{"id":43548,"date":"2026-01-26T15:54:26","date_gmt":"2026-01-26T23:54:26","guid":{"rendered":"https:\/\/idthefuture.com\/?p=43548"},"modified":"2026-01-26T15:54:36","modified_gmt":"2026-01-26T23:54:36","slug":"2166","status":"publish","type":"post","link":"https:\/\/idthefuture.com\/2166\/","title":{"rendered":"Applying Information Conservation to Biological Origins"},"content":{"rendered":"\n

Nothing’s free in life. It’s a sobering reality we all come to realize one way or another. And this important truth also applies to the realm of biology. On today’s ID The Future<\/strong>, host Andrew McDiarmid continues his four-part discussion with mathematician and philosopher Dr. William Dembski. The topic is Dembski’s work on the law of conservation of information, a principle asserting that information within a search process is redistributed from pre-existing sources rather than materializing from nothing. In addition to being used in computer science and physics, the law can also be applied to theories of biological origins to evaluate which theory best comports with the reality that all information comes with a cost, and that cost must be adequately explained.<\/p>\n\n\n\n

In this segment of the conversation, Dr. Dembski explains why Darwinian evolution depends on a search and why evolutionary mechanisms are subject to the law of conservation of information. While some have claimed Darwinism is not a search, Dembski begs to differ, explaining that biology must successfully navigate a nearly infinite space of non-functional possibilities to reach specific, functional biological targets\u2014such as the genetic code or the bacterial flagellum\u2014that are essential for life. He contends that if evolution is not viewed as a targeted search for these complex natural kinds, the theory fails to provide a model that accounts for the staggering increases in complexity observed in the biological world.<\/p>\n\n\n\n

The discussion also exposes the displacement fallacy found in famous evolutionary simulations, including Richard Dawkins\u2019s “Me Thinks It Is Like a Weasel” and the Avida program. Dembski explains that these programs smuggle in the information they claim to create by incorporating target sequences or rewarding specific boolean functions directly into the code. Critiquing Dawkins\u2019s “Mount Improbable” metaphor, Dembski notes that while gradual steps may make an outcome appear probable, it’s the specific topography or mountain that allows for such a path that is itself highly improbable and requires an external information source. Dembski holds that creative innovation in biology requires an irreducible intelligence that transcends the limits of mindless, material algorithms.<\/p>\n\n\n\n

This is Part 3 of a four-part conversation. Look for the conclusion next!<\/p>\n\n\n\n

Dig Deeper<\/h2>\n\n\n\n