A new peer-reviewed paper in BIO-Complexity, co-authored by four pro-ID scientists — Emily Reeves (PhD Biochemistry), Brian Miller (PhD Physics), Jonathan McLatchie (PhD Evolutionary Biology), and myself (PhD Geology) — provides a how-to manual for helping scientists use the theory of intelligent design to guide their research.
Titled “The Broad Utility of the Theory of Intelligent Design to Guide Scientific Research,” the paper explains what the theory of intelligent design is and how it can be used to generate testable scientific predictions, or “expectations” as we call them. It then reviews various case studies of how ID is being applied to conduct research in a variety of fields. We worked on this paper for over a year and we’re really excited to see it published — hopefully it will be useful for scientists looking to understand how to use ID to do research!
What Is Intelligent Design?
Our paper begins by explaining what intelligent design is:
Intelligent design (ID) is a scientific theory that uses the methods of historical sciences to infer that many features of nature are best explained by an intelligent cause because they exhibit forms of information and complexity that in our experience only come from intelligence. ID is fundamentally a theory of design detection, but it has also been applied as an experimental science to guide research into how the natural world operates in the present day. ID uses a positive argument, beginning its investigations by studying known-designed objects and the actions of intelligent agents to identify properties that indicate design, such as complex and specified information, irreducible complexity, purposeful coordination of parts, common design patterns, and functionality. Natural features can then be studied to determine whether they meet the criteria for detecting design. These hallmarks of design can then be further applied to model or predict how designed natural systems function.
We then review three main classes of ID research: theoretical design research, design-detection research, and applied design research. Here’s how we frame it:
Theoretical ID research has focused on developing “the theoretical mathematical and philosophical foundations for detecting design.” The paper reviews peer-reviewed publications by ID theorists such as William Dembksi, Robert J. Marks, Winston Ewert, George Montañez, Michael Behe, and others developing the theoretical bases for using concepts like complex and specified information and irreducible complexity to detect design.
Design-detection research represents intelligent design operating “as a historical science which seeks to determine whether intelligent causation is the best explanation for the origin of a natural feature.” The paper then reviews peer-reviewed publications by ID theorists such as Stephen Meyer, Douglas Axe, Ann Gauger, and others providing historical scientific arguments for intelligent design.
Applied design research represents research where ID theorists can “use design-based methodologies and hypotheses to model and predict how natural systems operate.” This especially involves using ID-based engineering principles to reverse-engineer the operation of biological systems. The paper further reviews work by many ID theorists applying ID to discover how nature works.
Using the Scientific Method to Generate ID-Based “Expectations”
The paper also explains how scientists can use the theory of intelligent design to do research. The evidence for design in nature can be investigated using the scientific method of observation, hypothesis, experiment, and conclusion. In this way, the theory of intelligent design begins with “observations about the causal powers of intelligent agents,” which are then used to “propose hypotheses and expectations about what should be found if intelligent design is correct.” These hypotheses, expectations, and predictions can then be experimentally investigated. This can be done in two different ways: either using ID “as a historical science to study the origins of natural features,” or using ID “as an experimental science to study the present-day operation of a designed feature.” The paper lays out case studies of using the scientific method to detect design in fields such as biochemistry, paleontology, systematics, and physics, or using the scientific method to study the operations of natural features in fields such as genetics, systems biology, biomechanics, and neurophysiology.
This scientific method can be used to generate a variety of predictions, or expectations, of what should be found in nature if intelligent design is correct. These include:
- Goal-directed operation
- Presence of high CSI.
- Existence of rare solutions to complex problems.
- Structured with a top-down design where multiple parts are coordinated to accomplish a purpose or goal, including a hierarchical design, wherein subcomponents are coordinated to contribute to higher functions at each level.
- Presence of irreducibly complex systems (e.g., machines).
- Reuse of functional components in different systems.
- Performance optimized to meet competing constraints.
- Components have a purpose and function.
- Rapid appearance of new information, where systems are fully formed and designed to be functional from the outset, showing some degree of discontinuity from other pre-existing systems.
These expectations are testable and can be used to guide research into both the origins and operations of natural features.
Reviewing the ID Research Program
The balance of the paper reviews many real-world examples of where research is being conducted using ID-based principles to study both the origins and operations of natural features. These include:
- Protein Science, where ID research is showing that “only 1 in 1077 possible amino acid sequences would yield a functional protein fold in [a] fairly typical enzyme,” or protein evolution where the amount of time required for “converting one protein to perform the function of a closely related protein would take over 1015 years, a duration much longer than the age of the Earth.”
- Genetics, where ID theorists are studying unique orphan genes since ID predicts that “information in biology need not be connected to material antecedents,” or junk DNA where “ID theorists long predicted that so-called junk DNA would turn out to be largely functional.”
- Systematics, where “designers regularly reuse parts in different systems according to the functional requirements of those systems, often called ‘common design,’” leading to the development of dependency graph models which “confir[m] the engineering expectation that a designer’s reuse of parts in different organisms for functional reasons is a possible explanation for organismal similarities.”
- Systems Biology, which “assumes there is a hierarchical, top-down design in living systems,” consistent with how human designers engineer technology. According to the paper, “Research conducted by design scientists over the past five years has extended the design-based assumptions of systems biology through the development of reverse systems engineering methodology.” This includes ID-based reverse-systems-engineering research into the operation of the bacterial flagellum, chemotaxis, and glycolysis, leading to new insights into the how these systems work.
- Biomechanics, where “engineering principles, especially from mechanical and electrical engineering, have significantly advanced the study of anatomy and physiology.” The paper reviews how “ID-based engineering analyses” have led to insights into the function and operation of vertebrate joints and limbs, the human foot and leg, the human hand-wrist-arm complex, feathers, and the general design of vertebrate limbs. Regarding the last of those examples, the paper recounts that pro-ID engineer Stuart Burgess has shown that “there are good functional reasons for its widespread reuse.” The paper also discusses how ID-based models are using engineering principles to yield insights into brain blood flow, including leading to improved therapies for treating hydrocephalus.
- Biomimetics: In many of these examples, ID-based engineering studies are revealing properties of natural systems that can aid in the improvement of human technology.
A Tour of Intelligent Design
This paper is a 40-plus page tour of what ID theory is and how scientists can use it to make predictions and guide research, followed by a comprehensive review of the ID research program. It shows that ID can “broadly be applied in a variety of scientific subdisciplines to guide research and make new discoveries” and that “the possibility of a ‘design science’ is becoming and has already become a reality.”
We hope that this paper will be a tool that students and scientists can use to learn how to apply ID to do their own research. Or, if your skeptical friend thinks ID isn’t science, give him this paper and hopefully it will change his mind.
There’s more to say about the development of this paper — we look forward to telling those stories in the future.