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This article is from
Creation 43(3):15, July 2021

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The waiting time problem

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Posted on homepage: 13 June 2022 (GMT+10)
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DNA carries the instructions for how and when to make the principal components of cells, called proteins. Different organisms differ in their DNA instructions (composed of DNA ‘letters’, technically called ‘base pairs’) such that they make at least some different proteins.

To change an organism into a different kind, you would have to have a mechanism for changing the letters. For evolutionists, the ‘only game in town’ to change the letters is mutation. Mutations are accidental changes to the instructions, which can be one letter at a time, or multiple letters at once. Letters can be swapped, deleted, or added. Obviously, to change an organism into something more complex, letters would have to be added, not just swapped or deleted.

Now consider that human DNA has about 3,000 million letters, which is equivalent to a thousand Bible-sized books. Imagine an ape evolving into a human. We have to add letters—via mutations—to create the information for the features that humans have that apes do not have. This amounts to a difference of at least 10%, compared to our closest relative, according to evolutionists—the chimpanzee.1 That amounts to 300 million letters!

Imagine that an ape has a baby and a mutation has added one letter to the baby’s DNA. Would the mutation be ‘beneficial’ in terms of progressing evolution? ‘Beneficial’ here means only that the baby will grow up to have more offspring than other apes that don’t have the mutation. Would natural selection be able to ‘see’ it and favour the survival of the mutation into the following generations? This is known as ‘fitness’. The probability that this random change will contribute enough to the individual’s fitness for natural selection to be able to ‘see’ it is very low. Evolutionary geneticists acknowledge this.

Now imagine that another mutation occurs, not just anywhere, but next to the one above, in an individual that has the mutation passed on to them. There could be a population of evolving apes, of say 10,000. The ‘right’ mutation is more likely to occur in the offspring of apes other than the one that already has the first such mutation. And then they have to meet, mate, and have babies, which is unlikely. Or, over many generations the mutations might spread slowly through the population, increasing the chance of them getting together in a mating pair. This obviously takes time.

How much time? Calculating this is complex, taking everything into consideration, such as mutation rate, fitness due to the mutations, number of offspring, generation time, population size, etc. Well, a team of scientists created a computer program, called Mendel’s Accountant,2 which does these calculations. In a review more than a decade after the program was first published, CMI geneticist Dr Robert Carter commented,

We are unaware of any peer-reviewed paper that attempts to refute the methods or conclusions of Mendel. After a decade of established work, there should be something. Their silence is telling.3

The program simulates or models a real population and can work out how long it would take to get these DNA letters lined up next to one another.

When numerical assumptions are made that favour evolution happening, such as unrealistically high fitness from the mutations, it takes 84 million years to get just two letters lined up in an individual.4 This greatly exceeds the timeframe—about seven million years— evolutionists give for the evolution of humans from a common ancestor with chimps. To get just five letters lined up together, the time exceeds two billion years! This is not even a tiny fraction of a single small gene, which might be several hundred letters long. Many genes are thousands of letters long. This is the ‘waiting time problem’—for evolution.

In other words, evolution of humans from apes is not just unlikely or improbable, but impossible.

References and notes

  1. Tomkins, J. and Bergman, J., Genomic monkey business—estimates of nearly identical human–chimp DNA similarity re-evaluated using omitted data, J. Creation 26(1):94–100, 2012; creation.com/chimp. Return to text.
  2. Sanford, J. et al., Mendel’s Accountant: a biologically realistic forward-time population genetics program, SCPE 8(2):147–165, 2007; scpe.org. Return to text.
  3. Carter, R., A successful decade for Mendel’s Accountant, J. Creation 33(2):51–56, 2019; creation.com/mendels-accountant-review. Return to text.
  4. Sanford, J. et al., The waiting time problem in a model hominin population, Theor. Biol. Med. Model. 12(18), 2015. Return to text.

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