The inherent randomness in evolutionary processes has famously been used in attempts to undermine the claims of natural theology, specifically the role of deity in the development of complex life forms. Richard Dawkins, for instance, has suggested that, “a universe with a creative superintendent would be a very different kind of universe from one without.”[1] Unfortunately, theists (and deists) confronted with such attempts and lacking a viable response, frequently interpret them as simply one more reason to reject evolution. Yet, a refusal to accept either divinity or the theory of evolution because of mistaken ideas about the nature of random processes is not only unnecessary, it is predicated on a basic set of highly questionable assumptions about randomness itself, about how God could or could not work, and about human inability to undermine those assumptions.

Thus, claims that randomness denies a creative role for deity become suspect if it can be shown that constraints on chance result in boundaries that enable some level of predictability. The constraints might constitute a kind of foreknowledge, with the interaction of those constraints tuning the accuracy of the predictions. The challenge is to show how this might actually work in practice. Efforts by scientists such as Richard Lenski to trace actual biological evolution are restricted to rapidly reproducing species such as E. coli and have, so far, shown impressive but limited results. Species change (the Achilles’ heel of demonstrable evolution) has certainly not been one of them.

A team lead by a scientist, a statistician, and a theologian from the Samford University Center for Science and Religion is attempting to address these problems. The project raises a number of fascinating scientific issues involving evolutionary mechanisms, randomness, and emergence with potential implications for insights into divine action. A better understanding of constrained randomness in creation could be a bridge between currently competing and seemingly incompatible views regarding God’s creative activity.

[1] Dawkins, R. (2006). The God Delusion. Houghton Mifflin: Boston, MA, p. 55.

In the areas of science and mathematics this project will

1. show the power of evolutionary approaches to generate neural architectures under the influence of constrained random processes.
2. demonstrate evolutionary pathways for increasingly complex neural architectures.
3. qualify and quantify the effects of a variety of constraints on the random factors controlling the evolutionary processes in our simulations with a view to how that translates into real biological systems.
4. develop formal mathematical relationships between the constraints and the results.
5. provide new support for claims of the power and necessity of self-organizing principles.

In the area of theology the project will provide

1. actual data that provides empirical support for the compatibility of God and evolutionary processes, clearly suggesting how constrained randomness might serve the purposes of deity.
2. a productive means to bridge the gap between differing religious views of creation as well as between conflicting religious and secular views.
3. concrete ways to think about the issue of God's foreknowledge.
4. new examples of how Christian theologians and scientists can legitimately explore these issues without losing their standing in either scientific or religious communities.
5. expanded understanding about what it might mean to be created in the image of God.

We hope that our work might be a springboard for scientists, mathematicians, theologians, philosophers, churches and the general public from which to explore the connection between constrained randomness, self-organizing systems, and the problems of consciousness and freewill, and extend awareness of both the scientific and theological potential in this way of apprehending the world.

Primary Investigators

Steve Donaldson, Ph.D.—Samford University, Project Leader

Dr. Donaldson is a computer scientist whose primary interests and specialties involve cognition (real and artificial) and relationships between science and religion. He led the effort to develop the simulation system that will be used to explore the scientific questions we pose and his published results provide the starting point for this project.

Tom Woolley, Ph.D.—Samford University

Dr. Woolley is a statistician located in the School of Business who came to Samford because it provided an environment where he could pursue answers to questions involving the connection between chance and deep questions of meaning and value. Besides his own statistical research, Dr. Woolley’s background includes extensive support for a variety of projects requiring statistical analysis, including many with biological components.

Josh Reeves, Ph.D.—Eastern Kentucky University

Dr. Reeves is a young theologian whose intense interest, study, and growing publication history in the areas of science and religion position him to play a lead role in posing and pursuing the theological questions that arise naturally from the empirical and mathematical results of this work.

Consultants

Bruce Atkinson, Ph.D.—Samford University

Dr. Atkinson is chair of the department of mathematics and computer science and has an extensive background in probability theory. His role is to help the team frame its empirical results with a view to mathematical rigor and to lead the search for formal proofs of suspected relationships between random variables and simulation outcomes.

George Keller, Ph.D.—Samford University

Dr. Keller is a biologist with a keen interest in science and religion. In order to draw many of the types of inferences suggested by our work, it is crucial to maintain plausible connections between our simulations and the natural world and Dr. Keller will assist in that capacity.

Wilton Bunch, M.D., Ph.D.—Samford University

After a long career as a physician and medical researcher, Dr. Bunch returned to school to pursue a masters degree in theology. He is an ordained Episcopal minister, former faculty member of Beeson Divinity School, and currently affiliated with the Department of Philosophy. His broad interdisciplinary background and penetrating insights will help bridge the gap between the scientific and theological components of the project.

Brian Toone, Ph.D.—Samford University

Dr. Toone is a computer scientist who will be involved with parallelizing the genetic algorithm used in the simulations. Attempts to evolve more complex entities (particularly when lifetime learning becomes crucial) tax machine resources and parallelization becomes important.

Student Researchers, 2013

Nick Dzugan - University of Alabama at Birmingham

Nick is a Samford graduate with a B.S. degree in Computer Science and Mathematics. He attends UAB as a graduate student of Computer Science. His prior research experience (with image combination via point clouds) and studies have well prepared him to work with the evolutionary simulation system and assist in formulating mathematical results.

Jason Goebel - Samford University

Jason is a senior Biochemistry major and Bioinformatics minor. He has research experience exploring the scaffold development of amino acid derived chirons and the synthesis of "smart" therapeutics that can simultaneously target, detect, and treat disease. His role in this project is to work with the evolutionary simulation system and provide insight from his biochemical background.

Melanie McConnell - Samford University

Melanie is a junior Science and Religion major with a concentration in religion. She is actively involved with the Center of Science and Religion, and in this project, researches contemporary literature concerning randomness and the use of simulations to stimulate theological and philosophical thinking.

Student Researchers, 2014

Sarah Bowhay—Samford University (senior Biochemistry major and Bioinformatics minor)
Matt Foreman—Samford University (junior Mathematics and Computer Science double major)
Anna McLendon—Samford University (senior Computer Science major)
Jared Nelsen—Samford University (senior Computer Science major)
Meredith Robinson—Samford University (senior Mathematics major and Bioinformatics minor)
Matt Skinner—Samford University (senior Sports Medicine major)

Our simulation environment permits specification of a number of probabilistic components affecting genetic operations involving crossover, mutation, and genome duplication. Mutation operators include addition and deletion of neural modules, modification of module parameters (such as its type, muscle target, sensory status, and process mode), and modification of connection parameters (involving connection addition and deletion, target modules, whether a set of connections is trainable, and the probability of creating connections between any two modules). The genomes affected by these operators serve as the blueprints for simulated neural circuitry whose purpose is to solve some problem(s) facing the evolved entities.

Previous work with this system suggests that, although the neural circuitry that is evolved to solve a particular locomotion problem can vary from simulation to simulation, it is not unreasonable to predict that circuitry sufficient to solve the problem will, in fact, evolve. Lenski, et al. found similar results with Avida, but this is not entirely surprising in either system given the nature of evolutionary simulation systems where constraints on the random processes and implementation of the fitness function lead to a certain level of predictability. As the number of random variables in a system increases, however, so does the size of the search space and that would lead one to expect that the range of resulting phenotypic variability would also increase. Yet this assumption might be challenged by the observation that not all random factors are necessarily created equal or that certain factors might work in concert to limit the possibilities.

Can digital programs such as the ones we propose reliably simulate evolution?

Attempting to replicate biological evolution is not feasible due to the extensive time required and an inability to re-create historic environments. However, evolutionary programs such as Avida and Tierra have demonstrated some notable successes simulating the evolution of digital organisms [2]. The crux of the issue is that certain abstractions from the organic processes must be made—too many lead to overgeneralizations and unrealistic results, too few and simulations cannot produce meaningful results in the allotted time. Part of this research involves determining which abstractions might be appropriate. A basic example is how to represent the genome of a simulated organism. Refer to the section "Description of Evolutionary Simulation System" (above) for a description of some of the other factors that can play a significant role.

Does this experiment deal with macroevolution? Is the theory of evolution adequately supported?

The aim of this project is to provide potential insights into biological evolution, of which a notable biologist and Christian famously said, “nothing in biology makes sense except in the light of evolution” [3]. Macroevolution is difficult to study, but substantially explains evidence from five main fields: the fossil record, comparative anatomy, comparative embryology, biogeography, and molecular biology. “Evolution, although not without its puzzles and controversies, is now so well supported that it demands our assent.” [4]. Well, “demand” may be a bit strong but the evidence is certainly there. In any case, although our simulations involve relatively simple neural architectures, they promise to demonstrate how complexity characteristic of species change can arise in an evolutionary setting.

