We already have a well-established law that shows us how order can decrease in a physical system. But is there a law that explains an increase in order? Scientists have been looking for “nature’s missing law” for a while, and while they might be asking the right questions, their training in a bottom-up reductionist framework is leading them to the wrong answers. On a new episode of ID the Future, mathematician and philosopher Dr. William Dembski continues a four-part conversation with me about his work on the law of conservation of information and its implications for theories that attempt to explain the origin of life and the universe.
A Proscriptive Generalization
In this segment of the discussion, Dembski characterizes the law of conservation of information not as a positive law that explains how complex order arises but as a proscriptive or negative generalization that defines what naturalistic processes cannot achieve. Much like the Second Law of Thermodynamics forbids the creation of perpetual motion machines, Dembski’s law asserts that you cannot get something for nothing when it comes to the information required for life. He argues that materialistic attempts to find a bottom-up law of formation are fundamentally flawed because they attempt to increase the probability of a functional outcome by introducing an amplifier, or mechanism, yet they fail to account for the extreme improbability of that mechanism itself. Dembski likens this effort to the act of filling one hole by digging another. In the end, you still have a hole to fill. The informational cost is simply moved around rather than truly explained.
A Prior Deposit of Information
Dr. Dembski also shares some of the historical pedigree of the law of conservation of information. Drawing on historical insights from thinkers like Ada Lovelace, who observed that machines have no “pretensions…to originate anything,” and French physicist Leon Brillouin, Dembski provides mathematical rigor to the concept that output cannot exceed input. This acts as a balance sheet for information, revealing that any search process — whether in biology or modern Large Language Models (LLMs) — that appears to beat the odds has actually relied on a prior deposit of information. Dembski contends that while AI can draw interesting connections, it lacks fundamental creativity because it is constrained by its training data. Without a purposeful agent to overcome probabilistic obstacles, such systems cannot generate truly new, highly improbable and surprising content. The bottom line here? The law of conservation of information shows that intelligence is a necessary requirement for the complex functional information found in nature.
Download the podcast or listen to it here. This is Part 2 of a 4-part conversation. Listen to or watch Part 1.
Dig Deeper
- Ready to learn more? Download Dr. Dembski’s monograph at no cost!
- Watch Part 1 of this conversation: