In a recent episode of the Mind Matters podcast, hosted by Pat Flynn, Dr. Winston Ewert, a computer scientist and researcher, discussed his contribution to Minding the Brain (Discovery Institute Press, 2023). His chapter, “The Human Mind’s Sophisticated Algorithm and Its Implications,” explores the computational nature of human cognition and its broader philosophical consequences.

Dr. Ewert’s Background and Research

Dr. Ewert, a self-admitted computer nerd, initially studied computer science through computer simulations of evolution. During his graduate studies at Baylor University under Dr. Robert J. Marks, he critically examined these simulations. He found that they often involved substantial intelligent guidance rather than truly naturalistic evolutionary processes. This background led him to explore questions about the nature of human cognition and whether it can be understood as a computational process.

The Computational Model of the Mind

At the core of Dr. Ewert’s argument is the idea that human cognition can be modeled as a highly sophisticated algorithm. He makes a distinction between two aspects of the human mind: phenomenal consciousness (our subjective experience) and problem-solving cognition (our ability to reason, calculate, and infer). While he acknowledges that phenomenal consciousness poses significant challenges for computational explanations, he argues that problem-solving cognition can be understood algorithmically.

Dr. Ewert aligns himself with the computational theory of mind, which suggests that human reasoning operates much like an advanced algorithm executing step-by-step procedures. He points out that in the past, the term computers referred to humans who followed mathematical procedures manually — an idea that reinforces the notion that cognition can be algorithmic.

The Halting Problem and Human Cognition

To illustrate his argument, Dr. Ewert references a well-known concept in theoretical computer science: the halting problem. This problem, first identified by Alan Turing (1912–1954), involves determining whether a given algorithm will eventually reach a conclusion (halt) or continue indefinitely. Turing showed that there existed no computer program that could solve the halting problem.

Dr. Ewert argues that many cognitive tasks can be framed as variations of the halting problem. For example, a mathematical conjecture like the Goldbach conjecture—which states that every even number greater than two can be expressed as the sum of two prime numbers—could be tested algorithmically by systematically searching for counterexamples. If a counterexample is found, the search halts; if not, it continues indefinitely. Since humans can solve some halting problems but not others, he suggests that human cognition resembles an advanced, but still finite, solver of some halting problems.

Implications for Artificial Intelligence and Materialism

Dr. Ewert’s argument challenges both materialist and computationalist views of the mind. While some theorists resist the idea that human cognition is algorithmic, he argues that if it is, that fact does not necessarily support a purely naturalistic view of intelligence. Instead, recognizing human cognition as an algorithm raises deeper questions about the origin and sophistication of that algorithm.

A key implication of his argument is that even if AI systems were to replicate human problem-solving abilities, they would still be constrained by the fundamental limitations of algorithmic computation, such as the inability to solve the general halting problem.

This suggests that AI, while powerful, may never fully replicate human cognition in all its complexity.

Moreover, Dr. Ewert highlights how intelligent design principles are embedded in many AI models and evolutionary simulations. The presence of teleological fine-tuning—where systems are guided toward pre-determined outcomes—demonstrates that intelligence is often a necessary ingredient in producing complex, functional results.

This observation further complicates the idea that human intelligence emerged solely through unguided evolutionary processes.

Final Thoughts

Dr. Ewert’s discussion sheds new light on the computational nature of human cognition while challenging prevailing materialist perspectives In the upcoming continuation of his discussion, he promises to explore how these ideas intersect with artificial intelligence and the broader philosophical questions they raise about human nature and intelligence.