From ResearchID.org

A Synthetic Overview of Intelligent Design and
Proposals For Procedural Scientific Heuristics

By Joseph C. Camapana* and other ResearchID.org contributors.

ResearchID.org
http://www.ResearchIntelligentDesign.org

* Principle and corresponding author. Email: jccampana (at) gmail (dot) com

This article is available from: http://www.researchintelligentdesign.org/wiki/The_Intelligent_Design_Paradigmatic_and_Heuristics

Copyleft 2006, ResearchID.org. Some Rights Released.
For details please refer to the GNU Free Documentation License, http://www.gnu.org/licenses/fdl.txt.

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Abstract

The scientific theory of intelligent design has several functioning research frameworks that have yielded new applications, methods, and approaches to scientific data. In order to explore these new approaches, this work will first provide a brief synthetic overview of the theoretical, empirical, and technological premises of intelligent design, as well as a summary of the sub-fields that are emerging from the exploration and research of ID. From this array of foundational premises and sub-fields, new scientific heuristics can be readily perceived. These heuristics hold the key to showing a unique and profound harmony with current scientific research, as well as a plentitude of new scientific perspectives and guides to fresh discoveries.

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Contents 1 Abstract 2 Prologue 2.1 “They may yet...” 3 Part I: The ID-paradigmatic 3.1 ID-theoretics 3.2 ID-investigatives 3.3 ID-detection 3.3.1 Comparative approach 3.3.2 Eliminative approach 3.3.3 Composite approach 3.3.4 Mind correlativity 3.3.5 Specified Complexity 3.3.6 Irreducible Complexity 3.3.7 Other design indicators 3.3.8 What ID-detection cannot do 3.4 ID-theoretics, ID-detection, and the origin of life (OOL) 3.4.1 Looking at the evidence 3.4.2 Evidence and the origin of life 3.4.3 Investigating the origin of life 3.5 ID-input 3.6 ID-innovation detection 3.7 ID-method detection 3.8 ID-informatics 3.9 ID-metrics 3.10 ID-heuristics 3.11 ID-synergistics 3.12 ID-empirics 3.13 ID-technics 3.14 ID-programmatics 3.15 ID-paradigmatic 4 Part II: ID-Heuristics 4.1 Research motivation 4.2 What is heuristics? 4.3 Internal framework of ID-heuristics 4.4 ID-heuristics and current science 4.5 ID-axiomatics 4.6 Types of ID-heuristics 4.7 Fuller’s hypothetical 4.8 Question detachability 4.9 Design-centrism 4.10 Primacy heuristic 4.11 Scientific pragmatism 4.11.1 Scientific pluralism 4.12 ID-detection heuristic 4.13 Giving up the Holy Grail of ID? 4.14 Streamlining approaches 4.15 Improving ID-detection 4.16 ID and evolution 4.17 Examples in ID-heuristics 4.17.1 Coding analogies 4.17.1.1 ID-heuristics are helpful 4.17.1.2 Analogy and reality 4.17.1.3 Methodological naturalism and science-stopping 4.17.2 Cell intelligence 4.17.3 Modern science 4.18 ID research 4.18.1 Reinterpretation research 4.18.2 Teleology 4.18.3 Causality 4.18.3.1 Causal specificity 4.18.3.2 Causal derivation 4.18.4 Testability 4.18.4.1 Falsification 4.18.5 Heuristics 4.18.6 Symmetrical 4.19 Researchers and theorists relevant to ID 4.19.1 ID Researchers and theorists 4.19.2 Symmetrical researchers 4.20 ID Relevant Research Themes 4.20.1 ID Relevant Empirical Research 4.20.2 ID Relevant Theoretical Research 4.20.3 Historical ID research 5 Epilogue 6 Appendix 6.1 Acknowledgements 6.2 Dedication 7 References and notes 8 Paradigm Dawning

Prologue

One of the worst “growing pains” thus far for intelligent design (ID) has been rendering exact definitions for scientific research. Exactly what is involved when one says “intelligent design,” and how does this proposal relate to current science? Empirical confirmation of the explanatory claims of intelligent design is possibly one of the most ambitious undertakings in the history of science. As the scientific research of intelligent design continues, unique sub-fields of scientific investigation are emerging. Significant and distinguishable aspects of ID can now be seen that inevitably appear during discussions of the science of ID. While these are recognizably distinct sub-fields, they cooperate in an extremely intimate manner. A scientific paradigm is an overarching hypothetical perspective; a different angle and a unique way of looking at the evidence. With the advent of these sub-fields, and their obvious cooperation, a developing “ID-paradigmatic” or “design paradigm” can be seen. Despite this fact, a descriptive systematic unity of ID, in summary form, has been lacking thus far in its history. The present work, intended for those interested in careful study of intelligent design, will provide a type of summary for this paradigm.

“They may yet...”

There is a clear potential for intelligent design to bring new insight into science. While highly skeptical, even harsh critics admit the possibility. Jeffery Shallit stated that, “Maybe intelligent design will eventually become science.”^[1] Kenneth Miller has stated that, “…can we test design? Yes.” Christopher Wills, professor of biology from UCSD stated that, "[ID] is in principle testable"^[2] Eugenie Scott, the most traveled critic of intelligent design, stated:

“I congratulate Steve [Meyer] and his colleagues because they are at least attempting to come up with some sort of positive arguments for intelligent design. My personal opinion and that of most others is that they haven’t succeeded. They may yet. If they do succeed, then they have a right to be taught.”^[3]

Allen MacNeill, also a critic of intelligent design, commented:

So, as soon as ID theorists stop spending all their time writing press releases and participating in debates, and start spending time in the field and in the lab doing actual scientific research, there might be a place in science for what they discover.^[4]

It is comprehensible to the ID community, and some critics, that intelligent design has some sort of inherent potentiality to contribute to science. What is this potentiality? How can an interested scientist harness this potentiality?

It is the goal of this work to outline some of this potentiality. Terms that other ID theorists may not typically employ will be discussed herein. A general contour of those new words will be given when they emerge, along with some salient commentary on the definitions presented.

Part I: The ID-paradigmatic

A Synthetic Overview of Intelligent Design

The sub-fields of the ID-paradigmatic addressed here are:

1. ID-theoretics
2. ID-investigatives
3. ID-detection
4. ID-input
5. ID-innovation detection
6. ID-method detection
7. ID-informatics
8. ID-metrics
9. ID-heuristics

a. ID-axiomatics

10. ID-synergistics
11. ID-empirics

a. ID-biotics

12. ID-technics
13. ID-programmatics
14. ID-paradigmatic

ID-theoretics

ID-theoretics is the most general outline of what the phrase “intelligent design” entails. This sub-field seeks out patterns in nature that are best explained by intelligence. Relying on physical, scientific evidence, intelligent design seeks to find natural objects or events that contain the same final conditions, or physical histories, as objects that science knows were intelligently designed. This proposed view of ID-theoretics is based upon the scientific observation of intelligent agency and its unique effects (design) in the natural world.

Intelligent design operates by an inductive procedure of inquiry wherein science explores new areas of knowledge by moving from facts and data that are well established, and extrapolating from those areas of knowledge into the obscure knowledge that is being pursued. More specifically, ID makes retrodictive inferences about the past from present evidence. The purpose of using inductive reasoning by intelligent design is to formulate general principles based on specific observations of recurring patterns in samples. So, samples used in an inductive proposition must share one or a subset of designated properties. The induction holds if 1) the examples share the designated properties, and 2) the dissimilarities do not make a relevant difference to the property(ies) one wishes to explain. How does ID utilize inductive reasoning when it proposes that the characteristic of design is found in phenomena? Design can be found in phenomena we factually know were intelligently designed, and design can also be found in phenomena where the cause is not known, e.g. specific microbiological components, certain aspects of the universe, and the universe as a whole.

ID-theoretics is not opposed to science using the causal explanations of chance and necessity. Far from eliminating chance and necessity from science, ID-theoretics is the consideration of intelligent agency amidst the other physical causes of science. In fact, design detection is wholly dependent on chance and necessity for its viability. In order for ID-theoretics to be possible, one must distinguish among the effects of intelligent and non-intelligent causes, making chance and necessity indispensable for the design paradigm. Chance and necessity act as a canvas, on which intelligent causes make their mark. The more we know about chance and necessity on the one hand, and intelligent causes on the other hand, the more we will know about their interactions. Alongside of considerations about intelligent causes, explorations of naturalistic causes must continue under the design paradigm.

In addition to a study of intelligence and design, those researching ID are discovering how science can wield knowledge of design to derive novel scientific applications. Within the context of science, intelligent design is a working scientific hypothesis by which unique data, hypotheses, information, explanations, experiments and technologies are derived. These unique scientific contributions result from hypothetically viewing phenomena in the universe as designed, whether the researcher holds that the objects under study are actually designed or not.

