It’s something you may have tried to convey to your kids: Nothing in life is really “free,” despite claims to the contrary. There is always a cost to every good. In other words, there is “no free lunch.”

Notwithstanding, evolutionary biology has been helping itself to free lunches since the inception of the field. As molecular biologist Doug Axe says in an excerpt from his new online course at DiscoveryU, “Douglas Axe Investigates Molecular Biology and Intelligent Design,” unguided evolution faces a massive “search” dilemma. To innovate by searching a space of solutions to problems, without intelligence or insight, it has to rely on sampling. That can be done randomly, or using an algorithm. Will either do the job?

The “Cost” of the Lunch

In 1995, machine learning theorists David Wolpert and William Macready explained, without reference to evolution, why insight is key. As Axe summarizes their No Free Lunch theorem, “Unless you know something about the structure of the space that is being sampled, there is no algorithm that will outperform random sampling.” Natural selection, the “blind watchmaker,” is a kind of algorithm. Evolutionists say it’s not “random,” and they’re right. But the upshot of the No Free Lunch idea is that the algorithm can’t do better than a random approach — it’s no more effective than if it were “random” — in the absence of a notion of the “structure of the space that is being sampled.” Intelligent design is what supplies that notion. However Darwinists might seek to obscure this, a mind behind evolution is the “cost” of the lunch.

Dr. Axe illuminates some quite abstract thinking in a very accessible way. In 40 brief lectures, his course covers three broad units: (1) Proteins and Genes, (2) Evolution, and (3) Intelligent Design. That there is a design to life is intuitive, but most of us, if challenged on it, would want to be able to defend our intuition persuasively. Giving you the ability to do that is one of the values of courses like this from DiscoveryU. You can get started right away. Watch the sample now: