competing origin hypotheses since 2020?

Both "zoonotic spillover at market" & "lab leak from WIV" theories were offered immediately as alternative origin explanation in early 2020. Mired in initial uncertainty, a scientifically reasonable version of the lab leak hypothesis could be postulated without running into evidentiary contradictions.

Given the constant goal-post shifting and diversification of origin speculations to account for ever increasing contradictory evidence, I think it can be a useful exercise to retrospectively check of how accurately both theories predicted subsequent research findings that took years to accumulate, or failed to stack up for that matter.

While the above matrix is neither comprehensive not free from some personal assessment, I believe it is fair to state that the zoonotic spillover at market theory has predicted subsequent findings extraordinarily well and remains virtually unchanged since its first formulation in 2020.

In stark contrast, the lab leak theory has constantly shifted speculations, trying to justify its existence against contradictory evidence. It predicted nothing about what subsequent studies would find or discover since 2020.

There is no scientific lab leak theory or hypothesis any more. That is why I have for some time now argued that we should stop calling the lab leak a theory, or even a "conspiracy theory".

It is something different; an emotive, engaging narrative that mutates over time and according to the preferences of who is in power. The Rand Paul version currently leading the news cycle is just its latest, most inflammatory, iteration.

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What explains the endurance of this lab leak narrative against a scientifically unchallenged zoonotic origin explanation?

This brings us to our next part:

2) Has the lab leak theory been censored / was zoonosis the preferred narrative in the media?

For many years, but latest since 2020, US Republicans and associated media operators and influencers have been building up the myth of media bias and censorship against American conservatives. (subsequent studies find the opposite)

Triggered by the big lie of a supposedly stolen 2020 presidential election, social media platform moderation teams, mainstream media fact checkers, and disinformation researchers like the brilliant have become a thorn in the eyes of the burgeoning fascists MAGA movement in power today.

Between the supposed censorship of the Hunter Biden Laptop story of 2020 and the manufacture of the Twitter-files “censorship industrial complex” narrative in 2022, there was one particular topic where the rightwing propaganda machine had set out to finally break the social contract of being held accountable, or at least fact checked and counter-spoken to, when spewing lies and conspiracy theories.

You guessed right. The supposed suppression of the lab leak theory.

As often, propaganda is most effective when there is a kernel of truth, a key fact or anecdote that can be retreated to when challenged. In this case, Facebook has indeed moderated assertions of a man-made virus on its platform between February-May of 2021.

To give some context:

And in the aftermath January 6th 2021, where disinformation has brought a violent mob to storm congress in order to overturn a democratic election, social media platforms scrambled to implement stricter content moderation and enforcement of their own stated community guidelines. Especially Facebook and Twitter found themselves in hot water for enabling these insurrectionist actors and act; bound to be facing potential liability or at least increased scrutiny by lawmakers that almost have been lynched. So they responded quickly by tightening moderation enforcement and deplatforming the biggest offenders. Most visibly, then president Trump, who had incited the storm on the capitol, was suspended from Twitter. A catastrophic event for those of the rightwing propaganda machine whose power and fortune relied on continuously lying to their audiences.

Stolen election and other conspiracy theories associated with the MAGA movement quickly came under scrutiny too; and this is where I assume Facebook made that call on “explicitly prohibited and removed content stating that "COVID-19 is man-made or manufactured" under its COVID-19 misinformation policy.

Worth knowing that in 2020, the most dominant lab leak theory was its bioweapon version conjured up by Steve Bannon and Miles Guo, Trump operatives strongly tied to the MAGA ecosystem. Additionally, Miles Guo’s scam operation led to defrauding believers in a man-made virus with financial scams amounting to a billion dollars.

Nevertheless, once Facebook reversed the policy a few months later, the rightwing propaganda machine seized upon the moment to claim that the “conspiracy theorists” were right after all. Subsequently, the lab leak theory became totemic as a symbol for censorship overreach and the suppression of conservative views and voices in media at large.

Most in mainstream media and elite circles either fell for the propaganda or decided it was necessary to signal their own performative neutrality on the lab leak question, and soon, willing op-eds started appearing across the quality and mainstream press, with articles such as:

It became common vibe-based knowledge that the lab leak theory was suppressed by fact checkers and scientists, and had been dismissed by the media. Some have argued these events also changed the lab leak narrative from a low-status belief into a high-status one.

In turn, the success of the supposed lab leak theory redemption arc just boosted the hunger of the rightwing propaganda machine to get rid of any and all content moderation, and as we learned later, any checks on their power to lie without consequence and accountability.

But what if the vibe was wrong?

I have spent years trying to reconstruct the major events that shaped public perception of the origin controversy, and I came to the conclusion that while legitimate uncertainty existed, especially in early 2020, everything that unfolded after can not be explained by scientific ambiguity or Chinese obfuscation alone.

The gap between scientific evidence and what scientists believe, versus what the public, including elites in media, politics and business believe, is among the biggest for any scientific topic in existence, including climate change.

Where does the striking evidence-belief gap come from? What prompts the New York Times to again and again platform lab leak activists like Dr. Alina Chan, or resident lab leak columnist Zeynep Tufekci for that matter?

Is it for performative neutrality? To balance reporting by giving baseless insinuations and unsubstantiated allegations equal weight to a body of scientific evidence? To fend off charges of bias or suppression? To remedy what is assumed true, that the lab leak theory did not get a thorough hearing by the media and in public discourse? I can not answer these questions for the NYT.

For this novel analysis, I will use two data sets that can be obtained freely without special API access to platforms. The first dataset is from MediaCloud, an open-source platform for media analysis. The second is YouTube Data tools, a front end to the YouTube Data API search.

Both allowed me to search for and assemble a comprehensive database of online-news articles and Youtube videos talking about the origin controversy published between Jan. 1 2020 and July 31st 2026. (please see method section at the end of the article for further details).

Using the context-aware natural language processing of advanced large language models (Claude Opus 4.8, Claude Opus 5.0), we assessed 11,086 COVID-19-origin online-news headlines and 1,546 YouTube videos on a mirrored seven-point ordinal scale from −3 (natural/zoonotic origin asserted as fact) through 0 (neutral, uncertain, both-sides or procedural) to +3 (laboratory origin asserted as fact), with graded intermediate points.

On the news articles dataset, I find that the lab leak theory has never not been the dominant theory in online news media, with the exception of the first quarter of 2020, where the emerging pandemic fueled a lot of reporting on wildlife trade and explainers of viral emergence through zoonosis.

After that, starting latest with the April-June of 2020 quarter, the Trump administration and MAGA movement has fully embraced the “China virus” narrative, columnist Josh Rogin sold a BS story of secret diplomatic cables to the Washington Post about a supposed biosafety warning from a diplomatic WIV visit, while conspiracy theorists like Yuri Deigin kicked-off gain-of-function fearmongering, DRASTIC began selling the dead Mojiang miner story and Dr. Alina Chan did her first front-page media tour based on a flawed “pre-adaptation” preprint that still has never managed to pass peer review.

From around April 2020 onward, the lab leak theory never left the public discourse, specifically on the right and partisan news media which also dominate in overall article volume at least 3:1 over centrist and left media.

That lab leak dominance pattern holds largely true even when we remove the rightwing partisan news media and just focus on “Quality press” or legacy news media, which gave the lab leak theory plenty of endorsing coverage. The biggest difference between rightwing partisan and legacy media is that legacy media also reported on new scientific discoveries when they happened (e.g market origin paper from Worobey et al. and Pekar et al. in Q2 of 2022, and raccoon dog-metagenomics paper from Crits-Christoph et al. in Q3 of 2024).

Yet additional evidence for zoonosis never seemed to last in whether to assess the origin question one way or the other, and soon even legacy media would be back with favorable lab leak coverage.

One illustrative, albeit not perfectly representative, example of lab leak coverage reflects the trajectory of Fox News and NYT over the years. While Fox news always followed a hard lab-leak endorsing stance, the NYTs had infighting between their science and reporting desks versus their op-ed and political desks. With the slow pace of scientific findings, but accelerated GOP witchhunts of recent years, the NYT got pulled stronger and stronger to endorse the lab leak theory, a stance it clearly continues in 2026.

We can also have a look at the aggregate of lab leak partisan coverage from outlets that are either right-leaning, center or left-leaning.

Here are the top-10 origin coverage providers in US media for each bucket, with the number of origin-related headlines, lab: zoo coverage ratio, average endorsement score and confidence intervals.

What is striking here is the dramatic difference in volume of rightwing media, and how one sided they present the lab leak theory to their viewers. On average, for every 14 articles endorsing a lab leak theory, only 1 would speak supportively of the zoonotic theory. (and honestly, some of that might be LLM attribution error for ironic articles). So this is being generous. For right-leaning media, taking no position at all or both-siding the alternative theories is also not very common.

This is in stark contrast to how the NYT and other centrist media clearly operate, where every story where there are two sides deserve equal opportunity and coverage, leading to a lot of 50:50 coverage or tit-for-tat (e.g news desk reported a scientific discovery for zoonosis; political/op-ed desk runs an op-ed on how a lab leak can not be discarded given the new discovery).

Another interesting result is that left-leaning media, despite often being presented or decried by centrists as equally bad than rightwing media, are barely edging out a slightly more reality-aligned lab leak coverage than their centrist peers. So if I had to summarize:

Now at the moment, we looked at news article volumes and endorsement, but just pushing out more and more digital content like rightwing propaganda outlets tend to do does not necessarily give a good indication of the consumption or popularity of that content.

So next, I used the same LLM-based methodological approach and criteria to rate the lean of YouTube videos. For anybody who has held out hope that algorithmically driven entertainment platforms would somehow be more accurate or at least diverse in their lab leak coverage, I am sorry to disappoint.

Scientifically accurate or aligned pro-zoonotic YouTube content dramatically underperforms not only on creator volume, but also on engagement itself.

While only about 14% of all YouTube videos on the topic strongly endorse the lab leak theory, they win 36% of all eyeballs for the topic.

43% of all YouTube origin videos show a clear lean towards the lab leak theory, and gather the largest portion of attention with 41% of overall views.

In contrast, of the 7% of all YouTube videos that either lean or strongly endorse the zoonotic origin theory (including multiple virologist interviews of ours) only manage to gain 2% of all attention for the topic.

The problem with engagement-algorithm driven systems is that the winner usually takes all; so the distribution of attention is very asymmetrical towards a few highly influential videos pro-lab leak videos among a cottage industry of conspiratorial video creators. You can explore the YouTube data interactively here to form your own impression too. Let me know what you find.

I think the classic example for the lab leak theory is when late-night comedian Jon Stewart endorsed the lab leak theory on the late night show with Stephen Colbert, seen by 8.6 million people as of today.

Now one caveat of the YouTube dataset is that the videos need still to be live in order to be recovered, so some influential videos such as when Tucker Carlson platformed Steve Bannon’s bioweapon whistleblower Dr. Li Meng Yan in 2020 that received 8.8 million views have since been removed.

So the endorsement and engagement slant of the YouTube lab leak dataset is possibly an underestimate, specifically around conspiratorial content that might have been removed since 2020.

So let us sum up the analysis:

The vibe was wrong. The lab leak theory was the preferred narrative all along and remains so today.

The lab leak theory was not suppressed nor discarded. It has been the dominant theory promoted by politicians in the highest offices, partisan and mainstream news outlets, legacy and alternative news media; and some of the most popular media personalities on the left and right.

The common knowledge that one could not even talk about the lab leak theory without serious repercussions was mostly a supercharged fabrication by a partisan media machinery based on a true, but not representative, anecdote of a Facebook moderation decision between Feb-May 2021. Mainstream media and elite belief accepted it as truism for various reasons, turned endorsement of lab leak theory into a high-status belief, while the public has been sold the myth of the lab leak theory suppression ever since. This is astonishing, given that in 2026, there is no scientifically legible lab leak hypothesis left to defend, and there is also no professional upside to pointing that out. The lab leak emperor is naked, and everybody making editorial decisions, especially the Grey Lady, just pretends to see the most compelling ball gown.

Ironically, it appears to me that a type of media group think did happen for a considerable fraction of legacy media. When a belief becomes costly to contradict in public, journalists and editors stop contradicting it in public, and their silence is then read as agreement by colleagues, which raises the cost further. Editorially discarding the lab leak theory as unevidenced, or even a baseless conspiracy theory, has become socially and professionally costly, for individual journalists, commentators and outlets alike, reinforcing the continued astonishing pattern of media coverage bias.

When was the last time you read in the New York Times that the lab leak theory is a baseless conspiracy myth; which is much closer to objective reality than whatever Dr. Chan cooked up in her recent op-ed?

So what explains the evidence-belief gap between what scientists know and the public believe on the origins of SARS-CoV-2?

It is certainly not scientific ambiguity.

If I had to propose a hypothesis, the astonishing and ongoing media coverage bias across news, digital and social media would certainly be a prime candidate for further investigation.

What now?

One argument I make in my book is that in the information age, where technological disruption has upended the news media business and fundamentally reshaped incentives, coverage tends to follows elite belief, not factual reality. From oligarchic consolidation of media ownership, partisan operatives, a business- and politician-friendly press corps to client propagandism for billionaire interests, extreme wealth found in the precarious economic situation of technologically disrupted media businesses an opportune moment to acquire and enshrine their power over society.

