Intelligent Design
Life Sciences
The Paradox of Biological Reproduction

In Plato’s Revenge: The New Science of the Immaterial Genome, David Klinghoffer quotes mathematical biologist Richard Sternberg explaining that the Levinthal paradox is that the “information output in a developed animal form exceeds the information present in the fertilized egg. Information transmission from egg to fully developed animal requires an external source of information to correct errors and an external channel of transmission.”
The back cover of the book states,
Recent findings reveal that genetic and even epigenetic sources alone cannot account for the rich dynamism of life — not even close. Some other informational source is required. The idea was anticipated 2,400 years ago in Plato’s Timaeus and periodically revisited in the ensuing centuries. Sidelined by scientific materialism, it is now reasserting itself on the strength of cutting-edge molecular biology, higher mathematics, and common-sense reasoning.
Well, I cannot contribute to the supporting cutting-edge molecular biology and although I am a mathematician I haven’t yet seen the higher mathematics, but I can offer some commonsense reasoning that helps understand why reproduction poses a paradox that does not seem to be solvable by materialistic science.
Self-Replicating Machines
My 2023 BioCosmos article, “Human-Engineered Self-Replicating Machines,” included the following paragraphs:
With all our advanced technology, we are not close to producing human-engineered self-replicating machines. This is significant because it is widely believed that the first self-replicators on Earth must have arisen through chance chemical processes — it being impossible to appeal to natural selection of replication errors before anything could self-replicate.
To better appreciate the enormous difficulties in designing such machines, and thus the difficulties in understanding how the first living things arose on Earth, let’s think about what would be required to build, say, a self-replicating “model T” car.
We know how to build a simple model T. Now let’s build a factory inside this car, so that it can produce model T cars automatically, and call the new car, with the model T factory inside, a “model U.” A car with an entire automobile factory inside, which never requires any human intervention, is far beyond our current technology, but it doesn’t seem impossible that future generations might be able to build a model U.
Of course, the model U cars are not self-replicators, because they can only construct simple model T’s. So let’s add more technology to this car so that it can build model U’s, that is, model T’s with car-building factories inside. This new “model V” car, with a fully automated factory inside capable of producing model U’s (which are themselves far beyond our current technology) would be unthinkably complex. But is this new model V now a self-replicator? No, because it only builds the much simpler model U. The model V species will become extinct after two generations, because their children will be model U’s, and their grandchildren will be infertile model T’s.
So back to work, and each time we add technology to this car, to move it closer to the goal of reproduction, we only move the goalposts, because now we have a more complicated car to reproduce. It seems that the new models would grow exponentially in complexity. And even if we were able to engineer self-replicating cars, it is hard to imagine that without any human maintenance these cars could keep reproducing themselves for more than a few generations before errors accumulate to the point that all replication halts.
And here we have ignored the very difficult question of where these cars get the raw materials they need to supply their factories.
Some will object here that the first living things may have been much simpler than self-replicating cars. It is widely believed that you only need to explain how very simple self-replicators could have arisen through chance chemical processes, because then natural selection of the resulting duplication errors could take over and explain how self-replicators far more complex than cars could have arisen. But even if we could explain the appearance of simple self-replicators, imagining trying to design self-replicating cars may help us appreciate the enormity of the difficulties facing any scientific explanation (let alone one which relies on replication errors) for the unimaginably complex self-replicators that we see everywhere in the living world.
“So What Is the Difference?”
The first reviewer of this article wrote, “It’s important to explain whether the infinite regress problem applies in the case of biology, and if it does, how life overcomes the problem.” The second reviewer similarly wrote, “As stated, the infinite regress problem appears to be intractable. However, this problem is clearly solved in all living systems. So what is the difference?” I could not really answer these questions.
Later, when I sent the published paper to a well-known intelligent design proponent, he also asked me, “What is it about life that circumvents the T to U to V regress?” I replied:
I don’t know, of course; in the last paragraph I linked to the video “Conception to Birth — Visualized.” Tsarias says it’s “divinity.” It’s hard enough to get people to believe that “bacteria to Beethoven” required divinity, much less that “Beethoven to Beethoven” requires something beyond unintelligent forces, since we see this happen daily. But when I spend time with my young grandsons, I’m convinced that it does.
How Indeed?
“How do these instruction sets not make mistakes as they build what is us?” asks Alexander Tsarias in his “Conception to Birth — Visualized” video. How indeed? I believe Sternberg is correct that the process from conception to birth seems to “require an external source of information to correct errors.”
So it does not really require any cutting-edge molecular biology or any higher mathematics, only a little common-sense reasoning, to at least understand why reproduction poses a difficult paradox for materialistic science despite the fact that we see it happen every day.
