Prof. Eleanor Hart: Yang, as a software engineer, you spend your days writing and debugging code. But have you ever considered the oldest, most complex, and bug-ridden codebase in existence? It's three billion letters long, it's running inside every one of us right now, and it's called the human genome.

hl01 yang: That's a fantastic way to put it. I've never thought of it that way, but it makes perfect sense. A massive, legacy codebase passed down for millions of years, with every developer just adding their own little patches. I can only imagine the amount of technical debt.

Prof. Eleanor Hart: Exactly! And that's why Adam Rutherford's book, "A Brief History of Everyone Who Ever Lived," is so thrilling. It's our guide to reading this incredible source code, to understanding its history and what it says about us. Today we'll dive deep into this from two perspectives. First, we'll explore the shocking discoveries in our 'legacy code'—the traces of Neanderthals and other ancient humans in our DNA.

hl01 yang: So, like finding code from a completely different, deprecated library mixed into our own.

Prof. Eleanor Hart: Precisely. Then, we'll use genetics to debug one of society's most persistent myths: the biological basis of race. It's a journey into who we are, written in the language of A, T, C, and G.

Prof. Eleanor Hart: So let's start with that legacy code. We have this popular image of human evolution, you know, the one that goes from ape to a slouched-over figure to an upright modern human. It looks like a clean, linear upgrade, like going from version 1.0 to 4.0.

hl01 yang: Right, a clear progression. Each version is a distinct improvement on the last.

Prof. Eleanor Hart: But the genetic data tells a much messier, and frankly, more interesting story. The book puts it bluntly: for most of our history, humans were "horny and mobile." And this led to some very surprising code merges. For decades, scientists debated whether we had interbred with Neanderthals. The challenge was getting a clean read of their DNA. Imagine trying to restore a file from a hard drive that's been buried in the mud for 40,000 years. That’s what the scientist Svante Pääbo was up against.

hl01 yang: The data degradation must have been immense. Contamination from bacteria, from the researchers themselves... it sounds like an impossible signal-to-noise problem.

Prof. Eleanor Hart: It was. But in 2010, Pääbo’s team succeeded. They published the first draft of the Neanderthal genome. And the bombshell was this: if your ancestry is from outside of Africa, you have Neanderthal DNA. The author, Adam Rutherford, found he has 2.7% Neanderthal DNA. It's a direct genetic echo of an encounter between two different types of human tens of thousands of years ago.

hl01 yang: That's incredible. So it's not just a theory; it's right there in our own code. I have to ask, does this Neanderthal 'code' actually anything in us today? Is it active, or is it just commented-out legacy script that doesn't compile anymore?

Prof. Eleanor Hart: A perfect question for an engineer! And the answer is both. Some of that DNA is active and seems to be linked to our immune systems, perhaps giving our ancestors an advantage in new environments. But other parts are being actively 'purged' by natural selection over generations, suggesting they might be like inefficient code, causing subtle performance drags or 'bugs' that our systems are slowly trying to refactor.

hl01 yang: So our genome is actively debugging itself. That's fascinating.

Prof. Eleanor Hart: It gets even stranger. The technology that allowed us to read Neanderthal DNA opened the door to analyzing other fragments. In a cave in Siberia called Denisova, archaeologists found a tiny piece of a child's finger bone and a large molar. They were dated to around 40,000 years ago. The assumption was they belonged to a Neanderthal or an early modern human.

hl01 yang: Okay, so they run the DNA sequence...

Prof. Eleanor Hart: They run the sequence. And it's neither. It was something entirely new, a previously unknown branch of the human family tree. They're called the Denisovans. We know almost nothing about what they looked like. They are, as the book says, a 'ghost population,' a species known to science almost entirely through a few lines of genetic code recovered from a fragment of bone.

hl01 yang: Wow. So from a data perspective, they had this tiny, corrupted dataset and from it, inferred the existence of an entire new class of human. That's the ultimate in data forensics. It’s like reverse-engineering a whole operating system from a single corrupted file.

Prof. Eleanor Hart: And of course, we bred with them too. People in Melanesia today can have up to 5% Denisovan DNA. It shows our family tree isn't a tree at all; it's more like a tangled, thorny bush. Our source code is a patchwork.

Prof. Eleanor Hart: And this idea of our code being a messy, intermingled tapestry leads us directly to the second, and perhaps most powerful, idea in the book. If we're all such a mix, what does that mean for the way we categorize people? Specifically, what does genetics say about 'race'?

hl01 yang: This is a huge topic. Our society is so structured around these categories. I'm curious what the raw data actually says.

Prof. Eleanor Hart: Well, the book argues that from a biological standpoint, race is meaningless. And it presents the data to prove it. The key evidence comes from a 1972 study by a geneticist named Richard Lewontin. He looked at the known genetic variation in humans at the time. What he found turned the whole concept of race on its head.

hl01 yang: Okay, I'm ready for the numbers.

Prof. Eleanor Hart: Lewontin discovered that about 85% of all human genetic variation exists any single local population. For example, if you take the population of Italy, you'll find 85% of all the genetic diversity present in the entire human species right there.

hl01 yang: Wait, let me process that. So the vast majority of genetic difference is not groups, but them?

Prof. Eleanor Hart: Exactly. Of the remaining 15% of variation, only about 8% is what accounts for the average differences, say, a person from Sweden and a person from Ghana. The differences we see, the ones our brains are so good at latching onto—skin color, hair texture, eye shape—are evolutionarily superficial. They're the 'UI,' the user interface. But the underlying architecture is astonishingly similar.

hl01 yang: That 85% number is a system-breaker. In software, if you told me that 85% of the code variation exists within a single module rather than between different programs, I'd conclude that the programs share the exact same fundamental architecture, just with different style sheets or 'skins.' It completely reframes the problem.

Prof. Eleanor Hart: That's the perfect analogy. And the book gives a great example with a gene called EDAR. A specific variant of this gene is very common in people of East Asian and Native American descent and is associated with traits like thicker hair, a certain tooth shape, and more sweat glands. But genetic analysis shows this mutation is recent, only about 30,000 years old, and likely arose in central China. It's a 'feature update' that spread through a population. It's not some ancient, fundamental division that defines a 'race.'

hl01 yang: So what we perceive as deep, defining racial characteristics are more like recent, regional software patches. It makes you think about how much of our social 'operating system' is built on a fundamentally flawed assumption about the 'hardware.' We've built entire systems of inequality based on misinterpreting the UI.

Prof. Eleanor Hart: And that's the beautiful, and tragic, irony. The science of genetics was co-founded by Francis Galton, who also founded eugenics. He hoped this new science would prove his prejudices about racial hierarchies. Instead, the data his field eventually produced completely dismantled the very foundation of his beliefs. The data is king.

Prof. Eleanor Hart: So, when we step back, our genetic code tells this incredible dual story. On one hand, it reveals a deep, messy history of surprising interconnectedness, of ancient code merges with Neanderthals and Denisovans that we're only just beginning to understand.

hl01 yang: A history that proves we're all a bit of a mutt, genetically speaking.

Prof. Eleanor Hart: Exactly. And on the other hand, that same data completely debunks the idea of deep, biological racial divides. It shows us that the categories we've created are social constructs, not genetic realities.

hl01 yang: I think for me, as someone who builds things, it's a profound lesson in humility. You might think you're designing a clean, elegant system, but you always inherit a messy, complex history. And the most important thing is to look at the underlying data, the source code, not just the superficial interface. The data tells us we're one beautifully complex, buggy, and interconnected human program.

Prof. Eleanor Hart: Beautifully put. And that leaves us with one final, thought-provoking question. We are now developing technologies like CRISPR that can not only read, but our own genetic code. So, as we become the developers of our own evolution, the question isn't just we, but we? And what does this deep, messy, interconnected history tell us about the responsibility that comes with that power?

hl01 yang: That's the question that's going to define the next century. We have to make sure we've learned the lessons from our past before we start writing our future.

Prof. Eleanor Hart: A perfect place to end. Yang, thank you for helping us decode this incredible story.

hl01 yang: It was my pleasure. It's given me a whole new way to think about code.