One of the foundational books undergirding the intelligent design research program is The Design Inference: Eliminating Chance through Small Probabilities, by mathematician and philosopher William Dembski. He developed a rigorous methodology for design detection. His work was initially praised by esteemed scholars. Then, he applied his design-detection apparatus to biology and demonstrated that life displays clear evidence for design. After making this connection, he faced enormous opposition for daring to challenge the sacred dogma of secular society that life is an unintended product of the blind forces of nature.
Many of the attacks were little more than knee-jerk reactions, but some raised legitimate concerns and asked relevant questions. In the decades that followed, Dembski responded to critics and refined his model. He also collaborated with computer scientists Robert J. Marks and Winston Ewert, along with other scholars, to expand upon his initial ideas and further apply them to biology (here, here, here).
Most recently, Dembski partnered with Ewert to write a second, greatly expanded edition of The Design Inference, which is being released today. The new edition represents the culmination of decades of thought and research. It presents a rigorous and reliable procedure for detecting design in any context. The esteemed Princeton University mathematician Sergiu Klainerman welcomed the book as follows:
Well argued and eminently readable… I don’t see how any open-minded scientist can ignore this important book.
Here I will present a primer on design detection that will aid readers in appreciating the genius behind Dembski and Ewert’s accomplishment.
The Logic Behind Design Detection
The fundamental goal of any approach to design detection is identifying patterns, events, or artifacts that (1) are extremely unlikely to have occurred through chance and natural processes and (2) show signs that they were deliberate acts of a mind. The challenge is rigorously meeting both criteria. Nearly everyone recognizes that the criteria have been properly met in certain contexts. Forensic experts can often clearly distinguish between a death resulting from natural causes and homicide. Archaeologists readily distinguish between naturally occurring rocks and an arrowhead. And tourists easily differentiate between patterns on mountains resulting from wind and erosion and the faces of the Presidents on Mount Rushmore.
In every context, the first criterion entails identifying, at least qualitatively, the probability for the occurrence of some event or outcome solely due to chance and natural processes. For instance, the probability of any number between 1 and 6 appearing on a well-constructed six-sided die is 1 in 6. The outcome is purely the result of chance. In contrast, the probability of rolling a 6 on a loaded die could be close to 100 percent. The outcome is a direct result of gravity.
The outcome could also be the product of chance and natural processes. The structure of a snowflake displays a hexagonal pattern due to the physical properties of water molecules. It also displays its own unique features due to chance molecular interactions. Determining the probability of undesigned outcomes must take into consideration both factors.
The second criterion entails a mind assigning significance or value to some outcomes independently of any law-like process. As a thought experiment, imagine Bill Gates deciding on a whim to give one billion dollars to five specific people scattered throughout the world. In addition, the day after the money was dispersed, you were one of six people invited to a dinner party. If you discovered that four of the five recipients of Gate’s generosity were also invited, you would know that the invitees were not chosen randomly. You would also know that the invitations were not primarily based on any factors independent of the invitees’ newfound wealth, such as their height or weight or nationality. The guests were deliberately chosen for some premeditated purpose, such as raising money for a charity or a political campaign.
The key elements for this conclusion are (1) the number of combinations of six people chosen out of the entire human population being extremely high and (2) and the number of combinations of six people possessing such wealth being much lower. The disparity between the probability of choosing randomly a specific set of six people and the probability of randomly choosing a set out of all sets of six people with at least that much wealth is what points to design.
Application to Biology
The argument for design in biology follows the same logic. The number of configurations of atoms resulting from chance and natural laws is unimaginably large. By comparison, the number of configurations is vastly smaller that correspond to life or anything to which a mind would attribute the same significance as life, or nearly so, such as a computer with an advanced AI or an automated space shuttle capable of colonizing mars.
Stated differently, the probability of a configuration of atoms corresponding to life occurring through chance and natural processes is unimaginably small. By comparison, the probability is vastly larger of choosing life out of a pool of entities that are as significant, or nearly as significant, as life.
Understanding the Design Debate
The design debate centers on one of the two criteria. Design proponents have described the exceedingly low probability of some biological system or structure emerging, such as a random sequence of amino acids folding into a functional protein. They also point out the significance of biological components, such as folded proteins, in the context of life.
Some critics challenge the first criterion by arguing either that biological structures are not as rare as design proponents believe, or that natural processes such as self-organization and natural selection dramatically improve the odds of their forming. Others challenge the second criterion by arguing that a specific structure might be extremely unlikely to occur by chance and natural processes, but biological structures are not as special as design proponents believe. Critics assert that life could have used many other structures to accomplish the same tasks, so the probability of finding anything that serves a particular purpose is tractable.
The second edition of The Design Inference lays out the theoretical framework and practical methodology for addressing all these objections. In addition, advances in biology over the past few decades allow the methodology to be rigorously applied. Such analyses demonstrate evidence for design that is now so clear and rigorous that, for intellectually honest and sincere seekers of the truth, denying it is no longer feasible.