Does randomness conflict with Biblical truths?

It is gradually being realized that, far from the epic of evolution being a threat to Christian theology, it is in fact a stimulus to and a basis for a more encompassing and enriched understanding of the interrelations of God, humanity, and nature [5]. Nevertheless, randomness, especially as used in evolutionary processes, raises significant questions regarding compatibility with certain approaches to Biblical interpretation. It is our contention, however, that a better understanding of randomness will help us better understand both God and the Bible. Our results will aid consideration of age-old issues including theodicy, divine omniscience, and divine action, and potentially open new ways to consider topics such as consciousness and free will.

How does this project define 'random'?

“A popular conceptualization of randomness is not having a governing design, method, or purpose; unsystematic; without cause. But this concept is not how randomness is actually used in mathematics, statistics, and the sciences” [6]. Instead, “random” refers to a lack of reason in the correlation of events, regardless of the motivation behind single instances. In the context of this project, “random” simply means “unpredictable.” Physicist and theologian John Polkinghorne provides this illustration: “An analysis of the test of Hamlet would show various statistical associations between the letters and the words, but it ultimately would have to conclude that the precise sequence of words was unpredictable. Thus, in a scientific sense, we can say that Hamlet is random, but there is clearly a deep rationality at work” [7].

Is the randomness used in this project “pure” randomness?

The source of the randomness, whether “pure” or not, does not matter. The outcomes themselves are still unpredictable and randomly correlated whether the initial parameters and constraints are known, as in a random number generator, or not.

Does “random” necessarily mean “arbitrary” or “meaningless”?

“The materialist claim that any randomness in the world proves there is no purpose to our existence is seen to be a fallacy” [8]. Science cannot answer questions concerning non-physical entities like meaning or purpose. Statistical randomness may be measured and observed, but science itself cannot conclude the meaning behind it. Instead, we turn to philosophy and theology to help us answer these questions. Scientific findings neither prove nor disprove meaning in anything.

How can there be meaning in randomness?

Scientists and theologians suggest several ways in which randomness might serve the creative purposes of deity:

“This interplay of chance and law is the basis of the inherent creativity of the natural order, its ability to generate new forms, patterns, and organizations of matter and energy. One might say that the potential of the being of the world is made manifest in the becoming that the operation of chance makes actual. God is the ultimate ground and source of both law (necessity) and chance.” [9].

“I would say that fruitful interplay between chance and necessity is a reflection of the twin gifts of freedom and reliability which God has given to the world, gifts which are the reflections of the combined divine nature of love and faithfulness” [10].

Overall outcomes can be purposive even in presence of chance. The purpose of the randomness is to preserve free will, moral responsibility and also to leave God free to act—to maintain his sovereignty [11].

“But all order originates in God and that includes the order in randomness. As Michael Heller points out, the laws of probability are still laws” [12]

Bak, P. (1999). How Nature Works: The Science of Self-Organized Criticality. Springer: New York.
Beltrami, E. (1999). What Is Random?: Chance and Order in Mathematics and Life. Copernicus: New York.
Donaldson, S. and Walling, C. (2012). A system for evolving neural architectures. In S. Vrbsky (Ed.), Proceedings of the 50th Annual Association for Computing Machinery Southeast Conference. Tuscaloosa, AL: Association for Computing Machinery, 232–237.
Donaldson, Steve (2008). A neural network for creative serial order cognitive behavior. Minds and Machines, 18:53–91.
Kauffman, S. (1996). At Home in the Universe: The Search for the Laws of Self-Organization and Complexity. Oxford University Press: New York.
Kennedy, J. and Eberhart, R. (2001). Swarm Intelligence. Morgan Kaufmann: San Francisco, CA.
Lenski, R., Ofria, C., Pennock, R., Adami, C. (2003). The evolutionary origin of complex features. Nature, 423(May 8): 139–144.
Mitchell, S. (2009). Unsimple Truths: Science, Complexity, and Policy. Chicago University Press.
Morowitz, H. (2002). The Emergence of Everything: How the World Became Complex. Oxford University Press: New York.
Morris, S. (2003). Life's Solution: Inevitable Humans in a Lonely Universe. Cambridge University Press, NY.
Ulanowicz, R. (2009). A Third Window: Natural Life Beyond Newton and Darwin. Templeton Foundation Press: West Conshohocken, PA.
Watts, F. (2008). Creation: Law and Probability. Fortress Press: Minneapolis, MN.