ID-investigatives

ID-investigatives are questions and identifiable scientific puzzles that ID-theoretics brings to an investigation of nature, especially those that other scientific frameworks cannot, would not, or have not asked. The range of investigative areas can be known through understanding the elements involved in causal histories. Causal history is the chronological occurrences of interactions of features of nature that generate phenomena. The causal history of most designed events or objects form steps in a process that guides ID as a scientific investigation. The general causal history of design events can be clearly perceived through a schema.^[5]

• Prior dynamics is the first step in designing and involves the planning and formulation of an object or event. Investigating this “conceptualization” step can, not must, include the designer’s character, intent, motives, opportunity, requisite knowledge, identity, and quantifying the information involved in conceptualization and actualization.
• Application dynamics is the second step that entails the means and sequential events of actualizing the design. This examination, also known as “actualization,” includes looking at material and efficient causes, implemental options, and surrogate phenomena. Boundary conditions and constraints are also considered.
• Subsequent dynamics are how designed events or systems autonomously operate. This inquest, also known as “functionalization,” can take place in many ways. This could be a study of what happens within an individual designed entity (internal dynamics), among other designed and non-designed phenomena (external dynamics), and the entirety of nature (totality dynamics).

This schema allows intelligent design to generate theoretical models that allow for novel explanations, tests, and predictions. Each of these stages has the potential of utilizing Aristotle’s final and formal causes to enhance scientific investigation. An ID investigator can study any of these aspects, since ID does not necessarily have to ask specific questions in a particular order (more details on this permissive axiom later in this work).

ID-detection

While ID-theoretics seeks to understand intelligence and its observable effects in a general way, ID-detection is the derivation of systematic methods to make a reasonable inference that an object or event was designed - as opposed to having come into being purely by natural forces. Intelligent design first inquires how science can determine if specific physical phenomena in the natural world were designed by intelligence. This is accomplished by detecting the types of unique physical effects known to be produced by intelligent agents when they act.

The goal is to understand the relationship between intelligence and the physical world, and identify intelligent activity by observation and analysis of data. Where the causal history of a design event is known, there are certain characteristics and patterns that (while not necessarily present in all things made by intelligence) are never present in things that are observationally known to be the result of natural regularity or chance. This fact leads ID theorists to propose that science can observationally identify design, even if the causal history is unknown.

Simply stated, ID asks, “Can science detect if something was designed by intelligence?” ID researchers are compelled by physical evidence, seen through the application of inference, statistical probability, and logical premises that detecting design is a scientific possibility.

There are many conceivable ways this goal may be accomplished; yet all of them can be arranged into one of four approaches. The approaches are eliminative, comparative, an eliminative-comparative composite, and mind correlation.

Comparative approach

In a comparative approach, intelligent design employs induction that moves from knowledge that is most certain and proceeds into areas of knowledge that are less certain. First, intelligent design states that there are certain instances where phenomena are known with certitude to be the effects of intelligence. These have been referred to as signs of intelligence by theorists of ID. One example of these proposed signs are phenomena that contain the following attributes: functional information, information interpretation, and the functional application of that information within a context (e.g. a computer-controlled manufacturing facility.) Objects or events that have these features are inferred as designed.

Eliminative approach

The eliminative approach works with the three fundamental causes in the known universe: chance, natural regularity, and design. If an event or object cannot be attributed to either natural laws or chance, design is a reasonable conclusion based on logical elimination. An eliminative approach is typified by what William Dembski has called the Explanatory Filter, which operates by reference to these three fundamental causes.

• If an event is necessary based on natural law, then natural regularity is the reasonable explanation. If an event is not necessarily based on natural law, natural regularity is reasonably eliminated as an explanation.
• If an event has a significant likelihood of occurring, then chance is the reasonable explanation. If an event is extremely unlikely, chance is reasonably eliminated as a cause.
• If law and chance are reasonably eliminated, and a phenomenon exhibits specificity, design then becomes a sensible explanation.

(Refer to the first figure in the Appendix to see an illustration of the Explanatory Filter.)

Composite approach

A composite approach incorporates aspects of both the comparative and eliminative approaches. First, the phenomenon under study is compared with other intelligently designed phenomena in order to uncover signs of intelligence. Second, if signs of intelligence are present, those signs are eliminated as possibly designed by inferring ways that chance or natural regularity could reasonably account for them. If the signs could be reasonably accounted for by either chance or law, an inference to design is not warranted. If the signs could not be reasonably accounted for by either chance or law, an inference to design is warranted.

Mind correlativity

The fittingness of understanding that exists between mind and phenomena in the universe, seemingly making knowledge and science possible, is called mind correlativeness.^[6] The universe and much within it is ordered in a systematic way such that it is understandable (e.g. galaxies, solar systems, biological systems, geological systems, etc.). The human mind is ordered in such a way that it can understand these many systematic aspects of the universe. This fundamental correlation in nature between mind and phenomena is taken by some as another sign of intelligence, indicating that the cosmos is designed.

Specified Complexity

Detecting design is the project that mathematician, philosopher, and ID theoretician William Dembski has been most frequently engaged in. The strongest formulation of ID-detection, which has undergone the most research and scrutiny, is his formulation of Specified Complexity. Dembski’s formulations of Specified Complexity are a type of mathematical rendering of the eliminative approach discussed earlier.

Specified Complexity is a two-part criterion for objectively detecting the effects of certain types of intelligent activity without first hand evidence of the cause of the event in question. Specified Complexity can only be employed to analyze the significance of patterns found in nature. It consists of two important components, both of which are essential for inferring design reliably. The first is the criterion of specificity, which is a type of independent informational-functional pattern with low descriptive complexity. That is to say, the pattern can be summed up in a short narrative span. “Minimum description length” is another term for this concept. The second component is the criterion of complexity or improbability. This means the pattern must be hard to achieve by undirected material means, which is to say, highly improbable with respect to chance and necessity.^[7]

Irreducible Complexity

A special case of Specified Complexity is what Michael Behe has called Irreducible Complexity (sometimes abbreviated IC). In his book Darwin’s Black Box, Behe defines Irreducible Complexity as a characteristic of systems “wherein the removal of any one of the parts causes the system to effectively cease functioning.”^[8] What does this loss of function mean for biological adaptation? Further research into Irreducible Complexity could bring clarity to the nature of these biological structures.

According to William Dembski in his No Free Lunch, Irreducible Complexity is: “A system performing a given basic function is irreducibly complex if it includes a set of well-matched, mutually interacting, non-arbitrarily individuated parts such that each part in the set is indispensable to maintaining the system’s basic, and therefore original, function. The set of these indispensable parts is known as the irreducible core of the system.”^[9]

One of the most scientifically interesting aspects of IC is that it makes possible the reverse engineering of biochemical systems. Scott Minnich made this observation in a talk he delivered, and Fernando Castro-Chavez summarizes this feature as follows:

"because biological systems are Irreducibly Complex it is possible to learn about the function of its vital genes through deliberated inactivation of them (by using artificial mutations, deletions, insertions, translocations, etc.)"^[10]

Systems having distinct IC cores essentially makes much of applied genetics research possible, since these processes of deactivation allow for cataloging of specific genotype-phenotype relationships.

Other design indicators

While not having a great deal of research and scrutiny to their credit, concepts outlined by Del Ratzsch such as artifactuality, counterflow, contextuality, and artificiality have definite contributions to make to the sub-field of ID-detection.^[11] All of these design detection methods are rough-and-ready to be used as tools for ID research.

What ID-detection cannot do

Currently, methods of design detection have inherent limits, just like there are inherent limits on detecting any event of the past, including the action of the mutation-selection mechanism. These inherent limits seem theoretically insurmountable, without further knowledge of the causal history of the object or event under study.

• ID-detection methods are able to detect almost everything in the universe that is designed, but like any methodology in historical sciences, exceptions do exist.

• Anything designed to mimic natural regularity cannot be detected as designed, without particular knowledge of its causal history. Yet, this concern is belayed by reality, since intelligent agents rarely set out to imitate nature in an undetectable way. (That is to say, intelligence tends to act in accord with its nature, which virtually never produces features that are indistinguishable from the regular processes of blind, natural regularities.) Additionally, such imitations will not concern ID-detection and many of its applications within the ID-paradigmatic because the inability to detect design in certain special cases in no way negates the strong ability to detect ID in most other cases.

• ID-detection can identify that something is not designed with high reliability, but not with absolute reliability.

• This follows from the fact that intelligence rarely imitates nature, but natural regularity cannot imitate many of the unique abilities of intelligence. Nevertheless, science does not deal in absolutes; it only deals in provisional acceptance pending subsequent data. As a scientific undertaking, detection can only claim that based on reasonable and knowledgeable inferences, intelligence is the most likely cause. This is the nature of all historical sciences.

ID-theoretics, ID-detection, and the origin of life (OOL)

While some ID researchers are studying how design-theoretic premises relate to cosmology, information theory, neuroscience, artificial intelligence, etc., many ID researchers have honed in on the complexity found in biological organisms. This research area is by far the most contested application of ID. Specifically, some ID biologists are very interested in the origin of life (OOL), which is thought to have happened about 3.5 billion years ago. This is the point in time when life is thought to have developed on the earth by some unknown event or process. A brief investigation of the origin of life can draw out some of the subtleties involved with the design paradigm.

Looking at the evidence

Before proceeding, a brief discussion about evidence is appropriate. In discussions of the ID/evolution/creation issue, what qualifies as evidence and as a supported conclusion, must always be held to very close scrutiny. When considering evidence, always ask:

1. Does the conclusion have supporting evidence?
2. Is the conclusion rigorously defined?
3. Is the evidence rigorously detailed?
4. Does the evidence presented actually lead to the conclusion proposed?
5. How strongly is the conclusion supported by the evidence?

Always view the situation from both perspectives; conclusions backwards to evidence and evidence forward to conclusions. This can often reveal strengths and flaws in an argument.

Evidence and the origin of life

The OOL is typically assumed to be a synchronic (one-time) primordial event. Or, it is thought that life started, at most, as a series of highly unlikely events, with a very limited window, in the far distant past. One reason given for this assumption is that we do not currently see life emerging from non-life under any extant conditions, nor is there any evidence that this has happend in the proximate past.

There are several acute problems with the scientific study of the origin of life:

• Long ago -- The great temporal remoteness of the OOL makes it the type of phenomenon that cannot currently be studied empirically per se. For example, it is impossible to watch an abiogenic OOL event under a microscope. This means that the repeatability of the origin of life experiment is completely absent from the present investigation. That is to say, we have not been successful at repeating the origin of life in any given laboratory.
• Virtually instant -- All current evidence points to the conclusion that life arose very shortly after the earth became a suitable habitat for biological organisms. This observation makes an OOL scenario based on chance even less likely, since there would have been less "deep time" for possible trials and failures. This seems to further exacerbate the formidable probabilistic dilemmas that abiogenesis faces.
• Initial conditions -- Researchers have extremely little sure knowledge about the circumstances of the OOL, and neither do we currently have sufficient knowledge to replicate the environmental conditions of the OOL. What could qualify as a “good guess” about the conditions may include a wide variety of initial reactants and conditions.
• Products -- It is unclear what the resulting biochemical products of the OOL were, which brings into focus the ultimate problem: scientists do not actually know what we are looking for.^[12] We know we are looking for some type of transition from prebiotic materials into something like amino acids, metabolic pathways, or RNA, and up to something like a cell.

These difficulties exacerbate an already extremely difficult scientific question, since these weaknesses can theoretically allow for research goals as wide as the human mind can conceive. So, it is easy to see why there is such a furor of disagreement about how the OOL event happened and how it should be studied. This is probably one of the most problematic retrodictive undertakings in the history of science. Given the remoteness of the origin of life, and the fact that we do not actually know what we are looking for, the hypothesized event of atelic abiogenesis is not testable, it does not make predictions, it is not falsifiable, and it provides no physical mechanisms. Any predictions or mechanisms tested in a lab as part of OOL research are derived from chemical or physical properties or possible prebiotic phenomena. Yet, conclusions are drawn from what can be called educated guesses only with extreme generosity. ^[13]

The study of the OOL falls between two areas of scientific investigation. Principally, this investigation is based on what is called an “historical science” approach, and this approach is informed by using the “simple science” approach of physics and chemistry to appropriate facts and experiments for conclusions. Historical sciences compare competing hypotheses by determining the best explanation from available (indirect or direct) observations, measurements, evidence, knowledge, and reasoning. The hypothesis that gives the best explanation of the known facts is the explanation with the best scientific viability.

Current scientific explanations of the origin of life (OOL) offer an unknown process based on some unknown form of combinations of chance and necessity, which are thought to be both blind and purposeless. This view will here be called “atelic abiogenesis.” ID, on the other hand, proposes that biological organisms show the tell-tale signs of being the result of an intelligent and purposive process, and so offers “telic biogenesis” as an explanation. Telic biogenesis offers an unknown intelligence involved at the OOL, since known methods of design detection are not able to determine the identity of the proposed intelligence.

It is important to notice that both explanations have an obvious gap in explanation. Both invoke a cause that have big question marks over them, and both causes have yet to be empirically verified as the initiator of life. Let us investigate how the OOL is explained by telic biogenesis and atelic abiogenesis.

Investigating the origin of life

In order to explain the origin of life, one must explain the origin of the cell. What is a cell? The living cell is a machine that obeys all of the known laws of physics. Within it is functional information, molecular machines, and is itself a very complex information-bearing code-program controlled machine operating with nano-scale precision. A machine can generally be seen as an energy-redirection force-multiplier, made with material formed into independent boundary conditions to fulfill proximate purposes. No one has ever witnessed chance and necessity originate a self-replicating phenomenon utilizing energy-redirecting boundary conditions that fulfill proximate purposes, and there is no observable evidence that this is the case.

In the mind of an ID theorist, a property of all machines is that they accomplish tasks that would otherwise be highly improbable. This is why we have not made machines that help objects fall to the ground or help salt dissolve in water. Unless, of course, making such a machine would fulfill our purposes, but not nature’s. For ID, a machine is likened to be a physical representation of purpose.

Another dimension to this dialog is innovation and problem-solving. Our knowledge of nature and living things shows us that innovation and problem-solving are realities. Within living organisms, we see the complex interaction and interdependence of parts working together for the apparent purposes of sustaining and reproducing themselves, oftentimes requiring innovation and problem-solving. Science knows, in fact, that there are entities which appear to be purpose-driven; biological organisms.

We do not see minerals and polymers organizing themselves into a car, or even a machine as simple as scissors. There are no blind physical properties of any element itself that would cause it to form into the shape of scissors, or any other proximate purposive force-multiplier. It is even more remote to think that the blind physical and chemical activity of elements could yield force-boundary multiplying complexes based on coding dependent templates. These types of machines and information are precisely what we see in living things, therefore chance and necessity do not suffice as explanations.

All machines operating under code-program control, where the origin can be determined, were caused by intelligent agency. Indeed, all functional information and all machines are only known to result from intelligence. No machine, whose origin is known, has ever been observed to self-assemble without the involvement of intelligent agency. Atelic abiogenesis, which is the currently accepted view of the OOL research community, assumes that science can only have recourse to the non-evidential explanation of blind and purposeless natural regularity. According to scientific authorities, intelligent causes can never be invoked as an explanation for the OOL. This conclusion is said to be based on methodological naturalism. Methodological naturalism means that science holds a strict rule that only natural causes are invoked to explain natural phenomena.

Unintelligent processes are not known to cause inanimate raw materials to self-assemble into machines running under coded-program control. Two types of machines like this are known to exist. Technological machines created by intelligent human agency and biological machines resulting from an unknown cause. So there is one solitary cause that is proven to be capable of creating self-assembling machines: intelligent agency. Despite this evidence-based fact, the only cause that has been proven capable of yielding self-assembling machines cannot be mentioned as a scientific possibility. In place of an evidence-based proposal, a completely unproven, entirely speculative proposal, with no direct empirical evidence of any kind to support it, is granted exclusivity as a scientific explanation.

How can this be? Scientific authorities propose that chance and necessity are the only possible scientific explanation for the appearance of self-assembling nanometer scale protein factories under information-coded-program control. Given a reasonable assessment, the amazing feat of self-assembly, without guidance of any kind, should be in grave doubt. It should remain in doubt until this extraordinary claim, which is beyond human experience, can be backed up with some kind of physical evidence. To ask that such self-assembly be taken as an axiom without evidence of how it happened is unreasonable. When direct evidence is not available, what matches experience and previous knowledge should be considered when assessing the claims of competing explanatory hypotheses. The burden of evidence is on the skeptic of telic biogenesis to show how we can get such strong appearance of purpose without there actually being any intelligent agency involved. A scientist should presume what experience, evidence, and reason demand. The machinery of life should be presumed to require intelligent agency until substantial evidence to the contrary is provided.

In proper adjudication of the evidence, the a priori dismissal of intelligent causes based on a metaphysical assumption is a red herring. The universe is an enormously large and old phenomenon. Intelligent agency capable of genetic engineering is already a proven phenomenon within it (e.g. humans). The observations outlined here all make reasonable the proposition that telic biogenesis is a viable explanation. Intelligent design is a common sense conclusion, and all of the observable evidence and available knowledge point toward this explanation. Scientists should not insist that this conclusion is wrong because it is so obvious.

Phenomena which appear designed may or may not actually be designed. Science does not know for sure yet. If they were designed, there will not be an adequate atelic explanation, and a gap in our knowledge of how chance and necessity produced life will persist. Not because we are ignorant of reality, but because biotic reality did not result from an atelic process. Scientists should not insist that there is an unnecessary gap in our understanding simply because design offers the better explanation that fits all observable evidence.

To recap a couple of the salient points, remember that both explanations have an obvious gap. The two opposing arguments are not weighed according to logic or evidence, but solely on a philosophical premise of methodological naturalism. If by “natural” we mean “something that we can directly observe,” this requirement would eliminate much of modern science, including OOL research into atelic abiogenesis. Since current knowledge of the visible world cannot tell the identity of the particular cause invoked by ID, it may or may not be natural, depending on how we define the term “natural.” If by “natural” we do, in fact, mean, “something that has effects we can directly observe” then science is opened to considering the OOL as a design event, and even more so than atelic abiogenesis. Design is something we witness on a daily basis and can be distinguished from natural regularity.

Methodological naturalism is a “demarcation argument” which disqualifies ID as a science before an investigation begins. Other demarcation arguments against ID are that it is not testable, it does not make predictions, it is not falsifiable, and it provides no physical mechanisms. An interesting thing to note about all of these arguments used against ID, again, is that they are not based on logic or evidence. It is also revealing to note that since the cause of atelic abiogenesis is completely unknown, neither can this atelic cause be said to qualify under these demarcations. An unknown cause cannot be tested, falsified, generate predictions, or provide a mechanism. Intelligent design is a known cause in the universe. ID proposes a claim that is connected to an absolute and incontrovertible fact, whereas the atelic premises have no connection to any facts. Instead, atelic abiogenesis is sheltered from physical evidence and scrutiny by a metaphysical axiom.^[14]

ID-input

ID-input deals with how a designed event or object is affected by subsequent modification, especially by an intelligent agent (e.g. certain copyright infringements, computer programming language manipulation, genetic engineering). There are three principle aspects of how the sub-field of ID-input investigates natural phenomena. First, ID-input considers how chance and natural regularity could modify a preexisting design. Second, design constraints are considered, which ways that intelligent agents can and cannot modify or add to the existing states of a previously designed phenomenon. Third, ID-input examines how receptive a previously designed phenomenon is to modification or the introduction of new information/structures. This sub-field has also been referred to as design receptivity, design input, and information receptivity. This sub-field of ID has a great amount of potential for future commercial, criminal justice, and judicial application.

ID-innovation detection

Innovation detection is the search for evidence of ID-input subsequent to the origin of a preexisting designed object or event. This sub-field can become a big player in commercial and technological applications of intelligent design. A conceptually related detection method is already being used by Genetic ID Incorporated.^[15]

ID-method detection

Method detection is the investigation and identification of what type of process was used to implement a design. While not mechanistic or deterministic in the way that many other scientific predictions have been offered, this investigation of method that can yield predictions for intelligent design. The inherent dynamics of ID-investigatives can be used to generate hypotheses and testable proposals. ID-conceptualization, ID-actualization, and ID-resultants, and their correlates discussed earlier, constitute an investigative matrix that can be used in scientific research.

ID-informatics

In the area where intelligent design overlaps with information theory, ID has produced what many think will become a wellspring of scientific and technological inspiration. William Dembski’s informational formulations are already being used as a basis for a metric of artificial intelligence and robotics applications. This research utilizes William Dembski’s understanding of Specified Complexity and puts it to practical use as a Native Intelligence Metric (NIM).^[16]

ID-metrics

The sub-field of ID-metrics is concerned with developing standards of scientific measurement from design-theoretic research applications:

• Complex Specified Information (CSI), being developed by William Dembski, is an informational concept based on Specified Complexity, mentioned in the section on ID-detection.
• Ontogenetic depth is being explored as a metric for the distance between a single-celled state (a gamete) and an adult animal (metazoan) capable of reproduction (producing other viable gametes). This distance is explored in terms of cell division and replicational differentiation.^[17]
• Habitability and measurability as planetary metrics, and indices that analyze the interaction between this pair of features, is a potential future astrobiological application from the Privileged Planet hypothesis of Gonzalez and Richards.^[18]
• Constrained optimization as a metric for gauging the effectiveness of designs, could also be used for deriving understandings of design limitations and purposes.
• Hierarchical evolution metrics are needed in order to clarify our understanding of designed systems and their development, e.g. TRIZ.
• Quantifying the induction between engineered systems and biological systems.
• Quantifying the induction between engineered systems and cosmological systems.

ID-heuristics

ID-heuristics is a principle portion of ID’s contribution to the general domain of science. ID-theoretics implies immediate research connections between many of the sciences, including (but not limited to) cosmology, computer science, engineering, biology, geology, and forensics. Heuristically, ID can be considered a hypothetical research network interconnecting the many scientific fields related to designs, planning, and teleology.

ID-theoretics, by its fundamental claims of likenesses between phenomena, explicitly contends it has the ability to develop a conceptual research-generating program, presented here as “ID-heuristics.” This “conceptual machine” interrelates current science with ID-theoretic concepts, and derives how they can work together in such a way that ID-heuristics could be a mass-production research factory. Current science here means facts, ideas, models, hypotheses, theories, techniques, and methodologies currently used in the scientific and applied science disciplines.

An important area under the ID-heuristics sub-field is ID-axiomatics. ID-axiomatics are the “rules of thumb” to be employed by ID researchers. Establishing the rules (heuristics and axiomatics) for the ID-paradigmatic could be difficult, and the second part of this work will address these.

Perhaps equally as important as the radically different scientific view on nature brought by ID-theoretics is our ability to look at current knowledge and see how it would relate to this new view using a heuristic framework. An example of this research method is what Stephen Meyer exacted when he elucidated a new way of studying biological systematics and taxonomy through a design framework.^[19] Another example is the research of Christopher Langan into the Cognitive-Theoretic Model of cosmology and Reality Theory.^[20]

ID-synergistics

All divisions of the ID-paradigmatic have the potential of conceptually reseeding and refeeding themselves and each other. Informational and biological advances in our own knowledge and technology brought about by ID will enhance our ability to detect design and apply ID premises to other fields of science. The generation of new ideas by ID-theoretics and ID-heuristics, and the resulting conceptual frameworks for a field, will cast light into various scientific fields by the synergistical relationship among the other sub-fields under the ID-paradigmatic. This dynamism will bring new scientific insights. Synergistic aspects of ID premises can be clearly seen by anyone who is actually “looking under the hood” of the ID-paradigmatic.

Principle areas of theoretical research needed are:

...undertake a reinterpretation of current knowledge and data

...formulate methods for reinterpretation

...synthesize ways to test intelligent design

...develop means of falsifying intelligent design

...cultivate means of verifying intelligent design

...brainstorm many new investigative questions

...derive frameworks to foster new investigative questions

...foster ways intelligent design yields predictive statements

...advance the ways intelligent design provides explanatory power

The above list will be addressed with an ever-increasing effectiveness as ID-synergistics take their course.

It is worth noting that in at least one case this synergistic relationship has already brought utility. The fact that William Dembski’s informational formulations involved in design detection are being used as a basis for an artificial intelligence metric is very enlightening on this point. Dembski himself sees the inherent potential of ID to work synergistically, and he thought it possible that modified versions of his formulations could be used to gauge the extent of intelligence from the specificational-informational qualities of a design. So, here we have a synergistic result of ID-theoretics, ID-heuristics, ID-detection, and current technological research. This is one cue that ID can function synergistically in a repeatable fashion.

ID-empirics

Applying the ID-paradigmatic to empirical science is an undertaking that is already in place. ID-detection and ID-innovation detection are by definition empirical applications of ID-theoretics, since they are an investigation of observable phenomena in nature. Privileged Planet research, especially Guillermo Gonzalez’s use of this hypothesis as an ID-heuristic, has generated many empirical applications for his research. Guillermo Gonzalez’s heuristic use of the Privileged Planet hypothesis may hold the astrobiological key to solving the origin of life problem by means of lunar research proposals.^[21]

A research area under ID-empirics is ID-biotics. This is the empirical study of biological organisms and cellular structures with ID-paradigmatic premises. Irreducible Complexity, formulated by Michael Behe, is thought to be the type of concept that can spawn a myriad of research applications for biology.^[22] As Jonathan Wells studies the role and cellular function of centrioles, he has employed an ad hoc ID-heuristic.^[23] Ralph Seelke and John Sanford are testing the limits of evolution by studying the relationship among the phenomena of mutagenesis and morphogenesis.^[24] Scott Minnich uses an ad hoc ID-heuristic to develop reverse engineering applications in genetics and microbiology.^[25] Protein evolution is being investigated by Michael Behe and David Snoke in the context of ID-paradigmatic principles.^[26] Neuroscience and the anatomical aspects of blood flow to the brain have also been empirically investigated by utilizing ID-paradigmatic premises.^[27] Karl D. Stephan and other ID theorists are studying evolutionary algorithms and how they relate to real populations in nature.^[28]

In application to biological sciences, ID uses observable evidence, and the scientific principles of causality (cause and effect) and uniformity. When applying the design paradigm to biology, it is observed that all living cells necessarily utilize the functional information found in DNA.

Considering the principle of causality ID asks, “What is the cause of functional information?” In all cases where we know the source of functional information, it always originates from an intelligent cause. Additionally, there are no verified cases of functional information arising by chance or by non-intelligent natural processes, nor by the cooperation of chance and necessity.

Employing the principle of uniformity, ID proposes that all functional information uniformly originates from intelligence, even the functional information of DNA. Like any other truly scientific endeavor, ID proceeds from current verified knowledge into new knowledge. To speculate or accept a non-intelligent source for the functional information of DNA is to deny the verified scientific evidence.

Also, one observes that all living cells necessarily utilize biomolecular machines. These are protein machines that do many tasks within the cell, including helping make other proteins, carrying messages between parts of the cell, folding proteins into functional shapes, and transporting cellular parts. The Oxford English Dictionary defines a machine as “an apparatus using mechanical power and having several parts, each with a definite function and together performing a particular task.”

Considering the principle of causality ID asks, “What is the cause of functional machines?” In all cases where we know the source of a functional machine, it always originates from an intelligent cause. Additionally, there are no verified cases of functional machines arising by chance or by non-intelligent natural processes, nor by the cooperation of chance and necessity.

Employing the principle of uniformity, ID proposes that all functional machines uniformly originate from intelligence, even the functional machines in the cell. Like any other truly scientific endeavor, ID proceeds from current verified knowledge into new knowledge. To speculate or accept a non-intelligent source for functional machines in the cell is to deny the verified scientific evidence.

Intelligent design then asks what types of new data, concepts, and experiments result from proposing that intelligence is the source of functional information and functional machines.

Of special note under ID-biotics is its conceptual joining with certain aspects of ID-theoretics and ID-technics. The explicit connection in ID-theoretics between biological technologies and human technologies immediately leads to biomimetics, which asks how we can emulate natural structures and even whole organisms in our artificial human technology. Non-ID scientists are already exploring this connection, yet with conceptual handicaps that the ID-paradigmatic will resolve through its robust heuristic and synergistic aspects.

Another interesting research area falling under ID-biotics is synthetic biology, or “artificial life.” Artificial intelligence, synthetic genes, man-made cells, de novo protein design, and artificial biomolecular machines. Scientists are currently researching how to write an artificial genetic code and are attempting to “create life from scratch.”^[29]

ID-technics

The cooperation of ID-theoretics, ID-heuristics, and ID-synergistics will be of great benefit to the applied sciences and technological development in the ID-paradigmatic. Forrest M. Mims III is putting the design paradigm to work in the field and in the real world. His current research focuses on the effects of ultraviolet light on microorganisms, and he has used design-based thought to derive new hypotheses about environmental effects on viruses and bacteria.^[30] It is worth mentioning here that Dembski’s informational formulations are being used as a metric for robotics and artificial intelligence. More use of ID-paradigmatic research products in technological development is to be expected. The explicit connection in ID-theoretics between biological technologies and human technologies logically leads ID researchers into the fields of biomimetics, biotechnology, and nanotechnology.

ID-programmatics

The sub-field of intelligent design that provides general frameworks for undertaking scientific research is ID-programmatics. A research program will typically give unique research goals and methods of meeting those goals. The most notable program is the research structure being continually developed by the Discovery Institute,^[31] which is mostly based on the concepts of Specified Complexity of William Dembski and Irreducible Complexity of Michael Behe. Del Ratzsch has proposed research views based on realism (or anti-realism), instrumentalism, and heuristics that he termed, “methodological designism.” ^[32] Robin Collins has proposed a research program wherein intelligent design is generally taken as a metascientific perspective, with individual proposals that are scientifically tractable.^[33] Stephen Griffith has proposed a research program that would strengthen the ID-paradigmatic by a goal-oriented exploration of mind/intelligence and how it affects the physical world.^[34] An ID-heuristics framework has been proposed at ResearchID.org. Christopher Langan has proposed a Cognitive-Theoretic Model of cosmology and Reality Theory that has the potential of developing a unique ID research program.^[35] Other research programs have been proposed as well. ^[36]

ID-paradigmatic

All of the sub-fields presented here represent the parts of the ID-paradigmatic. Since the ID-paradigmatic is a conceptual/theoretic edifice, it is significant that this whole is not the sum of its parts since many more sub-fields of the paradigm are still latent, waiting to be uncovered and explored. Given the breadth of this concept, more can be expected from the ID-paradigmatic. The presence of “designedness” in nature and in human technology indicates an emerging research view that is already bringing innovation and insight to science and technology, and is sure to produce more in the future.

Part II: ID-Heuristics

Proposals For Procedural Scientific Heuristics Resulting
From This Synthesis of the ID-paradigmatic

Research motivation

Many scientists and researchers see intelligent design as the key to opening up fresh insights into the physical, special, and applied sciences. The new ways of approaching scientific questions that the ID-paradigmatic brings indeed reveals previously unknown concepts. For these new concepts to receive a hearing, they must give succinct reasons. These reasons must be scientific, verifiable, and bring innovative applications to science and technology.

Inquisitiveness and curiosity about nature are the primary motivators for the development of ID-heuristics. Two hypothetical questions are driving this curiosity. “Is it possible to somehow derive new scientific data by hypothetically assuming that phenomena in the universe that appear teleological are teleological?” Also, “What would it mean for science if hypothetically assuming teleology was able to generate new useful research and technological applications?” These questions have given rise to new heuristic concepts for ID researchers.

With a very tight initial focus on ID-detection by theorists and researchers, there has been a stream of research applications of intelligent design, but ID-theoretics suggests much stronger results are possible. This fact brings clear questions: Where does intelligent design go from here? How can intelligent design become a much more robust springboard for scientific research? Detection will only help the ID-paradigmatic if it can yield new scientific research applications and help develop a means to methodically apply ID-theoretic premises in a heuristic framework.

ID-heuristics is the application of ID-theoretic premises to observed phenomena. ID-heuristics is about developing bases from which to proceed into developing research applications of ID in as many fields of science and scholarship as possible. Dembski and others have proposed questions ID researchers can put to nature, and seek out the answers to the questions within nature. What are the cues that led Dembski and others into the research proposals they present?

Asking these questions is like peering into the interior mental dynamics of an effective ID researcher. You might say this present work is an “under the hood” inspection of research previously proposed by ID theorists, including the development of a sound basis for researchers to proceed tentatively into a scientific investigation utilizing intelligent design, as well as developing postulates and foundations of an ID-heuristics program to guide investigators into new research applications in many fields.

What is heuristics?

Heuristics is the study of problem-solving techniques in which the most appropriate solution is selected using rules.^[37] William Whewell, considered the father of geology, describes heuristics as the “art of discovery.” As a problem-solving discipline, heuristics seeks knowledge of methods or strategies for solving problems efficiently and effectively. This study can be employed in planning the steps to solve a complex problem for which no formula or solution exists, but a heuristic can also provide a new solution to an old problem. Plans to modify a currently functioning system can be developed heuristically to improve performance. The set of rules utilized by heuristics to guide one in the direction of probable solutions can be derived from experimentation, experience, or prior knowledge. The most important aspect of heuristics is its ability to reduce the number of possible choices by eliminating the time spent considering the obvious “bad” choices. All of science, including the scientific method, can be seen as a highly developed heuristic.

Scientific problem solving, invention, nanotechnology, computer science, psychology, and sociological statistics all draw from heuristics. In fact, every academic discipline and scientific field employs some form of implicit or explicit heuristics. Logic can also be seen as a type of epistemic heuristic.

Heuristics can be both a science and an art. When used in the process of discovery, it takes on more of an art form. This is true for an effort in which serendipity has a major role. Familiarity can help, but ultimately achievement is determined by the circumstances that are beyond knowledge or experience. Methods used to discover a potential fossil bed is a heuristic. In addition, finding likely locations for discovering unclassified species can employ a heuristic that tries to maximize serendipity. When exercised in the effort to invent, it can become more of a science. The engineering developments of TRIZ and TIPS^[38] are examples of a guiding heuristic that functions in a scientific and methodical sense.

Heuristics is also the informal, decision-based knowledge of an application area that constitutes the “rules of good judgment” in a field. Because of the difficulty of finding dependable criteria for statistical evidence, a heuristic is employed to ensure that research continues towards particular goals that are seen as fruitful. Heuristics can guide research in a scientific or academic subject, directing a researcher’s attention productively. Non-telic evolution can be seen as the current heuristic for biology. Additionally, heuristics is a means of producing new research by developing and applying new discoveries with problem-solving steps to old questions.

Challenges exist for using heuristics in scientific inquiry. The use of informal methods, rules of thumb, educated guessing, tricks, and iteration all have their own problems. Some heuristic applications have more of a trial-and-error nature than a methodical one, sometimes making them unsuitable for exact sciences. This can be a disadvantage, but not always, since the scientific method itself is a type of trial-and-error process that is (ideally) self-correcting.

