VD: This is not my response to the two Eco-Avenger videos, this is the portion of the transcript of Will Duffy’s appearance last night on Ms Matthew’s channel when they discussed Probability Zero.
On Reading the Book and Watching the Response
Will: Here are my receipts. I purchased Probability Zero on July 26th and I didn’t read it right away. Then I purchased Hardcoded on August 9th. Then I purchased The Frozen Gene on August 10th. And then I emailed Vox for the first time on August 22nd. So these are the receipts. This is the exact timeline. This was nothing I had in my back pocket. This wasn’t the long game.
As to how I knew so many details about Vox Day, including details about his son—it’s quite simple. I read his books. Everything in my presentation was from his books. Everything.
It will come as a shock to most of you that Erica, Dr. Zack Hancock, Dr. Dan, Dr. Maddie Frank, and Grayson Hawk did not read the Probability Zero book that my presentation was based on. Details forthcoming. I had a lot of homework this go-round. I had to rewatch the last presentation, watch Erica’s rebuttal video to Vox Day, and then watch “Six Scientists Roast Vox Day” for over four hours. These videos were 12 hours, 42 minutes, and 25 seconds long total. My game plan: Step one, rewatch Human Evolution 2 live stream. Step two, meet with Mike Griffiths. Step three, watch Erica’s response video to Vox Day. Step four, meet with Mike Griffiths. Step five, watch “Six Scientists Roast Vox Day.”
For those who don’t know or don’t remember, Mike Griffiths is a mathematician—he’s the head of maths at a private institution in England. He’s a huge fan of Erica, and he’s an atheist.
I want to highlight one comment from Dr. Dan over at Creation Myths: “Can we also just marvel at the fact that Will went to a GD billiards player to learn popgen instead of, I don’t know, a population geneticist?” I’ll let the comment speak for itself.
On the Fossil Record
Will: Erica covered a lot in the last session. She covered fossils, more fossils, and finally more fossils. The more Erica teaches me about the fossil record and the more I learn about it, the more I struggle to make sense of young earth creationism.
I’m not going to elaborate on this now, but I will in January during our final discussion.
Predictions and Tiktaalik
Will: Erica, you said predictions are the gold standard of science. I’ve been thinking about that. Since our series started, I’ve tried to watch every evolution debate on the Modern Day Debate YouTube channel, and the number one evolution prediction that comes up almost every time is Tiktaalik. I’ve heard it so much that I never actually looked into the prediction and just accepted the claim that it was predicted. In the past couple weeks, I decided to look into it and I can’t find any evidence that it was predicted. I’m not making a positive claim that it wasn’t predicted—I’m just saying I can’t find any evidence that it was. So I want to know: in what way was Tiktaalik predicted?
Molecular Clock Discrepancies
Will: Erica, you said that the molecular clock matches with the fossil emergence time. Unfortunately, I have not had time to look into this, but I have been contacted by multiple people who said there are significant discrepancies with reconciling the fossil record with the molecular clock.
I have been sent multiple scientific papers that I haven’t read, and I’ll show them:
- “The Origin of Animals: Can Molecular Clocks and the Fossil Record Be Reconciled?”
- “Uncertainty in the Timing of Origin of Animals and the Limits of Precision in Molecular Timescales”
- “Survival and Selection Biases in Early Animal Evolution and a Source of Systematic Overestimation in Molecular Clocks”
- “Re-evaluating Molecular Clock Maximum Age Calibrations Revives Pre-Ediacaran Divergence Estimates for Animals”
Teleology
Will: When this part of the presentation came up, I mentioned to Erica that I thought what she was saying went against what she said about teleology originally—that we can’t tell if something’s designed.
Here’s what was said in the last presentation: “There is actually a way to use fracture patterns to tell whether or not a tool was made by a hominin or not. You can actually roll a bunch of rocks down a hill and see how they break. So there’s a way to differentiate between something that was designed by hands and something that nature did in the case of stone tools.”
But in our first session, she said: “The problem with teleology is exactly what you see on the screen. We can’t differentiate between the designed and the natural.” And a couple minutes later: “It’s not that teleology is impossible. It’s that teleology is non-scientific because it can’t actually be tested.”
I do struggle to understand that when combined with saying there is a test we can do. I think it’s possible teleology is kind of sneaking back in the door here.
The Selection Coefficient / Selective Turnover Coefficient Error
Will: When Erica and Zach were going over my slide, Erica said that “d” in the formula is “Day’s selection coefficient.” And then she said, “What’s crazy is that Day’s selection coefficient isn’t actually a selection coefficient.”
This is unfortunate. If you go back and look at my slide, it’s a selective turnover coefficient. It is not a selection coefficient. So when you said Day’s selective turnover coefficient cannot do what a selection coefficient does, that was not valid because it’s not a selection coefficient.
Zach was presenting and said, “So Vox has this other term d, but we don’t know what it means.” He admitted that he doesn’t know what it means, which makes sense. Unfortunately, that entire section of the video was a category error, and I didn’t find one person in the thousands of comments who caught this—I could be wrong, but I think it’s because people did not read Probability Zero.
After reading the book, you walk away with a really good understanding of what a selection coefficient is in population genetics, and you would never confuse it with Day’s selective turnover coefficient d. In population genetics, a selection coefficient uses the symbol S, which I actually used in the formula. Selection coefficients are S. The selective turnover coefficient is d.
Who Actually Read the Book
Will: People ask, “How do you know so much about Vox?” I read his books. In the beginning of the second video, Erica said, “So we read his book. Now when I say ‘we,’ I mean me, Zach, and four of our other credentialed friends.” That was a collective “we,” and I think people might have missed what it actually meant. It didn’t mean all of them read the book.
- Zach said: “It’s like trying to explain to a 5-year-old why the sky is blue. It’s just a waste of time and I’m not going to read your book. I’m not going to waste my time with it. I got science to do.” So Zach didn’t read the book.
- Maddie said: “I read 40% of a book about this.” So she read less than half.
- Erica said: “I read about 60 to 70% of the book in its entirety, whereas I skimmed the rest.”
Then something else happened. When Erica’s first video rebuttal to Vox Day came out, the numbers were not the same numbers that I originally presented. They were way off. The quotes and page numbers she was giving were not correct in my book. Come to find out, none of them purchased Probability Zero. They obtained an EPUB version somewhere and shared it with everyone else. It was the wrong version. The only version you can buy—which is what I bought, for $4.99 on Amazon—is the second edition, which had corrections, updates, and the latest science. The EPUB version they all used was the original edition.
Vox Day’s Prediction
Will: Vox Day made a prediction on his blog on September 26th, the day after our last live session: “My response is fairly simple and straightforward. I’ll be happy to talk to her or to whomever and explain these things. I do not expect anyone to actually (a) talk to me or (b) read the book. I don’t know what it is about biologists, population geneticists, and other science enthusiasts, but they always seem to imagine they can effectively critique anything without bothering to actually learn anything about it.”
I was really hoping this prediction would not come true.
Wright-Fisher, Moran, and Day’s Selective Turnover Coefficient
Will: Zach said: “There are two classic models—the Wright-Fisher model and the Moran model. In its classic sense, the Wright-Fisher model does not have overlapping generations. But you can equate the two by setting the population size (the N value) in the Wright-Fisher model to an effective population size and you just scale that effective population size by the slowdown of drift due to overlapping generations. So even the Wright-Fisher model can account for overlapping generations.”
Zach is correct here. But since he didn’t read Probability Zero and doesn’t understand Day’s selective turnover coefficient d, he doesn’t know why it’s still necessary and why it captures something that N-sub-e misses.
Both models—Wright-Fisher and Moran—are answering this question: How fast does genetic drift move neutral alleles through the population?
Day’s selective turnover coefficient d is designed to answer an entirely different question: How fast does the entire gene pool turn over?
The d formula involves variables that simply have not been accounted for in standard population genetic models.
Now, if anyone out there wants to grab my attention and immediately build rapport with me, simply acknowledge and tip your hat to Vox Day for his selective turnover coefficient. It has essentially nothing to do with his Mittens argument that evolution by natural selection is mathematically impossible. So conceding this one should be relatively harmless.
Zach’s Calculation Errors
Will: Zach said, “This is going to be 76.8 multiplied by 252,000, and that’s how many mutations you’re actually going to have in that time period.” This was a mistake. And remember what Erica said—trusted creators are people who can own their mistakes. Zach is a trusted creator. He owned his mistake, and it’s in the video. He corrected himself: “Importantly, we can’t use 6.4—this is the diploid genome size—for the fixation rate, because you fix on a haploid genome. So it should be 3.2.”
This made me happy. But then a few seconds later he said, “I want to quickly clarify that value, but I also want to say that we can still use this value in the following derivations.” He referenced Perubski et al. 2025, saying they estimate an average of 152 de novo mutations every single generation, and dividing that in half for the haploid genome size gives 76—meaning the original number can still be used.
But this is a pretty significant error. The Perubski et al. number includes large structural variants, insertions, deletions, and duplications—not just single nucleotide polymorphisms (SNPs). Zach’s entire calculation on the whiteboard is explicitly about single nucleotide differences using a single nucleotide mutation rate. You can’t validate a SNP-only calculation with a number that includes large structural variation.
Once again, I could not find anyone in the thousands of comments who caught this. But you know who did catch it? Mike Griffiths. The billiards player.
The 38 Million Number
Will: Zach says we can fix 38 million differences between humans and chimps. That’s incorrect for three reasons.
First, the calculation is being run on the diploid genome size (76.8) instead of the haploid genome (38.4).
Second, minor: he’s using 252,000 generations instead of the d-coded size of 201,600.
Most importantly: neutral theory applies to the entire genome. Zach is using circular reasoning in assuming the neutral prediction of 35 million differences all fall perfectly into the divergent sites. In reality, the divergent sites are only 1.09% of the genome. So statistically, only 1.09% of the neutral substitutions would end up in the divergent zone. The proper formula would be: 15-some-odd-million × 35 million ÷ 3.2 billion (the size of the genome). So Zach’s original 38 million number is in actuality just 169,344.
Rate vs. Latency: The Highway Analogy
Will: Zach said: “Hopefully you can see a very glaring problem with this math. One is that it assumes that each mutation has to both arise and go to fixation before the next mutation can occur.”
Zach is incorrect here. Part of me has sympathy for him as he’s trying to critique a book he hasn’t read. But the other part of me struggles to have sympathy for the same reason—he’s trying to critique a book he hasn’t read.
When you calculate a rate such as an observed fixation rate, you are dividing the total number of generations observed by the total number of fixations over that period. This tells you how many generations elapsed per fixation on average, regardless of whether those fixations occurred sequentially or overlapped.
Vox Day’s calculation is a rate calculation. Zach thinks it is a latency calculation.
I can help everyone understand with a simple highway analogy. Imagine you were counting how many cars pass a red line in one hour, and you count 360 cars. How would you calculate the average rate? The numerator is the time (3,600 seconds), the denominator is the number of cars (360). So 3,600 ÷ 360 = 10 seconds per car. This is the exact same method Vox Day uses to calculate the average observed fixation rate. If you see this formula and say, “Well, that formula means the cars can only travel one at a time, like through a tunnel,” that is absolutely incorrect.
Vox Day’s calculation is not a latency calculation and is not assuming one fixation happens before another one starts. This was explicitly covered and anticipated in Probability Zero.
I’m not hammering on Zach here. I believe he is a trusted creator and he’s going to own these mistakes. We’re all just trying to get to the truth.
Mittens Is Not the Waiting Time Problem
Will: Dr. Dan says, “Like the waiting time problem, which—even though Vox Day has never heard of it—that’s the argument he’s making.” No. Mittens is not the waiting time problem. The waiting time problem refers to the significant amount of time required for beneficial genetic mutations to occur in a population. The Mittens argument isn’t concerned with mutation rates at all. It is an empirical audit of observable fixations. Mittens would be better referred to as the fixation problem.
The Bacteria Issue
Will: Dr. Maddie said the idea of applying the fixation rate from bacteria to human populations doesn’t work when you just take the average of the fixations out of the Lenski experiment and apply that as a fixation rate to the human population assuming all the mutations are happening in series.
No, it doesn’t assume mutations are happening in series. But let’s talk about the bacteria issue. I don’t know anyone who argues that humans fixate mutations faster than bacteria in terms of generations per fixation. I think it’s possible the audience walked away from that video thinking that is what was being argued. So I’m hoping Erica and the others can clarify whether or not they actually believe humans fixate mutations faster than bacteria.
Zach said something good: “The issue with using even conceptually the Lenski long-term evolution experiment for a fixation rate is that the Lenski long-term experiment begins with a bacterial population that is clonal and has no diversity.” Zach makes a really valid point here. This was also caught by Mike Griffiths, who brought it to my attention before this video was released.
Here’s Vox Day’s response, which I’m not claiming to understand:
“The polymorphism objection sounds legitimate until you think about what standing variation is. It’s not a warehouse of pre-adapted beneficial alleles waiting for their moment. It’s mostly neutral variation, which is why it’s still segregating. If those variants were beneficial, they’d have already swept to fixation. If they were deleterious, purifying selection would have removed them. What mutation-drift equilibrium gives you is a population full of genetic noise at low frequencies, not a head start on adaptation.”
I don’t understand this enough yet to know who’s right. But the main argument with the bacteria thing seems to be that Vox shouldn’t apply bacterial fixation rates to humans because bacteria are clonal and slow.
Dr. Michael Lynch—who I’m told is one of the most respected population geneticists in the field—has stated that bacteria are actually faster and more efficient at molecular adaptation than eukaryotes because of their population size advantage. He says: “Prokaryotes appear to be much more efficient than eukaryotes at promoting simple to moderately complex molecular adaptations.”
Mike Griffiths as Intermediary
Will: Mike Griffiths watched Erica and Zach’s presentation. He also bought Probability Zero. He watched Erica and Zach’s presentation twice and has a list of about a half-dozen questions and issues. I introduced Mike to Zach via email and Mike shared his list with Zach. Zach has yet to respond.
On the Probability Zero side, Mike has started reading Probability Zero and Vox Day’s scientific papers. He has a list of questions and issues for Vox as well. I asked Vox if he would respond to Mike, and he agreed. The three of us did a Zoom together last week, and after the Zoom, Mike sent his list to Vox.
I told Erica already that I do not rush things like this. I spent a very significant amount of time not only learning Vox Day’s arguments in Probability Zero, but also learning as much as I could about the math behind population genetics. I have since spent a good deal of time reviewing the responses from Erica, Zach, Dan, Maddie, and Grayson. There are significant errors that I trust will be owned and corrected. As such, the verdict is still out.
I will tell everyone I’m relying heavily on Mike Griffiths as well. I’m honestly giddy to get to be a bystander on his conversations with both Zach Hancock and Vox Day. Mike has legitimate concerns for both of them, and I’m extremely curious how they will both respond.
Will’s Conclusion
Will: I want to point out to everyone what stood out to me most the last few weeks after I mentioned Vox Day and Probability Zero.
The response I received was the exact opposite of what everyone has been telling me to do from the very beginning:
- I’ve been told to focus on the data and science and not the person. Yet the vast majority of responses and comments I get are focused on Vox Day as a person and not the data and the science.
- I’ve been told that Darwin’s racism has no relevance to evolution and that Fisher—of the Wright-Fisher model—being a eugenicist doesn’t make his math wrong. But that’s all I’m hearing about Vox Day.
- I’ve been told to focus on understanding new things instead of just trying to refute them. But I see very few people trying to actually understand his arguments—just trying to refute them.
- I’ve been told not to run to creationists hoping they can refute what Erica teaches me and to study what I’m taught. But all I’ve seen is everyone say, “I’m just gonna have Erica and Zach and whoever else refute this instead of looking into it.”