Yet in this moment in the US and other places, the scientific community finds itself increasingly at odds with the beliefs of the powerful, and that has many unwelcome consequences.

Scientists in the US are attacked. Losing their funding, jobs, career prospects or livelihoods. If they have any public profile, they might get targeted by hate mobs, domestic terrorists, and increasingly a weaponized US government; endangering their physical safety and freedom. If you have not heard much about this, you should consider reading this:

Universities and federal scientific institutions are similarly under siege, threatened by lawfare, starved of resources and funding, subjected to new, often unlawful or unconstitutional rules, arbitrary enforcement and political interference.

One consequence of being at odds with power that is not often talked about is the permanent drumbeat of partisan and mainstream media, alternative and popular content creators, podcasters and client propagandists who are financially incentivized and politically rewarded to justify and foment such attacks on scientists and universities.

The fascist media machinery is of course the most visible driver of false narratives like the lab leak theory and needs to be destroyed for democracy to thrive. There is no way around that.

But we also need deeper media reform beyond that. It has been particularly disappointing when even influential centrist media, famous for observing performative neutrality, breaks their own neutrality rules with lab leak-favorable coverage dominating almost 2:1, with a mean slightly above the “both theories are equally likely” and a tilt towards “but if I had to guess the lab looks sus, doesn’t it?”

Particular scorn goes towards the economically thriving Grey Lady that basically enjoys a monopoly in journalistic influence after the disruption of the market by technology. They are the ones that have the resources to not cater to power, yet choose to do so. Even outside their usual performative neutrality stance on topics like “whether actual fascists or people calling them fascists are the real offenders here?”, the The New York Times is very clearly and consistently taking an editorial position towards endorsing and promoting the lab leak theory that fueled and still fuels a lot manipulative attacks on science. There is no way to sugarcoat this, and if you do not want to hear it from me, see what Michael Mann and Peter Hotez have to say about the Grey Lady in their book on anti-science.

Platforming the known lab leak activist Dr. Alina Chan, again, to fearmonger about gain-of-function research and allocate blame onto innocent scientists, while the news cycle predictably jumped on the Senate hearing of Dr. Fauci, is not “without fear or favor” coverage.

In a world where power can turn lies into reality, we all need a functioning fourth estate more than ever. There are many excellent journalists working at the New York Times, it is a large organization. But if the Times does not have a reckoning on its editorial and leadership’s cozy relationship with narratives of power, something new and journalistically independent will have to take its dominant place.

In the meantime, readers are advised to exercise scepticism and withhold trust. Especially when NYT spends their vast resources on producing a glitzy op-ed instead of an investigative story, we should understand what faction of the Times has won the editorial greenlight, and why.

Methods section

News-headline corpus construction

Headlines were drawn from the Media Cloud online-news archive across four high-reach United States collections (US Most Visited News Online [Mar 2025], U.S. Top Sources 2018, U.S. Top Newspapers 2018, and United States - National) for 1 January 2020 to 31 July 2026. To capture broad coverage without directional bias, articles were retrieved using a disjunctive Boolean query combining neutral baseline terms (e.g., “covid origin”, “viral origin”) with frame-specific keywords balanced across competing hypotheses: natural spillover (e.g., “wet market”, “zoonotic”, “pangolin”, “raccoon dog”, “Huanan”, “spillover”), laboratory accident and research funding (e.g., “lab leak”, “Wuhan Institute of Virology”, “gain of function”, “EcoHealth”), and engineered origins (e.g., “bioweapon”, “man-made”).

This search returned 92,255 English-language records across 247 outlets after de-duplication on record ID. The unit of analysis is the headline. Because the collections are reach-weighted to reflect broader news consumption reality of US digital news media consumers, the online news corpus over-represents high-traffic partisan and tabloid outlets relative to legacy newsrooms. We analyze full news media coverage as well as the subset of top 50 US newspapers coverage to track similarities and difference of origin coverage between these news formats.

To establish on-topic status of news headlines — whether an article concerns the origin of SARS-CoV-2 rather than COVID case counts, policy or unrelated health news — was set by a relevance classifier: a TF-IDF plus logistic-regression model trained on 10,583 positive-labelled IDs, thresholded at 0.74. Against a 140-item hand-labelled gold test held out from training, the classifier reached precision 0.985, recall 0.944 (F1 0.964), outperforming a rule-based keyword baseline (precision 0.958, recall 0.972) and a simpler keyword baseline (precision 0.979, recall 0.648) evaluated on the same set. Applied to the full corpus, the classifier’s on-topic set (10,577 headlines) was combined by union with an independently assembled reference set (10,583 headlines), giving a final on-topic corpus of 11,082 headlines (overlap 10,078; Jaccard 0.909 between the two sets). This union was validated against independent human coding on a stratified 220-item sample (seven strata by predicted probability and source): union precision was 0.933 (95% CI 0.868–0.999) and the off-topic false-negative rate was 3.49% (95% CI 1.73–5.24%), implying a corpus-wide true on-topic count of approximately 13,177 headlines (95% CI 11,576–14,779) — the reported on-topic corpus is a conservative, high-precision subset rather than an exhaustive one. Agreement between the two independent coders on this sample was Cohen’s κ = 0.890 (9 of 220 disagreements), with essentially all disagreements occurring on headlines that require real-world context not recoverable from the headline text alone.

3.2 Stance instrument

Each on-topic item was scored on a mirrored seven-point ordinal scale from −3 (natural/zoonotic origin asserted as fact) through 0 (neutral, uncertain, both-sides or procedural) to +3 (laboratory origin asserted as fact), with graded intermediate points. The “lab-lean” reported throughout is the mean on this scale, positive values denoting a lab-ward tilt. All 11,082 on-topic headlines were scored by a single large-language-model rater (Claude Opus 4.8, Anthropic), processed sequentially in batches with an explicit, cumulative set of calibration anchors (e.g., named-official assertive lab leak claims scored ±2, procedural WHO-investigation headlines scored 0; a specific worked example — “WHO panel says lab leak theory extremely unlikely, not worth exploring further” — anchored a canonical +2 zoonosis rating) to hold scoring consistent across the full run. Before analysis, 971 exact title-and-outlet duplicates (predominantly wire-service reposts of a single story) were removed, and a further 632 headlines were flagged as not actually bearing on the origin question on inspection.

YouTube corpus construction and coding

Videos were retrieved with YouTube Data Tools, a front end to the YouTube Data API search endpoint; because that endpoint caps a single query at roughly 500 results, the corpus was assembled as a succession of day-by-day searches to approximate a census, yielding 15,611 videos published January 2020–July 2026. Restricting to videos with more than 1,000 views (9,296 after de-duplication) and then to origin-relevant content left 1,546 on-topic videos, every one rated by Claude Opus 4.8 on the same seven-point scale. Because each record carries a cumulative view count, both an unweighted and a view-weighted mean are reported, the latter approximating the stance of the average viewing rather than the average upload. Reliability was assessed against an independent rater on a blind 200-video sample (100 pipeline-on-topic, 100 discarded): on/off-topic precision 0.98 and recall 0.87 (weighted to the true prevalence); on the shared scale, agreement within one point for 94% of videos, quadratic-weighted κ = 0.73, and a mean human-minus-study difference of +0.20 — the rater leaned marginally more lab-ward, so the reported tilt is conservative.

The lab leak zombie theory is having another forced revival in 2026 with political operatives trying to once again use the power and appeal of this compelling narrative for political gain.

On June 18th 2026, on her last way out the door, director of national intelligence Tulsi Gabbard released a set of classified communications which she falsely claimed would implicate former NIAID head and pandemic advisor Dr. Anthony Fauci in the origins of COVID-19 and subsequent cover-up conspiracy. The only problem? The released documents do not support her false assertions, instead, a careful reading clearly offers snippets into a reality that very much exonerates, rather than implicates, Dr. Fauci. But who has the time to go beyond the headlines and the political spin to actually check thousands of heavily redacted pages, right?

In what Georgetown University Professor accurately described as “declassification theater” , the point of these stunts is not to offer the public transparency, or lo and behold, actual evidence of the allegation, but to provide news-baity spectacle with the allure of secret documents to reach virality.

Public perception in an information-overabundant social media environment is increasingly shaped by politicians abusing their powers and positions to manufacture pseudoevents that feed into existing narratives that are already widely believed, and that support community belonging.

Using what is sometimes called “selective disclosure” methods in disinformation and propaganda research, US politicians can abuse their congressional subpoena power, access to classified intelligence, and testimony of client propagandists to leverage an asymmetric information advantage. They decontextualize, cherry-pick and frame often real information in manipulative ways that serve their goals and that a fair, contextual reading of the information would not support.

With the veneer of “releasing secret documents or assessments”, and the press’ close relationship to the powerful, widespread mainstream news coverage is almost guaranteed, and the momentum of news coverage is usually amplified by partisan media engagements, public commentary, and a cottage industry of conspiracy myth entrepreneurs and professional opinion-havers riding the news cycle.

For the lab leak narrative, we have seen these selective disclosure methods many times before, and most of the time, it would cause a flurry of subsequent media coverage.

Since selective disclosure usually works with decontextualized true information, fast and effective refutations remain difficult because the information disclosed is usually not fabricated or false, just incomplete and distorted.

By the time fact checkers or citizens gain access to the full contextual information and perform a fair reading or analysis of the document dump, usually the news cycle has moved on, correction does not find any traction, and the manipulative framing continues to linger in the public’s memory.

That’s why selective disclosure has become a favorite of anti-reality politicians and other manipulators to shape public perception in recent years.

And this brings me to this week’s news:

The selective disclosure of Dr. Fauci’s diaries

Senator Rand Paul, who has been positioning himself as a main antagonist to Dr. Fauci during the COVID-19 pandemic, has been on a years-long, conspiracy myth and libertarian ideology-driven crusade against the former presidential advisor.

Opposed to mask mandates, lockdowns and perceived governmental health agency overreaches, Rand found a popular target for his ire, and the heated exchanges with Dr. Fauci worked well for his popularity with the MAGA base as well as fundraising efforts.

I am not an investigative or political reporter, but here is what we know from others about how lucrative Sen. Paul’s “Get Fauci” efforts have been:

So politically and financially incentivized over the years, it appears to me that Rand Paul increasingly became radicalized and deeply captured by conspiratorial narratives that place Dr. Fauci at the center of a planetary cover-up conspiracy surrounding SARS-CoV-2 via gain of function research. Unfortunately for Paul, scientific evidence can completely refute any gain-of-function origin of SARS-CoV-2, and thereby Fauci’s, NIH’s or any other scientist’s alleged involvement.

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Nevertheless, Senator Paul has repeatedly doubled down on his assertions against Dr. Fauci, from unsubstantiated claims of Fauci funding gain-of-function research (not according to legal but contested definitions and NIH judgement) to asserting he lied, perjured himself, belongs in prison for not only being involved in the supposed creation of SARS-CoV-2 to orchestrating a “deep state” cover-up. How much of it is convenient following of the conspiratorial base, and how much does he himself believe is hard to detangle.

In any case, within this larger context, Senator Paul has this week started to selectively disclose his analysis of Dr. Fauci’s diaries; under the expected “secret documents” grant fanfare with partisan outlets and commentators on X amplifying the propaganda to an audience of millions. Senator Paul is set to gain another fundraising windfall from all this attention.

Now above, I mentioned that focusing on what the dump claims to have unearthed, rather than who it benefits and why it is happening now, is an error because it amplifies the selective information and manipulative framing of the discloser.

However, given the specific nature of this selected release, I happen to have pretty good contextual knowledge of the situtation given that I have very deeply researched the lab leak narrative, from its genesis to its conclusion; and written a book about the topic.

If you are interested in the surprising details of the events that preceded for example the infamous Feb. 1 teleconference, here is the inside story. If you are just here for the quick look and refutation:

TL;DR. Paul got nothing. Less than nothing, actually the documents he provided, same as the documents that DNI Tulsi Gabbard released 2 weeks ago, are much more exculpatory than incriminating to Dr. Anthony Fauci.

They show a public health servant thrown into a position of large responsibility and public profile, who often acted in a very nuanced, measured way and in accordance with his knowledge, roles and responsibilities. Sometimes he was a bit too comfortable being admired and in the spotlight, and a workoholic with a controlling presence. Nothing outside the ordinary human experience in my reading.

Despite very harsh and unjustified public smear campaigns against him and furor within a new media ecosystem where shameless and connving politicians, media manipulators and grifters get rewarded for bad faith attacks, the fact that the best Senator Paul got after six years is mild insinuations based on private diaries kinda exposes a whole lot more about him and his motivations than Dr Fauci’s.

Conclusion

None of this is new or unexpected. Nobody should fall for this, but everybody should understand whats happening.

US Republicans have long given up on an evidence-based worldview and are engaged in perpetuating political convenient and self-serving fictions detached from factual reality.

Any type of “bombshell” they try to conjure up on decontextualized and cherry-picked emails has to be understood as a sometimes sloppy, sometimes more carefully crafted propaganda prop; and arguing within the frame of their baseless accusations without demanding scientific evidence and coherence with scientifically established facts is an error.

The reality is that lab leak truthers and conspiracy theorists have failed in 6 years to find a shred of evidence to support their belief in a lableak, or even to formulate a scientific lab leak theory that is consistent with and not contradicted by the evidence we already have.

That will not change no matter how many layers of human testimony and partisan interpretations of email communications, intelligence reports or private diaries they try to pile on to obfuscate that simple fact.

When journalists and the public are charged with assessing the validity of such supposed “bombshell revelations” (selective disclosures), manipulators count on us to be seduced by the allure of access to secret information, and argue about the content, rather than the context, of the release.

Which is a pity, because the content released this week was stale already years ago; yet the context surrounding the manipulative power of politicians and its calculated impact on public perception is more salient than ever today.

I know many readers here are similarily exhausted; so this is not to complain but to show that maybe there are small things we can do here and there.

For example, I recently created an interactive Covid-19 origins timeline based on the research in my book with the help of AI tools. It´s not perfect, but it is a lot more accessible than a 500 page book. I prototyped (or vibe-coded) the html for the timeline up in a few hours using Claude code, because I thought this is a useful thing to have and a bounded application of AI I can stand behind. (I also wrote a new AI use policy for my blog here)

Because of this experiment, I got a bit more ambitious to try to create a useful resource from our Science Counterpunch interviews. You can watch the live video explainer on top, and you can find the library here.

What the Science Counterpunch library actually is

I went back through every transcript from all ten episodes and used AI to summarize and create ultimately 305 individual insight cards. Every card is attributed by name, and 169 of them carry a direct, timestamped link back to the exact second in the original video where the guest said it to make sure context can be re-established.

The more interesting part of this library is what it makes visible, which is that there are a lot of issues, but also a lot of proposed solutions. Overall, our guests had proposed up 90+ solutions (of course with various degree of overlaps or anecdotal touch)

I believe that by making the problem and solution space parsable, at a glance, maybe it opens a way to find some nuggets of insights for people who do not have the time to listen to 10+ hours of podcast inverviews and then do the pattern-analysis on top of it themselves.

But check for yourself.

The library has many ways to explore the insights:

The Insight Card Library — search and filter across all ten episodes and according to category (e.g solutions). This is to really explore freely. You can also type in a name, a tactic, a keyword; and every guest who touched upon it.

The Problem → Solution Map — I let AI group every problem-type card into 7 clusters and every solution-type card into 7 clusters, this is not perfect but a useful way to parse the problem and solution space.

The Episode × Category Heatmap — which episodes lean hardest into which kind of content. Episode 6 for example, with Gregg Gonsalves, is almost entirely focused on actism solutions. That is not a coincidence; that is who Gregg is and what fights he has actually been in.

The Recurring Concepts Map — just a different way to show where guests overlapped (e.g many had used RFKjr as a case example of a bad actors with real-world consequences)

It’s a tool. It’s also just fun to poke around in

I don’t want to hide the second half of this.

Yes, the library exists to make tactics, systemic problems, and solutions legible fast for people with little time and much exhaustion.

But it’s also just enjoyable to click through — to follow a thread from a problem cluster to the solutions guests actually proposed for it, to go down a rabbit hole starting from one guest’s name and end up somewhere you didn’t plan on.

I built it to be explored, not learned.

Participatory engagement for people looking for inspiration in the fight against anti-science.

Maybe that is not your cup of tea.

The Counterpunch Insights library

1.49MB ∙ PDF file

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Find it here to explore: https://www.lab-leak-fever.com/science-counterpunch-library

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Either way, this exists now.

Protagonist Science is a little digital corner that tries to bring science and society closer together. That mission only works if readers can trust what they find here is not only well sourced, reasoned and argued for; but also not build to steal their time, money or emotional engagement.

Consequently, I have seen the rise of generative AI very critically, as do I see the whole campaign to shove AI chatbots down everybodies’ throats so robber billionaires can become feudal godkings while the rest of us their servs.

Unsurprisingly, I have also been a lukewarmer on AI adoption; I see the innovations in machine learning, transformer architectures etc. as a cool and fundamentally normal, but not magical, technology that is powerful when used appropriately and in bounded use cases, and pretty terrible when implemented as a syncophantic user manipulation and lock-in before enshittification tool.

That all being said, either denying this technology exists now or objecting in principle to its use does not seem to be the right way for me, especially when there are many positive visions of AI use, from kami to community.

So inspired by science journalist on her newsletter´s AI policy, I thought about what my principles might look like for AI use.

My rules

1. The blog writing is mine. Maybe I am early because I read a lot, but AI-generated prose, even when trained on style, tone and voice of my own material, tends to fall short, be bland, boring, generic and just not really worth engaging with. I will not try to avoid certain constellations or phrases now associated with AI to signal my humaness, I will just keep writing.

2. My name means my accountability. Every factual claim, citation, and argument published here ultimately comes back to me. If I used an AI tool to assist with research on something, but I can’t verify it, it doesn’t run or will be transparently and explicitly caveated as AI generated content. In general, because AI is not accountable, it should not be used in processes where accountability is required.

3. AI for summaries, aggregation, bridging of bounded content tends to be good and useful. One of my understandings of modern LLMs is that they are superhuman token manipulators; and when the control of the original data is mine, reshuffling these tokens on existing, bounded-content in many ways to sundays is just something I find very useful for me and my work. Be it to summarize interview transcripts, check references, or filter and search content for things like ad verbatim quotes is a real time saver.

4. AI-assisted coding and prototyping. I think coding is the most interesting case of bounded utility where the AI can take the druggery of coding while keeping the creative process and architectural decisions on what to code by the human. Now I am not saying anybody should use AI for really critical tasks where accountability is needed (see rule 1), but for prototyping some personal project ideas that live on the web I have to say it has now grown on me.

How I use AI

• Research and literature triage: summarizing papers or articles, surfacing related work, helping me get through a stack of potential sources faster. I will still read the primary sources myself before referencing them.

• Prototyping: AI may help me brainstorm scenarios or execute certain ideas I have to a point where I feel ready to either discard or take over as human. Just like other humans can help us feel inspired, so can whatever a machine might bring forward. Anything goes. The question is the rigor and process applied afterwards, not how it came about. (this is very much how Feyerabend talks about science under the fancy term epistemological anarchism)

• Vibe Coding: for building new html features or data analysis graphs I found it very useful. AI handles the boring, mechanical parts — boilerplate, syntax, debugging. The creative and architectural decisions — what to build and why — stay human.

• and I quote directly from Elise Cutts:

  The absurdity exception

  If a system or task disrespects my humanity, it does not necessarily deserve the respect of a human response. I may use generative AI tools to do “creative work” (writing) for absurd tasks, especially if the entity demanding and/or evaluating the task is itself an AI (e.g. hiring systems). Absurd tasks are those whose point is not to produce something high-quality, creative, meaningful, or valuable but rather to satisfy some arbitrary requirement or check a box. This also includes highly repetitive, non-creative tasks like re-formatting a list of citations.

  …and here from Audrey Tang:

The crucial line is not between assisted and unassisted production. It is between expression and obligation. A model may help me find words, but it cannot stand behind the promise those words contain. A system may help me prepare for a conversation, but it cannot inherit responsibility for what I decide to say. A tool may render my thoughts more clearly across cultural traditions, yet the intention, the commitment and the accountability must remain human.

How I don’t use AI

• I don’t use AI to draft my prose.

• I don’t let AI hallucinate what it knows.

• I don’t use AI to manufacture sources or expert quotes.

• I don’t allow AI to make up data or research notes.

• I don’t use AI to claim somebody else´s deed.

• I don’t craft AI-generated images to mislead.

Why this matters

A blog built on fighting disinformation has a higher bar than most to not perpetuate harmful information.

This policy is a living document. As my tools and workflows change, I’ll update it to match. — but the underlying commitment won’t: my words, my ideas, and my accountability mean I stand behind what’s published here, even if I don´t get it right the first time.

Cheers,

Philipp

Sometimes constantly being hit by the news cycle creates a bit of a boiling frog syndrome, where terrible injustices, corruption, abuses of power and atrocities blend together into a cacophony of exhaustion that gradually gets accepted as the new normal of our times.

We all know that it is too much, the offenses are too severe, that they can not be allowed to continue, and yet how and when exactly we have to pull the trigger of drastic action, to figuratively jump out before being boiled alive, becomes quite difficult when it turns into collective action problem.

Yet this is the current hostage state of US science.

First movers and individual outspoken actors and resistors at federal institutions and universities have become, and continue to be, more likely targets to face the full wrath of the current anti-science administration compared to their peers who keep their heads down and their mouths shut. The warming waters just seems more tolerable for too many, certainly better than the prospect of consequences followed by jumping out, losing your job, employees, career track or life’s work and facing the threat of retribution without institutional protection.

Well, this week the temperature increase was neither subtle nor gradual.

Let’s revisit.

Trumped up federal crime charges for transporting inactivated virus samples

What do round worm materials, frog embryos, fungi and deactivated virus samples have in common? Apparently, criminal prosecution under the Trump administration.

Yesterday, a flurry of news outlets reported a rather dramatic story about two “foreign scientists” being charged with a “conspiracy to smuggle monkeypox” virus into the US.

What sounds like the start of a terrorist plot is of course much more mundane for some rather minor offenses. It goes back to Jan 2026, when two virologists working for the NIH’s Rocky Mountain laboratory returned from a trip to the Congo where they have been collaboration with local scientists on containing a monkeypox outbreak. It appears from court documents that the researchers had brought back deactivated monkeypox samples (non-infectious, harmless) for either diagnostic or research purposes while declaring to customs and border patrol agents that they were transporting a diagnostic kit; and according to one unreliable whistleblower, the virologists later clarified that it was just “DNA samples”.

Researchers transferring research materials between countries is very common; but often these involve some paperwork and institutional guidelines and specialized carriers. That does not mean that carrying research materials, including certain biological specimen or DNA samples for diagnostics, by commercial aircraft is necessarily illegal or improper, it usually just requires a proper documentation and declaration at customs. The prosecution alleges that the researchers did not have proper documentation and did not declare their materials upfront, which they allege is evidence of a deliberate conspiracy to smuggle those materials in, and lying about it.

The defendants are presumed innocent until proven guilty, and the virologists in question have previously published on using inactivated monkeypox virus in exactly such diagnostic research context.

Now what struck me were not the facts of the case, where the offenses appear to be minor at best, but the tone of the indictment.

And that within ~24 hours of the DOJ press release, roughly 10–12 major outlets picked up the story, including Politico, Newsweek, Associated Press (via Yahoo and U.S. News), FOX (multiple affiliates), CBS local, NewsNation, and widely distributed aggregators like MSN and Yahoo.

“Foreign nationals” “NIH “conspiracy to smuggle” “lying”

Other press releases from the same Eastern District of Michigan U.S. Attorney in recent months read similarly off.

Chinese. Wuhan. Dangerous pathogens. Labs…. Now I don’t know about you, but I have spend five years writing about the lab leak narrative and its weaponization by anti-science manipulators and politicians, and my pattern recognition spider senses were not only tingling, but hitting me with a sledge hammer.

So I started to look deeper….

Let’s start with where I started yesterday night. The unusual language. Maybe these type of DoJ press releases are just how things are in America when it comes to “biological” materials?

So first thing I did is look into the press release history of 10+ other US attorney offices (out of 94 DoJ districts in the US). I focused on districts containing major airports and big research centers, such as Southern and Eastern District of New York, all districts in California, Texas, Florida, Massachussets.

Until 2025, I was not able to find a single press release about biological material smuggling or related items in a collective of over 50.000 press release records for those 10+ districts, including the same Eastern District of Michigan that now so overeagerly has went on a spree against Chinese researchers.

With the sole exception of Massachussets, where in July 2025 a Trump-appointed prosecutor charges a Russian scientist for bringing undeclared frog embryo research materials in, the Eastern District of Michigan US attorney seems to stand out, with a flurry of press releases on foreign aliens from Wuhan allegedly “smuggling” biological material.

As Jon Cohen from Science Magazine notes on this story, this recent charge “comes amid a recent U.S. crackdown on potential violations by researchers of the rules and regulations regarding the import of biological materials”.

Now that attorney, Jerome F. Gorgon, Jr., who was appointed to serve as Interim U.S. Attorney by Pam Bondi, has been at the center of these cases against virologists and Chinese researchers.

But is it really a crack down or biological material violations or something maybe a bit more performative?

Let´s remember the press release. They alleged deliberate lying. That there was a smuggling conspiracy to bring in monkeypox. But the court documents themselves acknowledge that these samples were not monkeypox but inactivated virus or DNA; not-infectious, not harmful. Same is true for the other “biological materials”, i.e round worms and frog embryos.

So when I looked into the previous press releases against Chinese scientists, I found a familiar cast of characters who seemed all to willing to comment as if terrorist plots have been thwarted, such as:

“Allegedly attempting to smuggle biological materials under the guise of ‘research’ is a serious crime that threatens America’s national and agricultural security,” said Attorney General Pamela Bondi. “We will remain vigilant to threats like these from foreign nationals who would take advantage of America’s generosity to advance a malicious agenda.”

“Three Chinese nationals are charged with smuggling dangerous biological materials into the country and made false statements to law enforcement,” said Secretary of Homeland Security Kristi Noem. “Thanks to our brave DHS law enforcement and the FBI, they no longer pose a national security threat. Under President Trump’s leadership, we are ensuring foreign criminals cannot abuse our visa programs to harm the American people."