When properly understood, intelligent design is a unique scientific heuristic. Design-theoretic research is an inference from physical phenomena, evidence, and knowledge. Intelligent design is a powerful brainstorming tool for conceptualizing new research. There are great prospects for heuristics being beneficial to ID research. Refinements of heuristics could be a promising avenue for new design detection methods. Intelligent design hypotheses may also benefit from the practical nature of this subject area. Additionally, interdisciplinary fields have high potentiality for using heuristics to their advantage, and ID can vicariously benefit from this fact as well.

Internal framework of ID-heuristics

The internal framework of ID-heuristics is formed by aspects of the ID-paradigmatic, current science, research motivations, and research goals. Curiosity, insight, and persistence are the prerequisites for utilizing the framework, since applying a new paradigm and to research can be daunting.

Aristotle’s classical model of natural science serves as part of the framework. The four causes of Aristotle provide the structure of inquiry. Towards the goal of developing teleological research, final and formal causes are reincorporated into science, along with the material and efficient causes currently employed by science. The Aristotelian aspects of our framework are the three domains understood today as the basic expressions of scientific knowledge, which are theoretical (theoria), empirical (praxis), and technological (techne). ID-heuristics operates within these three domains. The theoria of ID-heuristics is, appropriately enough, ID-theoretics. ID-empirics is the praxis and ID-technics is the techne.. Within ID-heuristics, the different sub-fields of the ID-paradigmatic can be conceptually related to one another and to the general scientific corpus of knowledge. Other aspects of the ID-paradigmatic and current science serve as conceptual gears that cooperate to generate specific applications to fulfill the goals. ID-synergistics serves as a dynamo to amplify the conceptual energy produced. (Refer to the second image of the Appendix to see an illustration of this framework.)

ID-heuristics and current science

The observant reader noticed that the framework of ID-heuristics utilizes the entire body of current scientific knowledge and thought. In order for ID-heuristics to work in concert with current science, research hypothetically ignores some of contemporary science’s non-telic aspects. The utility of dismissing some of these teleological taboos can be easily seen when considering such research as the study of blood flow to the human brain, which is studied with principles of engineering and technological concepts such as fluid dynamics. Ignorance and misunderstanding about this point has been a major conceptual obstacle for many critics of ID.

ID theorists have noted that utilizing design-theoretics does not take away any scientific gear in the researcher’s toolbox.^[39] ID only adds investigative power to scientific research, by allowing techniques like reverse engineering, coding analogies,^[40] machine analogies, nano-, macro-, and micro-engineering and design principles, to be a vibrant part of research, not an antithetical or accidental usage.

ID-heuristics is not a complete abandonment of reductive approaches. ID-heuristics can be used concurrently with reductive approaches. A particularly distinct aspect of ID heuristics will be the attainment of research methods that are teleological and emergently synthetic, and not simply reductive. ID researchers will not be intellectually chained by such reductive constraints to investigation.

The interconnection within current science among various fields and ID can manifest itself in several different ways. A design paradigm would fit into the web of academic and technological disciplines at various levels of conceptual association. These associations with ID could be conceptual or historical. Cooperation between these fields and ID could create heuristic synergy and develop new scientific and technological applications.

• Direct connections are methodological relations to intelligent design that is of an immediate and close quality (e.g. biology, cosmology, physics, engineering, biotechnology, nanotechnology, computer/information sciences).
• Proximate connections are shared between ID and disciplines that could share methodology in an indirect way (e.g. psychology, Artificial Intelligence [AI]).
• Related connections are shared between fields that could cooperate, yet are not conceptually related in methodology (e.g. organization theory).
• Remote connections are shared between ID and subjects that could relate only in an intersecting way (e.g. futures research).

Intelligent design as a conceptual framework realizes many other connections, either implicitly or explicitly. The ID-paradigmatic implies scientific and technological connections between all research applications examining the general phenomena of both mind (intelligence) and the effects of mind (designed phenomena). Psychology, neuroscience, philosophy of mind, sociology, and archeology have the potential of contributing and/or interacting with the ID-paradigmatic in a profound way. Applied sciences of almost every form stand to gain from the ID-paradigmatic. Engineering, technology, as well as many forms of industrial and commercial research conceptually relate to ID. The multitudinous forms of forensics, including criminal and civil applications interrelate with the ID-paradigmatic: fraud and tampering detection and prevention of all varieties, patent law, copyright law, intellectual property protection, securities investigation, commercial fraud investigation, data security, cybercrime investigation, insurance fraud investigation, cult investigation, bioterrorism investigation, and counterterrorism. All of these connections could become stronger or weaker, depending on actual changes in methodology and approach of each field.

ID-axiomatics

The ID-paradigmatic must be functionally interrelated with other fields of science in order to become productive in empirical and technological research. The idea of axioms, hypotheticals, and heuristics in modern science can function as guides for scientists to move towards new fruitful research utilizing different approaches to investigation. Design-theoretic research that continues to be useful and practicable as science needs these well-understood underpinnings and boundaries. ID-axiomatics is the sub-field that explores these rules and hypotheticals for ID-heuristics. Design axioms should be open enough to foster a wide range of research across the entire spectrum of science, yet not so wide to fall from relevance.

Types of ID-heuristics

The heuristics and axioms of ID-heuristics can be arranged into three categories. The classifications are:

• A permissive heuristic is established in order to point researchers in a fruitful direction through opening the ID-paradigmatic to new research areas.
• A restrictive heuristic is set up to guide ID researchers away from research pitfalls or areas that do not show promise of productive results.
• A productive heuristic impels research directly towards new and innovative applications of the ID-paradigmatic.

Fuller’s hypothetical

Permissive heuristic

Fuller’s hypothetical – Hypothetically viewing certain phenomena in the universe as designed, whether the researcher holds that the objects under study are actually designed or not, for the express purposes of deriving novel data, hypotheses, experiments, and technological applications.^[41]

This hypothetical serves as a pre-theoretical foundation for the scientific endeavor of ID-heuristics. Steve Fuller proposed this hypothetical as applicable to ID, and it is the quintessential statement of ID-heuristics. Thus, Fuller’s hypothetical can be generally understood as “The ID-heuristic.”

This heuristic is based upon the fact that one may think that intelligent design offers an empirically valid and constructive way of viewing nature and also hold that actual designing agents of nature do not exist. In philosophy of science, this is generally consistent with the anti-realist^[42] view of constructive empiricism.^[43]

What good is anti-realism to scientific research? While very counter-intuitive to our way of thinking, the application of mathematics in empirical research is an anti-realist position. Consider for example the number “one.” The number one is an idea, an abstract thought. It is a metaphysical reality, not an actual physical reality. No one can put the number one under a microscope. No one can go to the store and buy a “one.” The number one is a non-physical, mental concept that has no real physical existence independent of the thought. In this way, one can see that the use of mathematics in science is an anti-realist position.

If signs of intelligence are present in a phenomenon, ID and other design-based fields such as engineering can be useful in studying it, whether the researcher thinks it is intentionally designed or not. It is possible that, given our current knowledge of the way nature operates, some part of nature may be best explained and studied as resulting from intelligent causation but that in actuality, it was caused by yet unknown unintelligent mechanisms. So it is possible for a person to think that intelligent design offers the best current explanation but that unintelligent mechanisms are ultimately the true cause.

Question detachability

Permissive heuristic

Can the universe be studied using ID-theoretic premises without simultaneously bungling into metaphysics? Listening to critics of intelligent design, one may think it absolutely impossible. The identity of the designer within the framework of intelligent design is probably the most contested implied questions of ID research. (While any current evidence suggesting design in nature does not preclude the possibility of multiple designers, the singular form of ‘designer’ will be used here in order to conform to Occam’s Razor, which stipulates that entities should not be multiplied without warrant.) it is possible that there are multiple ) However, is there a specific feature of scientific inquiry that requires a researcher to have particular knowledge of observable or unobservable designer?

To understand how this question relates to science, the nature of scientific inquiry must be examined. When conducting scientific research, can one ask distinct questions about nature independently? Clearly the answer is yes. It is true that considering two questions simultaneously can give unique results. It is additionally true that one question, independent of other questions, can be asked, and has at least the possibility of its own unique answer. Science is a piece-by piece process, akin to putting together a jigsaw puzzle. One piece of a puzzle can be carefully examined before another. This detachable nature of inquiry is a logical assumption of science; otherwise, science would be a cacophony of competing Grand Unified Theories.

Design-centrism

Restrictive heuristic

Immediately proceeding from the question detachability heuristic is determining what questions about nature one is asking. Regarding the cause-and-effect relationship that ID implies, the intelligent design investigation has an axiomatic focus on the effects of intelligence (design) and any subsequent development of the design.^[44] This “design-centrism” heuristic of ID is based on compliance with an axiom that the researcher is not currently deriving scientific knowledge about the identity of the designer based on ID research.