I think it’s important for what it’s worth to know what I’m experiencing and what I’m seeing from my perspective.
Erica’s Response
Erica: I have a lot of thoughts—like three pages of thoughts. I’m going to work through some of them, but I’m not going to get to everything because you have a hard stop at 7:00 and I want to get to the actual presentation and super chats.
I can understand your perspective on being frustrated with people’s response to Vox. I said this to you via email and I’ve voiced this to other people as well. I think you have to put yourself in other people’s shoes a little bit too, though. The reason Zach and I covered what we covered in that initial video is because that’s what you shared—that was in your PowerPoint. Our first video was obviously just in response to the PowerPoint we got from you. We didn’t have access to the book at that point. I hadn’t read the book at that time either, even the scant portion I did read, although I did read Mittens 3.0, which is available online for free and is supposed to be—according to Vox—the most up-to-date version of the argument. That’s also why in the second video we went over Mittens 3.0 in addition to the first version of Probability Zero, because that was according to him the strongest version of the argument.
I can understand your frustration, but I find it difficult to set aside a lot of his other beliefs in the same way one would for someone like Darwin or Fisher. In Darwin and Fisher’s case—and I said this to you via email—Fischer was a eugenicist and Darwin was racist. That’s factually true. Darwin was an abolitionist as well—he was progressive for his time—but that doesn’t change the fact that he lived within the context he lived in. But the work they did in science did stand on its own. Their work has stood the test of time, and Fisher and Darwin’s ideas are still being used today to make accurate predictions. I’ve not seen the same with Vox’s math.
This is something that people sympathetic to Vox have not appreciated, and I’ve yet to see him comment on it. The math that underpins standard population genetics has been used to accurately model real populations now. And there are like a billion of them, which is why I showed a slideshow of two dozen or however many it was. Point blank, full stop: if Vox is correct and traditional population genetics is incorrect, those papers shouldn’t exist. They shouldn’t be able to accurately model or even predict changes in real world populations.
I do still maintain that this is a waiting time problem. The waiting time problem in traditional creationist circles is a fixation problem. Mutation rate and fixation rate are used interchangeably a lot, inappropriately, as you would now know because you’ve read up on a lot of population genetics. But because they’re used interchangeably, it makes it seem like the waiting time problem is something distinct from this fixation problem. It’s not. You can go back to Doug Axe’s original paper in the early 2000s and see exactly this, which is why we’ve said this is a waiting time problem.
I’ll say too: the idea that he’s using the Lenski long-term evolution bacteria—which, as you accurately pointed out, are clonal and thus inappropriate for that reason—I don’t think anybody’s saying that bacteria quite literally fixate faster than humans do. That’s not my understanding. The problem is that in the Lenski experiment in particular, by their nature of beginning clonally and by their nature of not recombining, these two things are not analogous. It’s an apples-to-oranges comparison.
The numbers exist out there for eukaryotes—fruit flies, rats, humans. We have pedigree studies on real-world human populations: a grandparent, a parent, and their kid. And you can use that to model these populations into the past. They don’t match Vox’s math. And they don’t behave like bacteria.
To me, what rings out most severely is that he must rectify this math with the entire scientific community, and he won’t. I find that incredibly frustrating because he puts out the books and says, “This stands on its own,” but it’s never applied to any real-world populations.
I have to ask you this. I don’t understand how you could give him the benefit of the doubt for the other stuff. I can sit here and say I disavow Darwin for the shitty stuff he said. I disavow Fisher for the shitty stuff he said. I like their math, but I can recognize that in these areas, they’re bad people for holding these perspectives. And you’ve already said—just to be clear for everyone—Will said he disavows white supremacy and doesn’t think women should lose the right to vote and doesn’t think marital rape laws should be revoked. He said that up top. But I still think you’re being a little bit defensive of Vox, and I don’t understand how you could do that after watching the video that had a lot of this stuff in his own words. That’s confusing to me. I want to give you the benefit of the doubt here because I think this series is a good thing.
DISCUSS ON SG