"This case underscores the vital importance of safeguarding the American people and addressing vulnerabilities within foreign student and exchange visitor programs," stated acting ICE Director Todd M. Lyons. "Educational institutions must enhance their admissions procedures to prevent exploitation, which can pose risks to national security, as demonstrated in this instance. I commend the ICE HSI agents and officers who work tirelessly to protect our nation and uphold the rule of law every day."

"These charges show the FBI and our partners will aggressively investigate and hold accountable those who violate our laws, and that academic research cannot excuse illegal activity," said FBI Director Kash Patel. "The Chinese nationals charged today allegedly were involved in smuggling biological materials into the U.S. on several occasions. The FBI and our partners are committed to defending the homeland and stopping any illegal smuggling into our country."

Huh, quite the cast of characters for the terrible offense of carrying… round worms (material) for research?

So what is really going on here?

About a year ago, pulled together a team of scholars and academics to write the anti-autocracy handbook for scholars. In it, we describe how autocrats charge inconvenient citizens with often minor infractions to set an example, discourage dissent and create scapegoats.

The FBI famously scrutinized Martin Luther King´s travel receipts, wiretapped his phones, bugged his hotel rooms, and planted informants in hopes of finding ways to delegitimize him. One of our authors, also wrote about how academics in the US are again facing process-as-punishment: “Often it is not the goal or outcome that matters, but the spectacle along the way.”

Now let´s quickly return to the virologists in question; Vincent Munster, head of the virus ecology section at a division of the National Institute of Allergy and Infectious Diseases (NIAID).

For years, he has become a target of conspiratorial communities with some far-out conspiracy theorists alleging - in the most convoluted game of incoherent connections and nonsensical speculations - that Vincent Munster is the creator of COVID-19 together with Ralph Baric. Absurd of course, but not unusual as these hate communities constantly churn out new villains to sustain their conspiratorial worldview and community. Point is, Munster has had a target put on his back by these conspiratorial communities for a long time, and since many in the administration share the same tendencies and information environments, I highly doubt that what has happened to Munster is just a coincidence.

So what new directives exactly?

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Russell Voughts new commandment: We want your obedience, not your knowledge

Russell Vought is the current director of the Office of Management and Budget, or OMB in short. The OMB’s powerful role in the administration are to manage and supervise the budget of executive agencies and to implement the agenda of the president.

Russell is of course also famously entangled with the Heritage Foundation´s Project 2025, a conservative policy magnum opus full of disdain for liberal democracy, human rights, science, the environment, and anything else that is good in the world in favor of enriching the billionaires who sponsored it and the white supremacists who ideologically shaped it.

Russell has been busy to implement the 2025 agenda and now, a good year and a half in power, and after crafting many devastating assaults on the independence of science and proposing dramatic cuts to scientific agencies (that Congress rejected), he offered his next policy plan to completely eliminate the independence of US science, punish US scientists and control their associations, and basically purge anybody not willing to go along with the fascist MAGA project.

This of course did not go unnoticed, and I will just refer to some excellent coverage from fromer NIH programm officer of 22 years who first explained in detail what this new OMB rule would mean in practice:

Here is another high-profile emergency meeting organized two days ago by and Stand Up for Science discusses the proposal with historian , US Congresswoman Judy Chu, Nobel Laureate Carolyn Bertozzi, and of course :

On the printed side, there have been two very good articles in the magazine science from Derek Lowe and Editor-in-Chief Holden Thorp.

Rarely, there has been such uniform disagreement among scientists to a new policy proposal, and so much deserved attention on this topic.

The OMB´s rule to subjugate scientific grants to the whims of political appointees enforcing the presidents agenda comes on the back of NIH and NASA political appointees targeting international collaborations, banning “co-authorship with a scholar affiliated with a foreign institution, even if all the work was done in the United States” These “forbidden foreigners” could even include foreign students working in the U.S. and scientists who left the country after the research.

In short, it is mighty ugly and exactly what Nazi Germany, the Soviet Union under Stalin, and other autocratic regimes did to its scientists. Russel Vought and the second Trump administration has one clear message to US scientists:

And now this brings us back to where we started. That they are already willing to make a spectacle out of criminally prosecuting scientists for minor offenses is not an exception or a tough on “biologics materials” policy stance.

It´s a foreboding what is to come if they are not stopped.

Too many academic society and institutional leaders still are just sitting frogs in the warm water, waiting for the temperature to come down again. (h/t )

It won´t by itself. You gotta jump.

Start with defeating the OMB rule here by commenting your opposition today.

I guess that is my message.

PS: For a larger battle-plan, here are some ideas:

You might have read or heard that scientists have come under immense pressure ever since the pandemic, and specifically the second Trump administration. Given the dizzying array of outrageous news, authoritarian actions, war propaganda, brutality and blatant corruption scandals, it is easy to lose sight of the longer-term trends on some generational changes happening around us.

I’ve spent the last few years interviewing scientists and science advocates who have found themselves in an uncomfortable place they never asked to be: At the front row in the fight to resist autocratization. Many other scientists became targets of motivated actors and agendas not by defending their research or their area of expertise, but defending the principle of a shared, objective reality itself.

So I’d like to start with a bit of a data-driven summary of what has happened to US science since January 2025 on two dimensions, vaccines and science funding, using a tracking and database tool created by Prof. . Her Trump Action Tracker is extremely handy to zoom out to the larger picture and find the patterns behind the often chaotic and random-seeming day-to-day evils of the current regime.

Let’s just take a look how a federally-empowered anti-science movement has wreaked havoc in the vaccine space in the last 15 months, shall we?

Attacks on vaccines and immunization

From around 680 tracked action items pertaining to attacks on science and education, around a 115 have been focused on vaccine science, immunization, vaccine regulation or related topics. Here is a cumulative graph with vaccine actions highlighted, and a second visualization with labels showing the most severe actions based on population impact.

If anybody is interested in what the most severe actions are, here they are listed again with some comment about impact and at least one reporting source.

This is of course only one area of anti-science that the Trump administration, Acting CDC Director Jay Bhattacharya, and HHS Secretary RFKjr. and the MAHA movement have worked hard to dismantle and subvert. Here is another:

Attacks on scientific funding

Across scientific agencies such as NASA, NIH, EPA etc and federally funded universities (Harvard, Columbia…), also governmental departments such as the Department of Energy (DoE), ideologically motivated funding cuts and re-allocations are used to dismantle unwelcome science. Where that US Congress-allocated money goes is also not clear, but part of it will likely find it’s way to filling the pockets of regime-aligned beneficiaries; from Trump family and loyalists to big tech and fossil fuel interests.

The destruction of US science by the administration and the anti-science movement have mostly been met by media pundits, business elites and large parts of Trump supporters with apathy, or even tacit support.

The COVID-19 pandemic seems to have soured too many of those interest groups and powerful discourse shapers on scientists having any public voice or influence in public discussions. Especially on society-relevant topics such as technology, health, environment, defense and the economy, where scientists might contest political or business narratives with evidence and expert authority, few of those discourse shapers feel the need to speak up in defense of science.

An often quoted idiom of the billionaire-friendly pundit class and rightwing media machinery (and the NYT columnist section too) contests that “scientists themselves are to blame” for the loss of trust; that they either made too many mistakes, are ideologically captured by self-interests, brainwashed by democrats or leftwing institutions, or are part of multiple devious conspiracies, from big pharma to the deep state.

That at least a sizeable minority of ordinary US citizens believe some version of that absurd narrative is remarkable given that polls and surveys show that MOST PEOPLE STILL TRUST SCIENTISTS MORE THAN ANY OTHER GROUP.

I believe it speaks to the asymmetric power of discourse shapers to bring minority opinion to dominate not only public perception, but also political realities. Most US citizens and even Congress do not want NASA defunded, they do not want cancer research defunded, they do not support the dismantling US science, and they sure as hell want access to vaccines for their children.

So how does the anti-science crowd get away with it, in government and in discourse, against such strong public support for science?

These are hard questions that we tried to understand in our conversations at Science Counterpunch. So I wanted to drill down a little bit on some larger patterns between what the scientists, science activists, and science communicators we had on told us and maybe extract some learnings.

Writing often helps me think, and hopefully these lessons I gathered from my interviews can be useful for anybody who wants to understand or get active in the defense and support of science and scientists.

Here is the visual TL;DR summary of what defenders of science need you to know about the modern anti-science movement, it’s tactics, and why we can’t expect scientists to solve the problem without our support.

1) Anti-science is structurally, not epistemically driven

I think the first, and maybe most important key lesson is this: attacks on science or scientists are rarely driven organically; nor are they caused by confusion, error or poor science communication.

They are driven by vested interests and political power and the incentive structures they create through money, ownership, regulation, class and ideological networks, and governmental policies. Oligarchic platforms, vested industry interests, attention dynamics, culture war politics, monetization, grievance mobilization; all these incentives reward distortion of science and punish those who speak truth to power with science and evidence. Two of our guests, the esteemed scientists Michael Mann and Peter Hotez, have written a whole book about this, so I think it’s worth spending a few more words on this.

In the information age, those who get to shape what information people see, hear, consume or are exposed to wield power. Be it platform owners, influencers, politicians, media elites, power brokers or just conspiratorial or activist crowds that disproportionally participate online and get rewarded by algorithms for it.

Since I have written and spoken about how modern anti-science functions multiple times before, I will just leave you with another figure below on the eco-systemic nature of that anti-science media machinery.

Now, all fascist movements and most autocratization processes include attacks and ultimately the dismantling or subversion of science, evidence and any notion of accountability or objective truth. So the Trump administrations actions very much follow this playbook.

“This government has, led by Trump, entirely decimated the scientific ecosystem in the United States.”
— Colette Delawalla, Founder and CEO Stand up for Science

But that authoritarian playbook is not the whole story, because the anti-science ecosystem does not only operate at the level of government, but in public discourse, in online communities, in business, in religion, your doctor’s office and anywhere else where people can be reached.

Sometimes the inner workings of this anti-science machinery are obvious: anti‑vaccine entrepreneurship, “medical freedom” politics, or influencer profiles built on contrarianism. Sometimes it is quieter: the erosion of institutional norms, the lobbying against unwelcome laws and regulations, and the steady casting of expertise as corruption all converge to remove science as a tool for accountability against the currently powerful.

Most perniciously has been when seasoned anti-science grifters collaborate with the fascist movement to get into position of institutional power at scientific agencies, keeping the veneer of a somewhat functional institution but re-shaping it into a tool of propaganda, voter manipulation, and ideology; which is what happened not only with RFKjr and MAHA for HHS and vaccines, but across most federal agencies; from NASA to NIH, from CDC to EPA.

“These groups figured out that if you control the agencies, you control the narrative.”
— Peter Hotez, Baylor College of Medicine

The anti-science ecosystem has not only grown by its alignment to the fascist political MAGA movement, its rightwing media machine, and vested business interests, its now an essential part in furthering their agenda and enshrining their power.

Scientists that for decades enjoyed public trust and bipartisan support are obviously getting steamrolled and few have yet realized what formidable evil empire they are even up against.

“We’re not even in the fight. We’re literally bringing scientific and policy papers to a fucking war.”
— Colette Delawalla, Founder and CEO Stand up for Science

It’s high time for the rebel alliance to come together. If you need any pointers, I recommend checking out Colette Delawalla’s interview at the end of the article.

Let´s hammer the main point home:

2) Harassers target effectiveness, not error

I think another very clear pattern appears when looking at who gets targeted by the anti-science ecosystem and its media machinery.

The scientists most aggressively harassed across fields are rarely the most controversial or somehow sloppy with their data. The opposite: They are often the most effective communicators or have the most relevant expertise to speak publicly with authority on a topic.

“The people who get attacked aren’t the ones quietly doing bad work in a lab. They’re the ones whose voices reach outside the silo.” - Dan Wilson, Debunk the Funk

Harassment, across domains, follows a shared script to coerce outspoken scientists into silence.

1. Question legitimacy – undermine credentials, motives, or integrity of scientists when they speak up about their expertise

2. Isolate the scientist – portray them as partisan, controversial or ideologically suspect and demand their institution and social contacts distance themselves (Mike Mann calls it the Serengeti strategy)

3. Escalate harassment – threats, abuse, institutional complaints, lawsuits to intimidate and create multiple pressures for outspoken scientists

4. Wait for silence – few people can withstand sustained attacks over a long time without support. Most often, pressure campaigns lead to job loss or resignation, public withdrawal, or self‑censorship.

3) Narrative beats evidence (every time)

A recurring theme in online spaces is that storytelling is powerful.

We humans are a story-telling species. Stories help us navigate life by reducing the complexity of the natural and social world and maintaining social bonds or group-level cooperation. Storytelling represents a key element in the creation and propagation of culture, it is how we make sense of non-routine, uncertain, or novel situations.

Our Decoding the Gurus guests Chris Kavanagh and Matt Browne observed that “secular gurus” succeed not by insights but through anti‑institutional narratives. They position themselves as having answers to complex questions of science that the “mainstream” keeps from them. They spend hours building elaborate stories and spinning conspiracy myths.

Another thing that differentiates gurus from ordinary public intellectuals is the scope and width of their stories and supposed knowledge to help us make sense of the world.