ID-heuristics will be constrained by a tentative retrodictive ceiling that proceeds with an understanding that what is to be gleaned scientifically from design events is an investigation of what has happened on after the chronological origin of the event or process undergoing investigation. Summarily, this restriction states that ID is an investigation of natural phenomena “this side” of a design event. ID-heuristic premises do not seek to establish an “explanation dynamic” that probes the mind of the designer, but rather probes those patterns in nature that give the indication of design in order to derive novel scientific data, experiments, and research applications. This ceiling mirrors the empirical/explanatory usefulness of the Big Bang. ID-heuristics will be constrained by a tentative retrodictive ceiling that proceeds with an understanding that what is to be gleaned scientifically from design events is not an investigation of the nature or identity of the designer, or what was identified earlier in this work as prior dynamics.

This axiomatic rule is by no means absolute. Remember a heuristic is a rule of thumb, which is not a necessary restriction. Researching the effects of a cause can generate data about the cause. For example, if one can infer the designer, one can at least know that the designer designs things. However, the exact identity or nature of the designer does not necessarily follow from the effects.

Contrary to the claims of ID critics, the “design event” of ID is in no way examined differently from many explanations offered from the non-telic evolutionary explanation. Non-telic evolutionary explanations do not answer questions or provide evidence prior to abiogenesis, but merely assumes an inexplicable and completely unknown natural event at the beginning of life. Attempting to probe scientifically before the abiogenesis event wanders into the realm of unobservables where empirical tests of mutation, adaptation, selection, and genetic drift are impossible.

This is very similar to the initial and continuing studies surrounding the Big Bang,^[45] which only studies “this side” of the initial ‘bang’ event. Any investigation of the “other side” of the Big Bang is invoking what is currently unobservable, directly or indirectly.

Did investigative scientific questions concerning the Big Bang start with, ‘What was the cause of the Big Bang?’ No.

Where did the notion of the Big Bang start? It started with mathematical equations by Vesto Slipher and Howard Percy Robertson about red-shift, and these models were subsequently confirmed by the astronomer Edwin Hubble observing stellar phenomena in the present.

Did further investigative scientific questions concerning the Big Bang start with, ‘What was the cause of the Big Bang?’ No.

The first questions asked about the Big Bang were related to the question, ‘Why is this a reasonable assumption?’ An accumulation of mathematical, theoretical, and observational evidence surrounding the Big Bang proceeded.

In ID, the first investigative question is not ‘Can science identify the identity or nature of cause of the design?’ or ‘What is the designer?’ Properly, the first question is, ‘As a result of known empirical evidence, is it reasonable to assume design?’ If this be the case, what new questions can science ask about nature? ID was the result of an accumulation of mathematical, theoretical, and observational evidence regarding certain phenomena and patterns in nature that can now be seen as best explained by teleology. Not that they can currently be absolutely determined as teleological, but based on our knowledge, they are most fittingly explained by teleology. The reasonability of the design question is what William Dembski and most of the ID community have been intensely focused on, because they see current scientific evidence pointing to telic causation as a viable explanatory option in science.

Returning to our historical example, was a subsequent investigative question concerning the Big Bang, ‘What was the cause of the Big Bang?’ No.

Big Bang researchers asked, ‘What might one be able to find to confirm this Big Bang hypothesis?’ By reasoning and searching for other possible consequences of the Big Bang (e.g. cosmic background radiation), they were able to confirm these consequences through specific technological advancements. One such advance was the device created by Bell Labs for receiving and interpreting radio and microwave radiation, which confirmed the presence of a ubiquitous background radiation.

ID researchers have been investigating ‘What might one be able to find to confirm that design could be a successful approach to science?’ By reasoning and searching for other possible consequences of design in biology, ID researchers hope to confirm these consequences through specific conceptual and technological advancements. The discovery of Irreducible Complexity by Michael Behe is something to be found in nature that makes intelligent design a reasonable scientific assumption by which to proceed with research.

Asking about “pre-Bang” conditions attempts to make unobservables part of scientific inquiry. Asking about the nature and identity of the cause of design also attempts to make what is currently unobservable a part of scientific inquiry. Theoretical physics clearly investigates unobservables all of the time. Atomic theory, sub-atomic theory, anti-matter, dark matter, and dark energy are currently, or in the past had been considered, tentative unobservables. While asking about unobservables can be a part of a scientific investigation, these questions are beyond empirical science, and by no means do they have to be part of an investigation by any absolute rule of science.

If applied uniformly, this “unobservables” rule must also exclude from science certain elements implicitly related to “non-telic” evolutionary theory (e.g. the unobservable cause of abiogenesis), if science is to have such a rule.

The heuristic rules of question detachability and design-centrism for ID-heuristics dispenses with ultimate questions regarding the designer, like ‘what designed the designer?’ These axioms direct the researcher toward proximate explanations, not ultimate explanations, and make the ad infinitum argument irrelevant to ID-heuristics. This proximity puts the objection on par with such arguments against the Big Bang like the question of “What caused the Big Bang?” and, “What caused the cause of the Big Bang?” et cetera ad infinitum. As such, empirical science can leave these ultimate causal questions to the field of philosophy, metaphysics, or theoretical mathematics, since it is an unobservable, and not amenable to empirical investigation.

Can ID research proceed without knowledge of the designer? Given the detachable nature of scientific investigation, the clear answer is yes. Since ID is about an investigation of nature, plain and simple, research can proceed. Clearly, Einstein was not researching God by using his design axiom; he was studying the universe and phenomena within it. Utilizing question detachability and the design-centric approach, a researcher would be safe to proceed into investigating ID premises by asking the questions necessary to derive scientific insight about nature. While using the design-centric approach, information that can be derived about the putative designer can only be used if it brings benefit to whatever scientific research is underway.

Why is it necessary that certain questions be asked in a certain order? There is no such requirement. So the bottom line regarding scientific proscriptions is that it depends on what questions are being asked, how they are being asked, how they could be answered, and, are the same questions being asked across the spectrum of science? All these aspects of inquiry must point to nature; else one will be invoking unobservables. If a researcher invokes intelligence in a purely causal role in order to extrapolate the nature and identity of the designer, they are overstepping the heuristic limits of ID. Perhaps at some point in the future science will have greater knowledge and can undertake such an investigative task. For now, it is up to ID to investigate nature for signs of intelligence and their scientific applications, and not for the identity or nature of a putative designer.

Primacy heuristic

Productive heuristic Regarding scientific questions, there is a certain primacy of ID-heuristics in the ID-paradigmatic. One can abandon any ID-detection method, and opt for a different one or none. It is perfectly acceptable to abandon a particular ID-detection method for the sake of research vitality if at any point in research one thinks it expedient. If currently known detection methods inhibit scientific results, they can always be exchanged or abandoned. There are many different detection methods that ID-heuristics can proceed from. However, if this and other proposed forms of ID-heuristics prove to be duds, ID is likely to flounder as a scientific enterprise.

Scientific pragmatism

Permissive heuristic

ID-heuristics proposes that its scientific applications should be rejected or accepted based on observational usefulness, empirical practicality, or technological applicability, as opposed to metaphysical demarcations like absolute reductionism or methodological naturalism. The practicality of an ID perspective on many types of research is obvious to those open to new research perspectives.

Consider for a moment the field of biology, and its relationship to many of the technological and applied sciences. Bioinformatics, (especially genome and epigenome cataloging projects like those for E. coli, chimp, Neanderthal, and human genomes) biomimetics, biotechnology, nanotechnology, cybernetics, robotics, computer science, and the technological generation of artificial life including artificial genomes, artificial proteins, artificial cells, artificial organs, and artificial intelligence. All of these fields integrate, in a profound way, the technology of the biotic realm with the technology of the human realm. Part of the reason for this is, by definition, biomolecular machines and man-made machines are the same type of phenomenon. ^[46] Likewise, bioinformational-functional structures like DNA and the semantic codes of computational systems are by definition the same type of phenomena.

In addition to being hauntingly similar to man-made teleological technology, biological phenomena are compatible with computational analysis to an extreme degree. Computational, programmatic, and technological analyses of biological realities yield a cornucopia of scientific results. The cooperation among computational biologists, statisticians, mathematicians, computer scientists, engineers, and physicists shows that what is commonly known as "systems biology" is indeed a powerful scientific view for researching biology. Establishing interfaces between biological machines and human machines for computational analysis of biotic phenomena renders a technological methodology that is an apex of scientific efficiency and tractability. If the living cell can be technologically interfaced, mechanically understood, computationally quantized, electronically observed, predictably documented, rigorously calculated, reverse engineered, analyzed via informational dimensions, recognized, comprehended, understood, evaluated, theoretically explored, simulated, synthesized, imitated, emulated, and investigated in every aspect of its fundamental nature with function-informational and function-computational analysis, then is it a “bad argument” to say a scientist could study it axiomatically as a technological/teleological phenomena? Additionally, this investigative harmony between technological computation and biology is unique among all natural phenomena. There is a veritable “plug-and-play” dynamic between biological phenomena and human computational machines. This unique “hand-in-glove” fit of biology and computational-technological analysis is like no other aspect of the universe. Mathematics and computation indeed reveal much about physics and other sciences. Yet, there is no such mirror between human technology and other phenomena quite like biology. Nothing in the universe comes close. In the mind of an ID theorist, this techno-scientific fitness is an exemplary reason to utilize ID-heuristics.

The scientific pragmatism heuristic is a starting point for the "open philosophy of science" that ID theorists have mentioned. ID-heuristics operates on the principle that science is not an “all-or-none” proposition regarding non-telic methods of researching nature. That is to say, some claim that either everything in the universe is designed, or nothing is designed. ID theorists reject this view and accept that chance, necessity, and design are all parts of the scientific framework.

It is also claimed that in order for ID to become a regular part of science, teleology must show itself to be necessary for explanation.^[47] Teleological views are logically sound and scientifically consonant with the observable evidence. ID must show that it is a useful framework for exploring the universe and gaining knowledge about nature, not that teleology is necessary. In the history of science, teleological axioms have been indispensable in deriving new knowledge. If the researcher finds it expedient and fruitful to dismiss non-telic demarcations like methodological naturalism, then let it be so. New research cannot yield to axioms that under scrutiny reveal ideology, not practicality. Any researcher or theorist interested in utilizing ID-heuristics can leave methodological naturalism to the courts and education legalese. If the ID-paradigmatic continues to make headway in the empirical and technological areas of science, methodological naturalism (as a rhetorical tool to banish telic investigation) will become irrelevant to the ID-paradigmatic.

Scientific pluralism

Scientific pluralism is a related permissive heuristic that encourages new research approaches. While majority views may develop, minority views must always be welcome in the scientific arena of ideas. This is an important point for all concerned with ID's contribution to science: the intelligent design research community wants a seat at the table, not the whole table to itself. Any member of the ID community who wants ID to control the whole table should recognize that this would be a misstep of equal proportion to the bigotry that many ID researchers and theorists have experienced.

ID-detection heuristic

Restrictive heuristic

When considering ID-detection in the context of ID-heuristics, axiomatic dimensions of ID-detection can be seen as a productive heuristic. While both ID-detection and ID-heuristics can function independently, they can cooperate and yield useful results. Irreducible Complexity and Specified Complexity could serve to direct the researcher towards particular phenomena that would yield novel observations, data, and tests through ID-heuristics. To use a car analogy, a robust ID-heuristics approach would be the “engine” of this hypothetical ID research program, with design detection working more like the “tires” that can help research gain traction, and can be easily changed out.

Some phenomena that cannot be detected as designed can still benefit from ID heuristics. This shows further the primacy of the ID-heuristic over other sub-fields of the ID-paradigmatic. For example, applying a design detection method on the entire universe is a formidable task. Yet Einstein’s axiom mentioned earlier in this work, which operates conceptually as a pre-theoretic ad hoc ID-heuristic, was shown to have scientific merit when studying the laws and constants governing nature.

Giving up the Holy Grail of ID?

Design detection has been seen by some as a type of “Holy Grail” that can definitively show God has been at work in the universe. In a properly understood scientific context, design detection is not meant to be employed as if it can force all scientists to acquiesce to a conclusion of divine causation. Invoking causal explanations, especially mathematically, is an extremely difficult goal to accomplish. (If not downright impossible for biology, without more knowledge of the causal history of living things than science currently has.) On the contrary, in the hypothetical ID-heuristics scientific framework being constructed in this work, ID-detection can function as a type of cue for determining cases where the ID-paradigmatic may be applicable. To emphasize an earlier point, recall Fuller’s hypothetical which states that one does not even have to hold to the position that there is a designer in order to employ ID-heuristics.

The goal of convincing the scientific community that it is possible to detect whether a non-human intelligence has been involved in life’s history is beyond the reach of any known methodology. It is clear that William Dembski has generated top-notch research in design detection. Some who claim, ‘it just doesn’t work,’ should also say it is the most admirable attempt ever.^[48] A promising means of improving ID-detection will be addressed briefly.

Any scientist who does not want to see life as designed can muster a long line of argumentation to refute the idea. In order for ID-paradigmatic research programs to proceed, perhaps this “Holy Grail” of ID will have to be set on the back burner. The socio-political impact of giving up the “Holy Grail” of ID will make general perceptions about ID even more sobering than current disillusions (e.g. the fact that ID cannot identify the nature of the designer). This could be a very good consequence for ID as a scientific heuristic. It is clear that wide acceptance of this design-centric proposal among ID researchers would only strengthen two of the observations of the ID Effect.^[49]

Streamlining approaches

Exchanging the Grail for a Scientific Road Map
Some ID researchers may complain that the baby is being thrown out with the bath water: "But critics could say that neo-Darwinian mechanisms generate the appearance of design (designoids),^[50] and so ID-heuristics as presented here is compatible with neo-Darwinism." ID-heuristics may need to shed the “Holy Grail” goal to become a useful scientific heuristic. The currently unwarranted obsession that a few members of the ID community have with scientifically showing that a non-human intelligence has been involved in life’s history is side-tracking ID from generating research with the detection concepts that William Dembski, Michael Behe, and Del Ratzsch have already presented. One can be confident that Dembski and Behe’s detection methods can point science toward phenomena that can yield new empirical and positive knowledge by applying ID-heuristics to them.

Perhaps ID-heuristics should be based on a type of statistical coincidence, instead of claiming causal agency. Combined with the previous successes of pre-theoretic design heuristics, this would suffice as warrant for the researcher to proceed with ID-heuristics into scientific research.

Improving ID-detection

Briefly returning to the earlier point about improving design detection, as ID-paradigmatic research proceeds, these detection methods will be honed and made more effective. The best way to improve design detection methodology is to proceed with ID-paradigmatic research, and allow the ID-synergistics therein to do what they do best. The synergistic aspects of ID-heuristics will no doubt bring to light more useful information on the avoidance of false positives in ID-detection. The avoidance of false negatives, which is actually the larger statistical concern with Specified Complexity, could also be a benefit of ID-synergistics.

ID and evolution

ID-heuristics will be the best thing that ever happened to evolution. It will conceptually free researchers to hypothesize and explore the telic taboos of current evolutionary theory, including some of the stronger telic views in structuralism, holism, and hierarchical views of natural phenomena. Based on the history of science, exploration of the teleological aspects of biological function independent of the constraints of strict and absolute reductionism will certainly bring great utility to the biological sciences.

Examples in ID-heuristics

In the history of science, the design paradigm has brought utility in many ways. Presented here are a few examples.

Coding analogies

Discovering the function of the genetic code is one of the most important events to transpire in the biological sciences. For understanding the importance of heuristics and teleology, the use of coding analogies in genetics is one of the most noteworthy events in the history of science, not only biology.

The process of uncovering the function of the genetic code is instructive for a researcher in three ways, by showing that: 1) ID-heuristics were helpful for this great scientific discovery, 2) analogies that collapse into actuality might be revealing reality, and 3) defining science as 'methodological naturalism' can be a science-stopper.

ID-heuristics are helpful

John Maynard Smith explains the how the genetic code was investigated:

"The scientists who discovered the nature of the genetic code had coding analogy constantly in mind, as the vocabulary they used to describe their discoveries makes clear…. If, instead, the problem had been treated as one of the chemistry of protein-RNA interactions, we might still be waiting for an answer."^[57]

So, as the inner workings of the genetic code were elucidated in the 1950's and 1960's by researchers like Francis Crick, Har Gobind Khorana, Robert W. Holley, and Marshall Warren Nirenberg, each one of them were fixed on a strangely teleological idea: an informational code. They used the computational code-program function of human technology as a teleological heuristic for understanding genetic function.

Hubert Yockey explains why this heuristic usage in discovering the code and semantic context is significant. He also acknowledges the non-material properties of the genetic code that make it so much like a human language, and that make it so apparently teleological:

"the meaning, if any, of words, that is, a sequence of letters, is arbitrary. It is determined by the natural language and is not a property of the letters or their arrangement ... For example, "O singe fort!" has no meaning as a sentence in English, although each is an English word, yet in German it means, "O sing on!" and in French it means "O strong monkey". Like all messages, the life message is non-material but has an information content measurable in bits and bytes"^[58]

Analogy and reality

Yockey even goes so far as to say that this way of looking at the genetic code is not an analogy, but that the genetic code is a symbolic and semantic unity in the same ways that a human language is:

"It is important to understand that we are not reasoning by analogy. The sequence hypothesis [that the exact order of symbols records the information] applies directly to the protein and the genetic text as well as to written language and therefore the treatment is mathematically identical."^[59]

It is a fact that genetics being mathematically identical to teleological realities like human language has allowed bioinformatic