“Public intellectuals are very clear about the limits of their expertise. Secular gurus don’t do that. They add strategic disclaimers, but the performance is certainty.” - Matt Brown, Decoding the Gurus podcast

Their stories offer their audience rebellion aesthetics: the thrill of insider knowledge without the cost of actually learning how things work. Even a role in a moral drama: the awakened dissenter, the persecuted truth‑teller, the heroic minority fighting the good fight against mainstream science.

Sensationalist, intriguing, emotional, or outrageous stories can shape public conversations, even when they are baseless, speculative, or plainly false. Stories as sense-making devices are full of peripheral cues such as familiarity, processing fluency, and cohesion which create an “illusory truth effect”

For a very long time, this power of storytelling has been used by leaders, powerholders, and manipulators alike to further their goals. Media manipulators are interested in creating and selling engaging stories for their bottom line, and science is often an enemy to those efforts because of its debunking potential. So discrediting mainstream science and scientists is part of the business strategy of storytellers.

On top of that, science suffers a dramatic disadvantage when it comes to storytelling because it is bound by fact. Evidence is slow. It is also often nuanced, jargoned, and hard to explain to non-experts. It demands caveats.

“I think you are at a bit of an inherent disadvantage when you’re constrained by the truth.” - Matt Brown, Decoding the Gurus podcast

There is a million ways to make a story more compelling by using fictions; there is decidedly less ways when sticking to facts.

4) Scientific norms utterly fail in asymmetric environments

Online ecosystems are mercurial, capitalistic, maybe even somewhat meritocratic, within their own logic. They monetize outrage, reward spectacle, and build identity-based loyalty. Information is a product to sell, not to educate. Those who do it best profit the most. Truth is incidental at best—and often a liability.

Channeling the feelings of audiences is what matters, not having the best or most accurate information. Scientific caveats, articulating nuance, uncertainty and limitations are inherent to scientific process and accurate communication, but they make for rather poor or dry content.

Many of our interviewees began their public engagement careers believing that their deep expertise, paired with good faith engagements, would be rewarded, or at least reciprocated. They rarely were.

“You can leave in the uncertainty, you can explain carefully—but shouting matches outperform patience every time in that environment.” - Prof. David Kipping, Cool Worlds YouTube channel

Traditional scientific discourse and civility norms fail in such an asymmetric media environment.

Science finds itself at systematic disadvantage, while that asymmetry profoundly shapes the nature of what content gets produced, what content gets seen, and what characters rise to the top of the attention economy.

“Being an edgelord works. It gets attention, it gets clicks, it gets invited on platforms.” - Flint Dibble, Archeology with Flint Dibble YouTube channel

“Everything needs to be clickbaited… We just want the clicks. We want the money.” - Kayleigh Düring, History with Kayleigh YouTube Channel

Another problem of asymmetric media environments is that they are profoundly unequal, following a “rich-get-richer” dynamic or power law distribution of attention. That means once a critical mass of attention has been reached, algorithms constantly deliver new, unsuspecting users while platforms reshape social graphs into “interest” communities around shared narratives. And once there is “audience demand” for a particular “interest”, the supply side will follow.

Given the vast amounts of money flowing into cultivating audiences and creators for the anti-science ecosystem over the last years and decades, a critical mass of misinformation merchants has built a now self-sustaining cottage industry of deception that will not go anywhere anytime soon.

“Charlatans have gotten better and better and better at building businesses from online grifting.” - Dave Farina, Professor Dave explains YouTube channel

Into this well-oiled machine of motivation, monetization and manipulation, you throw in scientists with their inconvenient facts and appeals to evidence-based discussion and expect it to go smoothly for them? Good luck.

The only thing less helpful than being left to our own devises in fighting these grifters is mainstream press implanting themselves as supposed neutral mediators of the conflict.

Giving equal airtime to radically unequal claims, adopting the grifter’s framing of the issue, tripping over themselves to sanewash, whitewash or otherwise rationalize the words and actions of grifters to put them in the best light and most cheritable interpretation are deeply harmful acts.

And the press’ reason for it are so petty and self-absorped; it’s to simulate an outdated journalistic ethos of their own “view from nowhere” neutrality, that they take no sides, have no stakes, and no skin in the outcome. All they end up doing is being played for suckers.

“False balance. Performative neutrality, sort of two sides of the same coin. And it has been completely exploited by bad actors.” - Mike Mann, University of Pennsylvania

5) Disinformation sticks because of psychology, not ignorance

One of the most frustrating realizations for scientists and science communicators alike is that misinformation does not evaporate once a claim is labeled false, corrected, or debunked, even if the correction is taken up by audiences. This is not a deficit of intelligence or education. It is a feature of human cognition. Once an idea enters memory, it continues to exert influence even after it has been consciously rejected.

“It’s very difficult to unbelieve things. Once you’ve heard it, it’s in there.” — Prof. Stefan Lewandowsky

People may acknowledge that a claim is false — and yet they still continue to reason as if it were true minutes later.

Repetition compounds the problem: familiar ideas feel more credible, regardless of accuracy. Add emotion, identity, or narrative coherence, and even consciously rejected, but internalized falsehoods gain an undue influence on our minds and decision making.

This has profound consequences in an information environment optimized for repetition, novelty, and emotional reward driving virality.

“I was depressed and I was disabled… all I could do was sit or lay around… and that makes you watch a lot of YouTube” - Kayleigh Düring, History with Kayleigh YouTube Channel

Disinformation is more prevalently believed in spaces where scientists rarely show up or are seen; from entertainment to online communities and social platforms.

Disinformation does not need to be elaborate to be effective; it only needs to be circulating faster to reach people that have not been exposed to alternative explanations and thus internalize it as knowledge on a topic they might never have thought about before.

6) Institutions externalize costs of engagement to individuals

The lack of courage and silence from institutions may be the most damning pattern of all for individual scientists that come into the crosshair of the anti-science movement.

On the one hand, scientists are encouraged to engage publicly by their intuitions. Grant proposals reward “broader impact.” Universities praise public visibility and might even recruit students and faculty based off it. Journals celebrate influential voices speaking up against power. But when backlash arrives, the costs are privatized.

Harassment, burnout, and career risk are treated as personal resilience failures rather than predictable system outputs.

“We had mass movements. Now we tell individuals to be brave—and leave them alone when things go south.” - Gregg Gonsalves

The message this sends is unmistakable: public engagement is encouraged in theory, but unsupported in practice. The system praises courage abstractly, yet engineers conditions where the rational response is silence.

Institutions often justify this abdication by invoking non‑partisanship, academic freedom, or liability concerns. In reality, these explanations collapse under scrutiny. Choosing not to protect scientists facing coordinated harassment is not apolitical; it is a political choice with dire consequences. It cedes ground to actors who understand that asymmetric pressure works — and that institutions will look away.

The result is a tragedy of collective action. Each institution acts as if the problem of scientists under attack is marginal, exceptional, or external. In aggregate, their inaction normalizes intimidation as a cost of doing science in public. What should be treated as an attack on the integrity of knowledge production that required collective action get quietly reframed as a problem or failure of individuals.

What can be done to fight back?

This has been one of the key questions that I have been occupied with for at least the last five years and that I also posed to most, if not all, of my interviewees out there fighting the good fight. So of course I am not gonna leave you without some actionable solutions to our current problems. In fact, that is the whole point of our Science Counterpunch community.

As you can imagine, there were many fascinating answers, first-hand experiences and practical ideas out there. As my first analysis on the solution space, I tried my best to categorize and group them, look for commonalities across and boil them down drastically to what I believe is a set of broadly agreed actions. There is no single solution, but a set of things we all probably should have been doing years ago and need to start doing today.

Below is again the visual TL;DR summary. I will keep writing and talking more about this in the future, but check out all our interviews below and let´s wrap this long article up.

The growing gap between science and society

Over the last few years, we have seen the gap between science and society widen. While most citizens around the world still believe that scientists are trustworthy and work for the public good, a lot of noise and doubt has been introduced into that relationship by a well-funded, manipulative anti-science ecosystem. We can see the cracks in funding, vaccination rates, muted responses and apathy to a fascist movement feeding US science into the woodchipper.

“Doubt is our product”, has the tobacco industry famously coined. With the modern anti-science juggernaut, we are at this point again. And we seem to be heading faster and faster in the wrong direction, both scientists and society can feel it.

Scientists alone can not defeat an anti-science machinery they did not create. What we can do is ask for help. Give guidance. Start acting and hope others will join.

So to me, the real question of this moments seems no longer whether science can explain itself better to society, but whether society is willing to defend the conditions under which evidence-based discourse, and with it science and democracy, can still exist.

The answer is up to all of us.

PS: If you want to hear more from people who fight back against anti-science, all our interview conversations are freely accessible:

Is a cosmic rock truly an alien spaceship that the government does not want you to know about? Misrepresentations of scientific inquiry or hypotheses often aren’t an accident, but a structural by‑product of how curiosity, media incentives, and speculation collide. Space science, especially the search for alien life, sits at the perfect fault line: high uncertainty, high awe, and enormous public attention. The result is a constant churn of overreach, misinterpretation, and claims that outrun the evidence.

This week on Science Counterpunch, we’re joined by astrophysicist David Kipping—director of the Cool Worlds Lab at Columbia University and creator of the Cool Worlds channel—to examine how serious science pushes back. We unpack why astronomy and astrobiology attract so much distortion, how careful speculation differs from storytelling dressed up as science, and what it means to communicate uncertainty without killing curiosity.

We talk about:

• why space and alien life grab the public imagination—and why that makes audiences vulnerable to grifters

• the difference between compelling speculation and testable scientific hypotheses

• working with institutions like NASA, and where institutional communication succeeds or fails

• the risks and rewards of engaging massive platforms that don’t consistently respect scientific limits

• what scientists, creators, and audiences can do better or differently to stop misrepresentation before it hardens into belief

Being careful and evidence-driven isn’t about shutting down wonder or fun speculations. It’s about protecting them—by keeping evidence in charge.

Science Counterpunch is a punchy YouTube-first podcast that exists to defend the Enlightenment in an age of information warfare. We expose merchants of doubt, amplify experts under attack, and arm you with the tools to spot anti-science rhetoric before it spreads.

Evidence matters. Reason isn’t optional. Let’s counterpunch.

Find the full playlist of Science Counterpunch here.

Follow, like and subscribe to Sam´s YouTube channel to watch the video recording and not miss any upcoming episode. Any thoughts and feedback? Let us know in the comments!

Subscribe for free to receive updates on my work and join the fight for an evidence-based worldview.

Anti-science isn’t a bug in the modern information ecosystem—it’s the feature. Today’s secular gurus don’t need robes or rituals; they wield academic credentials, technical jargon, and a galaxy-brained confidence that turns YouTube, Twitter, and podcasts into pulpits. Their gospel? That institutions are corrupt, science is suspect, and only they have the answers.

This week on Science Counterpunch, we’re joined by Chris Kavanagh and Matt Brown, hosts of Decoding the Gurus, for a forensic look at the rise of anti-science influencers and the cult dynamics that keep their audiences loyal. We dissect how “decorative scholarship” and anti-institutional rhetoric undermine trust, why audiences crave affirmation over information, and what happens when universities and media fail to defend the basics.

We talk about:

• the anatomy of a secular guru—and why credentials are both weapon and shield

• how online communities form around grievance, identity, and ritualized in-group policing

• the psychology of audiences: why emotional energy, resentment, and narcissism fuel the ecosystem

• why institutions struggle to respond; and what academic freedom really means in the age of information warfare

• practical strategies for fighting back: critical consumption, evidence, and refusing to feed the fire

This isn’t about dunking for sport. It’s about understanding the playbook—and arming yourself for the next round.

Science Counterpunch is a punchy YouTube-first podcast that exists to defend the Enlightenment in an age of information warfare. We expose merchants of doubt, amplify experts under attack, and arm you with the tools to spot anti-science rhetoric before it spreads.

Evidence matters. Reason isn’t optional. Let’s counterpunch.

Find the full playlist of Science Counterpunch here.

Follow, like and subscribe to Sam´s YouTube channel to watch the video recording and not miss any upcoming episode. Any thoughts and feedback? Let us know in the comments!

Subscribe for free to receive updates on my work and join the fight for an evidence-based worldview.

Modern authoritarianism doesn’t arrive with tanks. It announces itself with spreadsheets, budget cuts, accreditation fights, and the quiet capture of institutions most people barely notice—until they’re gone.

This week on Science Counterpunch, we’re joined by Professor , Professor of Operational Research at UCL and creator of the Trump Action Tracker, a data‑driven record of nearly 3,000 actions documenting the attacks on democratic and scientific institutions in the U.S.

Drawing on her public communication work with Independent SAGE, Christina now raises the alarm about US politics with hard-to-refute data; explains why universities, regulators, media, and science itself are always early targets, and how fear and anticipatory compliance do much of the authoritarian work for free.

We talk about:

• her data collection project “Trump action tracker” and the administration’s method behind the madness

• why modern authoritarianism is quiet, bureaucratic, and strategic

• how controlling data and “official numbers” beats outright censorship

• why institutions don’t protect themselves—and often can’t

• how vulnerable UK institutions really are (even the ones you assume are safe)

• and why paying attention, speaking up, and refusing to disengage still matters

This isn’t about doom-scrolling news. It’s about pattern recognition—and a warning from someone who knows how quickly “it can’t happen here” turns into “it already has.”

Science Counterpunch is a punchy YouTube-first podcast that exists to defend the Enlightenment in an age of information warfare. We expose merchants of doubt, amplify experts under attack, and arm you with the tools to spot anti-science rhetoric before it spreads.

Evidence matters. Reason isn’t optional. Let’s counterpunch.

Find the full playlist of Science Counterpunch here.

Follow, like and subscribe to Sam´s YouTube channel to watch the video recording and not miss any upcoming episode. Any thoughts and feedback? Let us know in the comments!

Subscribe for free to receive updates on my work and join the fight for an evidence-based worldview.

What happens when fringe anti-vaxxers move from fleecing online communities to the highest halls of power?

This week on Science Counterpunch, we’re joined by Dr. Dan Wilson, molecular biologist and creator of the Debunk the Funk YouTube Channel, to dissect how anti‑vaccine narratives became mainstream—and why so many institutions seem unprepared to stop them.

Dan walks us through his journey from being conspiracy‑curious as a teenager to becoming a meticulous science communicator, explaining why teaching the scientific method matters more than just throwing facts at people. We unpack the rise of COVID contrarians, the business model behind misinformation, and how grifters learned to weaponize frustration, identity, and “medical freedom.”

We also talk about:

• Why journalists keep asking the wrong questions

• How figures like RFK Jr. slip past accountability

• Why being polite to ordinary people is imperative, yet being polite to grifters a recipe for disaster

• What burnout looks like when misinformation keeps winning

• And how ordinary people can still make a difference without losing their sanity

This isn’t about losing faith in humanity. It’s about learning how bad ideas spread—and how to push back with evidence, empathy, and better questions that spark curiosity rather then reactance.

Science Counterpunch is a punchy YouTube-first podcast that exists to defend the Enlightenment in an age of information warfare. We expose merchants of doubt, amplify experts under attack, and arm you with the tools to spot anti-science rhetoric before it spreads.

Evidence matters. Reason isn’t optional. Let’s counterpunch.

Find the full playlist of Science Counterpunch here.

Follow, like and subscribe to Sam´s YouTube channel to watch the video recording and not miss any upcoming episode. Any thoughts and feedback? Let us know in the comments!

Subscribe for free to receive updates on my work and join the fight for an evidence-based worldview.

In this episode of Science Counterpunch, we welcome epidemiologist, MacArthur Fellow, and lifelong AIDS activist Gregg Gonsalves to talk about what happens when politics is attacking public health.

Gregg was on the front lines of the AIDS epidemic with ACT UP in the 1990s, helping to force institutions like the NIH and FDA to accelerate research and expand access to lifesaving treatments. Later, he brought that same activist-scientist playbook to South Africa, confronting deadly AIDS denialism at the level of government policy.

What happens today in the US not only echoes but in many cases exceeds the terrors of the past.

We talk about state-sanctioned pseudoscience, the capture of public-health institutions by political actors and charlatans dead-set on burning down the house, and what has already been destroyed for a generation. We also dig into what activists and scientists did in the 90s to change the course of history—and what those lessons mean now, as global health systems face funding cuts, political sabotage, and a new wave of anti-science ideology.

How do you defend public health when the notion of reality itself is under attack?

You speak up. You organize locally. And you fight them for every school board, city council or community leadership seat at the tables where you can make the lives of people around you better.

Science Counterpunch is a punchy YouTube-first podcast that exists to defend the Enlightenment in an age of information warfare. We expose merchants of doubt, amplify experts under attack, and arm you with the tools to spot anti-science rhetoric before it spreads.

Evidence matters. Reason isn’t optional. Let’s counterpunch.

Find the full playlist of Science Counterpunch here.

Follow, like and subscribe to Sam´s YouTube channel to watch the video recording and not miss any upcoming episode. Any thoughts and feedback? Let us know in the comments!

Subscribe for free to receive updates on my work and join the fight for an evidence-based worldview.

Ancient aliens. Lost Ice Age civilizations. Atlantis hidden under the pyramids.

Pseudo-archaeology is having a moment—and it’s not just harmless fun.

In this episode of Science Counterpunch, we step into the ring with archaeologist Flint Dibble and science YouTuber Kayleigh Dunning to break down how conspiracy history took over the internet—and what it takes to fight back.

We talk about the rise of viral pseudo-history pushed by figures like Graham Hancock, why “secret knowledge” narratives spread so easily online, and how social media incentives reward myths over evidence.

But this isn’t just about bad history. It’s about anti-intellectualism, harassment campaigns against scholars, and the growing gap between academic knowledge and public discourse.

So how do you push back?

By stepping into the arena. By meeting audiences where they are. And by showing that our human history is far richer than grifter fantasies want to make you believe.

Science Counterpunch is a punchy YouTube-first podcast that exists to defend the Enlightenment in an age of information warfare. We expose merchants of doubt, amplify experts under attack, and arm you with the tools to spot anti-science rhetoric before it spreads.

Evidence matters. Reason isn’t optional. Let’s counterpunch.

Find the full playlist of Science Counterpunch here.

Follow, like and subscribe to Sam´s YouTube channel to watch the video recording and not miss any upcoming episode. Any thoughts and feedback? Let us know in the comments!

Subscribe for free to receive updates on my work and join the fight for an evidence-based worldview.

You can’t fact-check your way out of a system designed to amplify lies.

This week on Science Counterpunch, we’re joined by cognitive psychologist Stephan Lewandowsky to dissect the machinery of modern disinformation. We explore why falsehoods leave a cognitive footprint — and why even highly educated people can fall for propaganda and reason themselves into nonsense.

We dig into:

• The psychology of “sticky” misinformation

• Why intelligence isn’t immunity

• How social media architecture supercharges conspiracy thinking

• What the EU’s Digital Services Act gets right about platform power

• Why democracy depends on “epistemic integrity”

• And what scholars can do when autocracy pressures academia

Democracy runs on shared facts, so what happens when those facts are systematically undermined?

We take a hard look at how cognition, algorithms, and power collide — and what it will take to defend reality.

Science Counterpunch is a punchy YouTube-first podcast that exists to defend the Enlightenment in an age of information warfare. We expose merchants of doubt, amplify experts under attack, and arm you with the tools to spot anti-science rhetoric before it spreads.

Evidence matters. Reason isn’t optional. Let’s counterpunch.

Find the full playlist of Science Counterpunch here.

Follow, like and subscribe to Sam´s YouTube channel to watch the video recording and not miss any upcoming episode. Any thoughts and feedback? Let us know in the comments!

Protest isn’t radical. Silence is.

This week on Science Counterpunch, we’re joined by Colette Delawalla, clinical psychology PhD candidate and founder of Stand Up for Science, for a furious, clear-eyed breakdown of how American science is being dismantled in real time—and why scientists can’t afford to stay “above politics” anymore.

From mass purges at federal agencies and frozen clinical trials to banned words lists and regime-sanctioned pseudoscience, Colette lays out how the Trump administration has turned science into a political weapon. This isn’t abstract policy debate: patients lose hope, researchers lose careers, and the public loses protection.

We dig into how a single act of defiance—“fuck it, let’s protest”—sparked the first mass mobilization against Trump 2.0, why appeasement by legacy science institutions is a dead end, and what actually works when democracy and evidence are under coordinated attack. Along the way, we talk whistleblowers, organizing under pressure, why “science is apolitical” is a myth, and why bringing white papers to a political war guarantees defeat.

This episode is about harvesting anger productively, taking up more responsibility, and drawing lines.
If science is a public good, defending it means showing up—and saying no.

No neutrality. No appeasement.
Just resistance, strategy, and a counterpunch.

Science Counterpunch is a punchy YouTube-first podcast that exists to defend the Enlightenment in an age of information warfare. We expose merchants of doubt, amplify experts under attack, and arm you with the tools to spot anti-science rhetoric before it spreads.

Evidence matters. Reason isn’t optional. Let’s counterpunch.

Find the full playlist of Science Counterpunch here.

Follow, like and subscribe to Sam´s YouTube channel to watch the video recording and not miss any upcoming episode. Any thoughts and feedback? Let us know in the comments!

This week on Science Counterpunch, we step into the ring with one of the most uncompromising voices in online science communication: Dave Farina, better known as the creator of Professor Dave Explains.

Dave joins Sam Gregson and Philipp Markolin for a no-holds-barred conversation about the modern pseudoscience economy: how misinformation spreads, why it pays so well, and how grifters, influencers, and political actors exploit distrust in science for profit and power. From antivax propaganda and flat-earth cults to billionaire-backed “anti-establishment” narratives, we break down how the science denial ecosystem works—and why it’s more dangerous than ever.

We dig into Dave’s famously combative style of debunking, the ethics and effectiveness of punching back hard, and whether politeness has quietly helped misinformation go mainstream. Along the way, we talk burnout, audience capture, cult dynamics, algorithmic incentives, and why factual discourse so often loses to flashy lies online.

Most importantly, this episode asks a hard question for scientists and communicators alike: if science denial is now institutionalized, what does fighting back actually require—and who needs to get into the trenches?

No false balance. No kid gloves. Just evidence, context, and a right hook straight to pseudoscience.

Science Counterpunch is a punchy YouTube-first podcast that exists to defend the Enlightenment in an age of information warfare. We expose merchants of doubt, amplify experts under attack, and arm you with the tools to spot anti-science rhetoric before it spreads.

Evidence matters. Reason isn’t optional. Let’s counterpunch.

Find the full playlist of Science Counterpunch here.

Follow, like and subscribe to Sam´s YouTube channel to watch the video recording and not miss any upcoming episode. Any thoughts and feedback? Let us know in the comments!

What do vaccines and climate science have in common? The same political actors, media ecosystems, and financial interests have worked to discredit both.

In this inaugural episode of Science Counterpunch, Dr. Peter Hotez and Dr. Michael Mann go head-to-head with the modern anti-science machine—petrostates, plutocrats, propagandists, performative media, wellness grifters, and the platforms amplifying them.

We break down the tactics: gaslighting, false balance, “freedom” rhetoric, debate traps, and the weaponization of uncertainty. More importantly, we ask what it costs when societies can no longer agree on basic facts.

This is frontline testimony from scientists who’ve taken the hits—and refused to stay quiet.

If you care about science, public discourse, or the future of evidence-based policymaking, this is one to listen to.

Science Counterpunch is a punchy YouTube-first podcast that exists to defend the Enlightenment in an age of information warfare. We expose merchants of doubt, amplify experts under attack, and arm you with the tools to spot anti-science rhetoric before it spreads.

Evidence matters. Reason isn’t optional. Let’s counterpunch.

Find the full playlist of Science Counterpunch here.

Follow, like and subscribe to Sam´s YouTube channel to watch the video recording and not miss any upcoming episode. Any thoughts and feedback? Let us know in the comments!

For years, science and scientists have come under pressure from anti-science influencers, propagandists, conspiratorial crowds, deep-pocketed industries and politicians in power.

While the visibility and velocity of these attacks have increased general awareness and raised alarm in the wider scientific community, especially since the second Trump administration, many scientists feel trapped between a rock and a hard place. Institutions they thought would have their back either caved or got corrupted, played it safe in silence or tried to appease. Academic societies are slow to wake up and find their spine. And the press was all too often complicit in sanewashing insanity, simulating neutrality while justifying abuses of the aggressors and shifting blame onto scientists.

We have had enough.

When systems fail, when aggressors threaten, when we get suckerpunched by fascist goons and lose the first round, we don’t give up; we get back up and ready for round two.

This fight has just started, and in our corner there is plenty of reason for hope. We got the brains. We got the evidence. And more importantly, we got the extraordinary courage of ordinary people, scientists and citizens alike, to fight back and not relent when the going gets tough.

So join us, when we bring on scientists under pressure, science communicators, science journalists, activists to explain how to fight back for science.

Every episode will cover new case studies, hard-earned experiences and concrete solutions from people in the fight already. We need to listen and learn. And just maybe, their actions and insights will create a roadmap of effective actions for all of us too.

The time of lying flat on the mat is over.

Now we get up and fight for the future of science and democracy.

Check out our inaugural episode:

Get ready.

Note: This article is a first essay out of my larger research focus on building participatory democracy in the digital age: how to counteract the global authoritarian movement. Given recent AI news and a sense of urgency, I wanted to share one idea that maybe is worth a discussion today.

Unease about the AI investment boom is everywhere

The Atlantic’s excellent article by Charlie Warzel and Matteo Wong “Here’s How the AI Crash Happens” inspired something that has been on my mind for quite some time. I will get to that in a bit, but let’s recap:

Quoting from the article:

“The AI boom is visible from orbit.” Fields in Indiana now host vast data centers that “demand more power than two Atlantas.” The U.S., they argue, is becoming an “Nvidia-state,” where one chipmaker has become a “precariously placed, load-bearing piece of the global economy.”

Despite hype, profits lag: “Nearly 80 percent of companies using AI discovered the technology had no significant impact on their bottom line.” Analysts whisper “bubble.” OpenAI lost $5 billion last year; Microsoft’s AI losses topped $3 billion.

The article likens today’s frenzy to “the canals, railroads, and fiber-optic cables laid during past booms.” Whether AI transforms the world or triggers a crash, the authors warn, “either outcome will bring real, painful disruption for the rest of us.”

It paints a vivid picture of America racing headlong into an AI-driven infrastructure boom that could reshape—or destabilize—the global economy.

In a matter of years, AI infrastructure has come to dominate American growth. Vast energy-hungry data centers rise from farmland; trillions flow into chips and computing power. I think the authors point out, correctly, that the economic return remains uncertain, I recently argued a similar point about AI and productivity loss and why that might be. So rapid economic windfall justifying the investments seems very unlikely. Like many others, the authors point to the dot-com and other infrastructure bubbles; history suggests such frenzies rarely end smoothly. Whether the AI revolution fulfills its promise or collapses under its own weight, they conclude that shock will be profound, and the United States may already be too invested to turn back.

For me, there is no real question whether this is a bubble, of course it is. But everybody seems to think they can ride it long enough to be not harmed when it inevitably bursts.

As The Atlantic article pointed out, the bigger the bubble gets, the more people will get harmed by the ensuing fallout. Yet hunger from the companies for finding ever more convoluted, reckless and possibly illegitimate ways for money to be poured into their ecosystem to stretch the AI bubble just a bit longer is palpable.

And if the dynamics also sound familiar, it’s because not two decades ago, the Great Recession was precipitated by banks packaging risky mortgages into tranches of securities that were falsely marketed as high-quality. By 2008, the house of cards had collapsed. - The Atlantic

Which is why, when the WSJ just a few days ago reported that the OpenAI CFO calls for a federal backstop, more than a few eyebrows were raised by investors. The comment was followed by a quick supposed walkback from the CFO on LinkedIn, but not really since she just rephrased the point more politely about the government having to “play its part”. Privatize the win, socialize the losses I guess.

All while the systemic risk of a major recession increases by the day.

So why are we allowing them to take the gamble?

Know the game before you gamble

Several stories are told of why the current AI race, despite being a bubble, needs to happen as fast and recklessly as it does, no matter the cost, harms or methods deployed. That China will otherwise win the AI race is one such current crowd pleaser, especially out of the CEO of NVIDIA who coincidentally would gain the most by stoking such US anxieties. Or that AI will unlock untold productivity and lead to real value creation in every sector of the economy soon. Well, I am more of the persuasion that AI is a normal technology, useful and transformative in the long run, but not magic. It seemingly follows a normal S-curve of innovation and people overextrapolate from the current slope while ignoring that we are already seeing some signs of a plateau. But whatever your belief in economic gains in the mid to long-term, I would certainly like to retire the bedtime story that today’s AI boom is a moonshot for machine sentience, and not only because these graphs look immensely silly:

The current AI paradigms will inspire innovators to find applications that actually add value to various industries; but they can not usher in AGI, singularity or extinction. And yet, a combination of these stories and their penetration of the public infosphere, especially the part about imminent or future superintelligence, ushering in various visions of utopia or dystopia, seems to inspire investor FOMO and public imagination.

So let me challenge that frenzy with a different story, one I believe to be more grounded in history and reality, and in many ways more urgent:

It’s the robber barons, rails, rents and defaults of the next twenty years I worry about, not skynet, the singularity or misaligned paperclip optimizers.

Infrastructure ownership: it’s the rails, not the robots

Infrastructure capture refers to the consolidation of essential systems, such as transport, energy, communications, or now AI tech stacks, under the control of a small number of private actors. Historically, this pattern has produced enduring power asymmetries. When a resource becomes indispensable for competition in the market and cannot be reasonably duplicated, its owner wields structural power. When public infrastructure gets privatized or commodified into a corporate chokepoint, those who own it do not merely extract rent; they set the terms of participation in economic and civic life.

A classic example is the Gilded Age railroad monopolies in the United States. By the late 19th century, a handful of companies controlled the rail network, enabling discriminatory pricing and political leverage while producing the largest wealth inequality between a small elite and masses in poverty.

We have seen the same more recently with the big social media platforms, that for too long were treated as consumer products, when in reality they aimed to become the roads and bridges of digital life for most of us while extracting a heavy rent on our attention. That rent did not only make them filthy rich but also extremely powerful and politically influential, enshrining continued exploitation of their users data as their business model.

AI infrastructure magnifies these stakes, as AI tech stacks are becoming the interface to information creation, dissemination and consumption. If a few companies own the chips, data centers, cloud compute, foundational models, model weights, and distribution channels, they effectively control any future useful AI application build on top of it; and with it, the epistemic and economic arteries of the 21st century.

The gamble to become the next Vanderbilt, Rockefeller or Carnegie’s of the info age are long underway. Current tech giants have already captured chips and cloud computing, that is why Nvidia’s data‑center revenue hit $18.4 billion in a single quarter—up 409% YoY as AI hyperscalers started hoarding H100 chips like potable water before a drought. Amazon plowed $8 billion into Anthropic so Claude will use Amazon Web Services (AWS) as its primary cloud and training partner, and will utilize Amazon’s custom AI chips. OpenAI will purchase an additional $250 billion of Microsoft Azure cloud compute and locked its model distribution to Azure’s cloud for the next decade.

Such infrastructure costs billions and billions of dollars to provision and maintain, and it’s highly depreciable. In the case of the hyperscalers, the staggering cost is cross-subsidized by other businesses–themselves also massive platforms with significant lock-in […]

In short, the problem here is not that Signal ‘chose’ to run on AWS. The problem is the concentration of power in the infrastructure space that means there isn’t really another choice: the entire stack, practically speaking, is owned by 3-4 players.

- Meredith Whittaker on Bluesky

This brings us to the next point:

Strong-arming society into technological lock‑in

Infrastructure capture is not just about finding one bottleneck to own, because bottlenecks can be remedied with just building more capacity over time through market competition or government investment. Real infrastructure capture today is much more about owning the full value-chain, tech stack or ecosystem. That is why the current AI players aim to cement vertical control—chips → cloud → model → API—where each layer enforces the others and makes competition almost impossible. The current AI web of partnerships and strategic investments have only one goal: to entrench big tech incumbents across multiple layers of the value chain.

Good luck trying to spin up an alternative service provider when technical incompatibilities, contractual exclusivity and prohibitively expensive user switching cost sabotage any type of fair competition.

Historical examples include AT&T’s telephone monopoly and Microsoft’s bundling of Windows and Internet Explorer in the 1990s, both of which stifled competition until antitrust interventions, and they seem really tame compared to the AI tech stack capture we observe today by what is basically an industry cartel.

One idea we have to get rid ourselves of is the thought that technological lock-in just happens as a feature of innovation or first-mover advantage by offering new technological capabilities. No, these are deliberate business decisions as rapid adoption is the biggest challenge these companies face, they need to race to entrench themselves before the dust settles.

We can feel their urgency by opening any app these days. They simply put their AI anywhere so people can not escape it. Again, this is not coincidence:

Here is an article by Brian Merchant puts it succinctly: How big tech is force-feeding us AI.

By inserting AI features onto the top of messaging apps and social media, where it’s all but unignorable, by deploying pop-ups and unsubtle design tricks to direct users to AI on the interface, or by pushing prompts to use AI outright, AI is being imposed on billions of users, rather than eagerly adopted.

When your AI business model is to extract rent and exert power through infrastructure and technological lock-in, you better find a million ways to force people to adopt your AI stuff, no matter how crappy, immature or outright unsafe, by any and all means necessary, even leveraging the Trump administration to pressure EU regulation.

Technological lock-in is key because it ensures dominance of tech-turned-AI giants for generations to come. And we know that dominant firms face little pressure to improve quality, consumer protection, or maintain reasonable prices. Instead, once we are locked in, the real squeeze can start.

Preparing for the big squeeze with data colonialism

AI models are built on collective data: the internet’s archives, social media posts, public domain works, academic research, and user interactions. Yet, as these commons are appropriated into proprietary model weights, they cease to be shared public knowledge and become enclosed corporate property.

The AI hunger for data is palpable, not least shown by a steady drip of licensing deals between content publishers and AI hyperscalers.

With a lot of money going around, cash‑starved newsrooms are happily negotiating with AI firms whose models already cannibalize their traffic but now promise them a share of the AI boom and newfound social relevance.

Take a look at The Associated Press:

The news organization has spent the last nine to 12 months making its tens of millions of content assets across text, video, photos and audio formats, machine-readable for LLMs to assimilate easily. […]

“The best AI has the best inputs and generates the best outputs. This is the inverse of garbage in, garbage out,” said Roberts at the summit. “This means that in the future, we need more good quality, high quality content, not less. We’re going to transform the entire multi-trillion-dollar global economy based on AI, and AI fundamentally needs great information to be great”

- Jessica Davis, Digiday

Then there’s Reddit, which disclosed AI data‑licensing contracts with Google and OpenAI, selling their user content for training in exchange for boosts in AI search, immediately tripling their user base thanks to Google AI search.

Sounds like a win-win, right? Let me come to that in a second.

Before, we need to also acknowledge that AI hyperscalers are rarely so kind to ask for information, rather than pirating it by scraping the internet or worse. All AI companies are currently in legal fights over their blatant copyright infringement of information they had no legal way of obtaining, such as books or art. Anthropic recently settled one case for $1.5 billion for pirating half a million books. Peanuts for AI hyperscalers drunk on investor money and the prospect of robbing humanity blind in the future.

But this will make AI just more useful to users, so why worry about how companies get there?

This dynamic mirrors what Nick Couldry and Ulises Mejias coined data colonialism: the systematic appropriation of human life through data extraction, justified by narratives of progress and innovation. There was also a time when big tech platforms, from google search to social media platforms, felt genuinely useful and empowering to users. How did that turn out?

The Canadian writer Cory Doctorow coined the term “enshittification” to describe the lifecycle of digital platforms that initially serve users, then prioritize business customers, and finally exploit both for maximum profit.

Remember social media platforms that once felt like open, empowering infrastructure? It is no coincidence they quickly devolved into an extractive apparatus for mass exploitation, with all the negative social and political consequences for society we have to grapple with today.

The AI data colonialism currently happening is even more worrisome. The common goods of our digital lives—language, images, art, stories, code—are either mined, bought or simply stolen to produce systems that we then must rent access to through corporate APIs and subscriptions. Every prompt becomes a micro-transaction in a planetary rent economy, and everybody will pay for what was once a public good.

And the social and political consequences will be almost unfathomable.

Something new: owning the interface to reality

Historically, media theorists have warned that the medium shapes the message. Today, it is more like: Control the interface, control the story.

As AI systems are installed as the default lens on the web, they act as new gatekeepers that will arbitrate which facts surface and which fall through the cracks. How thoroughly vulnerable this approach is to the whims of billionaire oligarchs that own the AI systems will surprise exactly nobody who just paid a glimpsing look at Elon Musk’s Grokipedia.

“Shortly after launch, several sources described articles as promoting right-wing perspectives, conspiracy theories, and Elon Musk’s personal views. Other criticism of Grokipedia focused on its accuracy and biases due to AI hallucinations and potential algorithmic bias.”

-Wikipedia (which is actually a community-based model that has proven invaluable to the world)

This is a subtler, more pervasive form of any previous censorship or propaganda system because it operates under the guise of assistance and personalization while selling a very specific and narrow ideological worldview.

The more these captured AI models mediate our access to information, summarizing search results, generating news reports, drafting our communications, the less we experience the raw plurality of perspectives that once defined the open web.

Gatekeepers, censorship and propaganda are of course only the surface of how bad things can get.

Because AI is currently also deployed to create an unmeasurable amount of slop, deep fakes, fan fictions and disinformation that fundamentally will pollute and destroy the information ecosystem as we know it and make it basically unusable for human agents. Leading the pack is of course X.

“We’re trending quickly toward an internet that could be 99.9% AI-generated content, where agents and bots outnumber humans not just in traffic but in creative output. AI agents chat with each other on forums, generate news articles, create thought leadership, engage on social media, leave product reviews, spark controversy, and post memes. Each bot believes it’s talking to a human. Each human statistically is engaging with a bot. Every interaction seems plausible, even engaging. But it’s all synthetic.”

- Benjamin Wald, Galaxy

When the signal to noise ratio of any true information is one in a million within an ocean of related, personalized and microtargeted lies that are optimized to be emotionally compelling, what confidence can we ever have in any information we consume?

Our current chaotic and broken information ecosystems already breed epistemic nihilism, where citizens believe that nothing is ever really true except for what feels right and convenient in the moment.

It is no surprise so many people turn to AI and treat them as answering machines, oracles or all-knowing gods over fact-checking and verifying sources themselves. That cognitive dependency on AI models and agents as navigation tools will only get more profound as time progresses.

Do I really have to point out the power differential when few entities will own and control the AI gatekeepers that generate the bulk of information flows at a time when billions depend on AI for cognitive navigation? Market monopoly would instill a much more powerful epistemic monopoly: control over the conditions of knowing.

Linguist have already noticed that AI “externalized thinking so completely that it makes us all equal” in our use of language. It decreases democratic plurality in the worst way possible; by boiling our human diversity of thought and expression down into a homogeneous language slop.

Once users internalize the AI model’s outputs as truth, it will not only homogenize how we speak but how we reason and see the world. I for one would put that power under as much democratic accountability as possible.

Or much worse… but I do not want to give them any more ideas.

So let’s conclude our current state of affairs:

Welcome to the robber‑mogul playbook

All this leads me to an unpleasant but not unexpected conclusion:

Today’s AI arms race is best understood as a calculated corporate power grap: spend unprecedented sums on compute, secure strategic infrastructure along a vertical tech stack, use your investor billions to manipulate, muscle or coerce a critical mass of users and industry into rapid adoption of your stack despite productivity and expertise losses, security risks and environmental destruction, and let the narrative fog of “AGI” anxieties, geopolitics and empty promises cover up the construction of your death star rentier empire.

Unfortunately, the AI infrastructure boom for these tech moguls isn’t about reaching AGI; winning against China, or unlocking productivity utopia and abundance for humanity. As if any of these narcissistic wannabe sun-king egos would ever spare ambition for anybody but themselves. They play into these narratives with their appearances, press releases and pocketbooks to keep the media and the population occupied to look somewhere else.

But best I can tell, the current evidence suggests that the AI race is mostly about an older, more mundane, imperialistic impulse from centuries past that vast wealth inequality has always engendered: A lust for power. Dominance over the means of human affairs, from collaboration to production, enshrining their position over society for generations to come.

If the tech moguls win their gambit, if they succeed at infrastructure capture, technological lock-in and public dispossession of our shared information ecosystem, we will have ceded more than we have bargained for. Once control over knowledge creation, distribution and consumption (and with it increasingly cognitive agency) is lost for most of us, what awaits is a new dark age of monarchs, myths, manipulation and magical thinking.

A handful will own, a tiny minority will benefit, and the rest of us will fall into exploitation, exclusion or serfdom.

How to stop feudal entrenchment

What would a non‑feudal alternative require?

It is a question that many people are currently working on in the EU and elsewhere. One of them is Robin Berjon, a seasoned technologist and governance expert whose career spans web standards, open protocols, data governance in media, and next-generation infrastructure like IPFS. He works on figuring out how digital systems can be governed in the public interest. He was also very kind and charitable to sit down for a chat with me and outline solutions.

“We really have to break this myth that monopolies were made by innovation, and that they could be broken by innovation.”

- Robin Berjon

He emphasized that the first imperative is to treat digital and AI infrastructure as public-interest infrastructure rather than private consumer products. That means regulation, not innovation, is needed. Historical lessons from railroads and telecom monopolies show that when essential systems are privately captured, democratic oversight collapses. As a strong proponent of digital sovereignty, Robin was very clear about the stakes:

“We have to treat this like a war effort... what you’re fighting for is the right to set your own rules in your own country.”

- Robin Berjon

While my investigation into this topic is still very much ongoing, I already learned from him and others that there are good reasons for hope.

For example, there are already some practical solutions, often with proven efficacy at smaller scales or throughout history, already on offer.

So here is what we (and our representatives) should work on:

• Establish pre-emptive regulatory guardrails today like the EU AI Act’s transparency and systemic-risk obligations, combined with antitrust enforcement to curb exclusive cloud-model tie-ups and break vertical control by tech cartels.

• Enshrine capabilities-centric infrastructure neutrality for things like identity verification, safety or content moderation, ensuring plural applications can compete with each other without having to recreate their own capabilities to fend off bots, spam, scams or cyber attacks that any digital endeavor suffers from

• Demand open protocols, federated architectures and interoperability standards (similar to ActivityPub [Bluesky] or Beckn) to reduce dependency on single platforms, prevent lock-in and empower citizens by transferring data ownership back to users.

• Governmental and public adoption incentives of pro-democracy communication infrastructures. Habermasian democracy depends on institutionalizing norms of discourse. Adoption incentives ensure these norms are embedded in digital spaces rather than leaving them to market forces.

• Foster institutional density: AI should be regulated by a dense web of local institutions and governance models that reflect the diversity of communities and use cases. Start by building governance frameworks locally, experiment and pressure test, whatever works can then be shared or scaled horizontally to other domains.

“If you want democracy, it has to look like a hairball. Democracy is messy, but that’s what makes it resilient.”

- Robin Berjon

• Allow for epistemic pluralism by encouraging many models with diverse priors; resist interface monopolies. Information has a powerful impact on our identity and worldview. Grant individuals the right to control the mechanisms and interfaces that filter their perception

In short, we have to understand and reclaim digital infrastructure as a public good for all of society.

That is my key message for you today; and wildly at odds with current AI developments, media narratives and public attention.

Let’s change that, together.

A quick update on a COVID-19 origins-related discovery making headlines this week — and often for the wrong reasons.

The Telegraph is reporting the finding of a “new COVID virus” in Brazil. That headline is inaccurate: COVID-19 is a disease caused only by SARS-CoV-2. The new virus, BRZ batCoV, is something different — and its discovery actually reinforces what scientists already know about: That nature, not engineers, created the Furin cleavage site in SARS-CoV-2.

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Here is the quick rundown of the discovery:

An international team of scientists has discovered a new coronavirus, BRZ batCoV, in moustached bats from Brazil that carries a furin cleavage site — a key genetic feature also found in SARS-CoV-2. While the Brazilian bat virus is quite divergent from an overall sequence perspective, forming probably its own subgenus next to the Sarbeco- and Merbecoviruses, its amino acid sequence and position at the critical S1/S2 junction, forms a functional cleavage site remarkably reminiscent to the one observed in SARS-CoV-2.

Of note, the spike protein of this novel bat coronavirus possesses a functional furin cleavage site at the S1/S2 junction with a unique amino acid sequence motif (RDAR) that differs from that found in SARS-CoV-2 (RRAR) by only one amino acid. - Takada K. et al., bioRxiv, 2025

This finding is significant, but not surprising.

As I wrote previously, these cleavage sites are not unique by any means; in fact, they independently develop all the time in the wider coronavirus family. The wider CoV family tree is sprinkled with FCS sites at the S1/S2 position.

This is not surprising either, because FCS are very short sequences (4 amino acids) and these polybasic cleavage motifs will happen over and over just by chance through recombinations, insertions, or mutations. Most FCS motifs are likely acquired de novo and just don’t stick around if selection pressures do not favor them.

Furthermore, there is good evidence that the S1/S2 boundary region of the genome is a highly variable region in all CoVs and more permissive to genetic alterations than the wider genome through point mutations, insertion, and recombination mechanisms.

The authors find this as well by investigating the protein structure in the S1/S2 region of the BRZ batCoV

"…our results suggest that FCS acquisition is impacted by protein-level constraints, with the S1/S2 junction representing a structurally permissive “hotspot” for stable incorporation of cleavage motifs. - Takada K. et al., bioRxiv, 2025

Again, this just adds to the picture we already had. To support this notion of a ‘higher dynamic’ at the S1/S2 location, another genomic study of SARSr-CoVs in European bats found some indications that FCS at this location might pop in and out of existence in Sarbecoviruses at very low frequencies in a population.

Overall, this discovery adds to our already exisiting evidence basis that nature is perfectly capable of creating a furin cleavage site, no engineer needed.

And if you need any more convincing that the FCS we observe in SARS-CoV-2 is natural and was not engineered, I’ve written a very long article about it, but just look at that hot mess below:

Alright, so science does what science does, continuously adding new nuggets of evidence to an already existing body of knowledge.

The day closes with another L for the lab leakers, as is typical when it comes to scientific support for their fantasy.

Anyways, what else is new?

Rand Paul keeps digging a rabbit hole to hide in:

Sometimes, it is hard to convey how ignorant, dishonest and malicious political actors have been on this topic.

Rand Paul treats virology papers the way flat-earthers treat NASA photos: highlights the wrong part, zooms in 400%, and calls it a smoking gun.

That will not change anytime soon, but for anybody who wants to understand why this fabricated origin controversy has reached the highest halls of power, you know I got you covered:

Alright, that is it for my origins news dispatch.

Stay safe, stay smart, stay connected.

Manufactured controversies for the classroom?

A recent opinion article in statnews by Michaela Kerrissey and Richard J. Tofel has caught my eye on Bluesky.

In it, the authors argued that the origin dispute should serve as a case study in how public-health agencies, science communicators, and media have supposedly struggled under conditions of ambiguity; how they treated and still treat the origin as a taboo topic, and that:

Initial concerns about the possibility of lab involvement gave way to the forging of an apparent early scientific consensus on zoonotic spread. Countering that consensus became very costly; at least one scientist who did so received enough threats to consider changing her name.

This consensus, however, has now at least partially unraveled in the face of multiple investigations.

If you are not so familiar with what they are talking about; these are basically regurgitating three totemic falsehoods highlighting how eagerly they gulped down the lab leak koolaid.

• nobody “forged” an early consensus; unless the authors believe in Anthony Fauci teleconference / proximal origins conspiracy myths

• The authors reference Alina Chan, who was rewarded immediately, never changed her name, never faced any real cost but rather became a media darling by playing the contrarian martyrer. In contrast, virologists that actually worked on the origin question faced incredibly dire costs, from defunding to death threats, from smear campaigns to security incidents at their homes

• The scientific consensus has solidified over the years, and the investigations the authors link to are unscientific political fictions from GOP congressional operatives

Funnily, the authors claimed that they hold no position on the origin questions but somehow align 100% with lab leak lore.

Within science, the consensus remains that zoonotic spillover is overwhelmingly supported by the evidence. The many mutually-contradictory lab leak speculations lack comparable empirical grounding and are often contradicted by hard evidence.

Anyways, that does not stop the authors from explaining their alternative history of events as a supposed failure of public health scientists to grapple with uncertainty.

The lessons here involve both management and communications […]

Beyond this, we think students (and maybe all of us) benefit from exposure to the arguments of those who believe passionately that they know something, even as passionate advocates reach very different, often irreconcilable conclusions — and even if they are partisan.

Apparently, not the strength of evidence, but the strength of belief behind a position should guide our serious considerations and public health communication.

With this simple appeal to “teach the controversy”, the authors fall back on a tried-and-tested tactic from the past. “Teaching the controversy” was a manipulation campaign by creationists from the conservative Discovery institute to subvert evolutionary theory in schools. It manufactured a controversy surrounding evolutionary theory and claimed that fairness requires educating students with a “critical analysis of evolution”, basically that creationism should be taught side-by-side.

Maybe the authors should also have learned from the past they are trying to recreate. One should not respond to manufactured controversies by taking them serious, but contextualizing and questioning them:

The scientific community and science education organizations have replied that there is no scientific controversy regarding the validity of the theory of evolution and that the controversy exists solely in religion and politics.

-American Association for the Advancement of Science. February 16, 2006

I would then still argue that a more robust approach would be to teach why scientific controversies emerge — how media incentives, partisanship, and online ecosystems amplify extremists views — rather than treating both hypotheses as symmetrical. This preserves the authors’ stated goal (teaching epistemic humility) without furthering unsupported narratives.

Blaming the scapegoats

Unfortunately, when continuing to read their opinion piece, the intentions and worldview of the authors become hard to explain cheritably.

We need to come to grips with the root causes of this loss and avoid the easy out of apportioning responsibility to bad actors only. Loss of trust also comes to those that are well intentioned but do not foresee — and do not return to address — the eventual consequences of their early actions, from either a management or communications perspective.

What the authors really do here is to perpetuate not only a manufactured controversy, but something more sinister; they validate the anti-science narrative that the scientists who have been turned to scapegoats by politics and bad actors are to blame for their own circumstances:

I have lost count on how many supposedly “polite society” pundits and outlets have moved in the last years towards blaming scientists for the loss of trust in science, if not for the hardships and trauma of the pandemic itself.

And while the pandemic origin controversy often seems far behind, those who profited the most from it are still working every day to entrench their positions and excert influence over public understanding. All while ordinary science and scientists lose their independence, funding, freedom of inquiry and societal trust and goodwill.

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So what can we do about it?

This has been a question I find myself increasingly occupied with. The participatory nature of online discourse makes it clear that influence flows through networks, that communities often decide what is heard, seen, believed. Silence is surrender, and many scientists are waking up to this reality:

To defend themselves, they [scientists] had no choice but to recognize the political battlefield they were placed on.

And you are right—scientists are now more outspoken. They’ve realized that silence isn’t neutrality; it’s surrender. If they don’t defend evidence-based inquiry, no one else will. Scientists are a minority in every country. Journalists are weakened by collapsing media ecosystems. If both remain silent, truth itself is left undefended.

Of course, scientists must also reflect on their role. For too long, many lived in ivory towers, buffered by public trust and generous funding. The pandemic fractured that trust. Politicians, charlatans, and business interests exploited the gap between science and society, deepening public mistrust. Bridging that gap now requires effort on both sides: scientists must engage more directly with the public, and citizens must reclaim science as a defense against manipulation. - Philipp Markolin, www.wsws.org

So while I spend most of my time these days researching and interviewing experts from many different fields to map out a solution roadmap, I will still try to be present and participate in correcting pandemic origin discourse.

Because althought it is exhausting, it continues to be important.

Today more than ever, I believe we need to have an honest account of what happened in this origin controversy, not regurgitate retconned bullshit, to adequately address what happened to us as a society.

If you are new, unfamiliar or have forgotten a lot about the details surrounding the lab leak narratives, you are not alone. Matt and Chris from the Decoding the Gurus pod created a fantastic primer on the topic while talking about my book:

If you have any questions, feel free to write in the comments or reach out; and I will try to answer them best I can.

Stay safe, stay smart, stay connected!