ID research questions

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Because intelligent design is in it's infancy, there are more questions than answers. Exploring these potential investigations, and theorizing answers, are good starting points for generating research applications of intelligent design.

Contents

Questions from Colin Thomas

Intelligibility, Internal Critique, External Critique, and Novel Testable Hypotheses.

"The ultimate goal of all of this debating is to set the stage philosophically and theoretically (i.e. scientifically) for an empirical science that embraces the possibility of design."

  • What direction should research go?
  • If you had a lab and were writing a grant proposal (to someone who accepted the validity of design hypotheses), what problem would you propose to work on and how?
  • What things do you assume to be true about origins, and how could you test them?
  • For those readers who are still in high school or college, think about the classes or the graduate programs and labs that will best allow you to hone the research skills necessary to investigate the hypotheses you generate. Is there an area of science you particularly love?
  • What are the tools of that discipline that can be used to investigate design hypotheses?

Mike Gene's questions

  • If [something] is designed, is anything else designed?
  • Does some coherent pattern emerge when scoring things as designed?
  • Does this pattern suggest further insights into the workings and evolution of life?
  • (What is) the extent of design (in biology, in cosmology)?

Questions from W.E. Löennig

"On the strictly scientific level the combination of stasis and ID does not mean the end of inquiry (as is sometimes objected), but the very beginning of entirely new research programmes. For several questions have to be thoroughly investigated before valid scientific inferences can be suggested. To name but a few:

  • (a) "The hypothetical irreducible complexity of biological systems and/or correlated subsystems has first to be fully established on the different functional levels, i.e. genetically, anatomically, and physiologically. Since there are hardly any entirely non-redundant systems in biology, the irreducibly complex core systems have to be discovered and scientifically be defined and analyzed on the levels just mentioned. Closely associated with that task is the problem of developing realistic models for the initial/primary biological boundary conditions for the origin of new putative irreducibly complex systems, i.e. for thoroughly delineating the gap between them and hypothetical evolutionary precursors. Dembski’s improbability calculation of of 10-234 for the origin of the bacterial flagellum quoted above constitutes nothing but a first potentially falsifiable hypothesis in that research programme [7, 64].
  • (b) "Granted that such systems can be established, the correlation between the organism/species and its different environmental conditions have to be carefully studied pertaining the question, to what extent a species can relinquish certain subsystems without selective disadvantages under special circumstances. Although a subsystem could be irreducibly complex as such, some organisms might florish without it (the topic of regressive evolution holds a large series of instructive examples for this question) [46, 53, 63]. Problem (b) is intimately connected with the question for the boundaries of morphological variation of functional phenotypes [53, 55, 56]. In simple terms, a part of the ID research programme could thus be put: find the boundaries of functional phenotypic and physiological variation under different realistic environmental conditions.
  • (c)"Specified complexity is not necessarily irreducible. So, what could be the molecular connection/relation between specified complexity ‘only’ and the phenotypic constancy found in most of the higher systematic categories of living organisms? Although it seems that many gene functions specifying constant generic and higher systematic characters are somehow (and this ‘somehow’ is a research programme of its own) integrated in a correlated web of interdependent cascades in Behe’s sense, nevertheless some parts appear to be reducible in the sense given in paragraphs (b) and (e), and yet might display marks of specified complexity.
  • (d) "There appear to be many ornamental and even luxurious structures in the plant and animal kingdoms, structures that – from a purely functional point of view – do not seem to be absolutely necessary, to say the least. For instance, in terms of population density, reproductive success, and geographical distribution, the house sparrow (Passer domesticus) is much more successful than the peacock (Pavo cristatus), whose males display the ingenious beauty of its fanned tail to perform courtship display and mate with a female – yet often also inviting a tiger for an easy prey and meal. In the plant kingdom the orchid family is one of several groups providing a range of further intricate ornamental as well as functional structures (e.g. the extreme examples of the reproductive organs of Coryanthes and Catasetum, which have posed enormous problems for gradualism [57]), whilst most plant species survive – again often much more successfully in the terms just mentioned above – by much simpler devices. Even independently of the fact that the often quoted answer of sexual selection for the origin of the peacock’s tail (and similar examples) in itself poses a series of further unsolved problems [53] and, what is more, can hardly be applied to plants, the ensuing questions have to be investigated: to what extend can specified and irreducible complexity be detected on the genetic, anatomical, and physiological levels of such more or less selectionally ‘neutral’ or even hypertrophic organismic structures, too, and can this research programme provide scientifically more realistic answers than those given so far?
  • (e) "Also, there exist many constant features delineating morphological species and genera from each other that are probably due to further factors than specified and irreducible complexity. For example, features due to losses of more or less redundant gene functions [63] affecting morphological features, but with a very low probability to revert or being counteracted by compensating mutations in other genes (modifiers), can be constant for all the time a species survives. Let’s have a look at an event, which has repeatetly occurred in wild as well as in cultivated species: originally red flowering plant species have irreversibly lost their ability to generate anthocyanin and these species might produce white flowers almost forever. Other possibilities to generate rather stable features by mutations include buffering gene functions by gene duplications and polyploidy. On the other hand, mutations in essential gene functions involved in the formation of species- or genera-specific structures – functions, which were originally buffered by accessory redundant genes – could become regularly lethal after mutational loss of that redundancy.
  • (f) "There are some indications that at least a part of biodiversity is, so to speak, predestined by the constitution of the genome and its mechanisms, possibilities, and limits to generate functional DNA-variations, including preferential insertions of transposons of an initial line or species [64]. Assuming an original vast genetic potential for functional morphologic deviations – to what extend is specified and irreducible complexity relevant for that originally purely potential part of genetic variation realized in time and space of the history of a genus? [53] Moreover, several transposon specialists have, in fact, postulated rapid species formations by transposable elements (thus we are coming back to the question posed at the end of the introduction): concurring with McClintock [69], Syvanen [87] stated: "I believe that transposons have the potential to induce highly complex changes in a single event". Also, Shapiro [79] is convinced that "there must exist mechanisms for largescale, rapid reorganisations of diverse sequence elements into new configurations" for the integrated mosaic genome to make evolutionary sense. However, to date hardly any positive experimental evidence can be cited for this view [46, 53, 64]. A research project testing the possibilities and limits of species formation by TEs could also include the issue of the evidence for specified and irreducible complexity on the DNA- and morphological levels, e.g. can TEs be key factors in releasing a dormant genetical potential possibly displaying the marks of ID – say a master regulator with a set of corresponding target genes – for abrupt morpho-species formations?
  • (g) "Another question that should be investigated is, to what extent the correlations between the genome and its cellular surroundings (cell organelles, membranes, cell walls, physiological cascades and their interrelationships) can be lighted up and explained by a research programme addressing particularly specified and irreducible complexities in this area. For the first steps into such a research programme, see Behe [5] and Lönnig [53]."

Research themes from William Dembski

1. Design Detection
Techniques, methods, and criteria of design detection are widely employed in various special sciences (like archeology, cryptography, and the Search for Extraterrestrial Intelligence or SETI). There's currently much discussion from all sides about the validity of detecting actual design in biology using Michael Behe's criterion of irreducible complexity or my criterion of specified complexity. Design theorists need to be at the center of this discussion.

2. Biological Information
Information, according to its Latin etymology, means to give shape or form to something. It's no exaggeration to say that the origin of life and its subsequent complexification constitutes an "information revolution" in the history of matter. Indeed, matter needs to be formed in very special ways to constitute life. What is the nature of biological information? How do function and fitness relate to it? What are the obstacles that face material mechanisms in attempting to generate biological information? Most importantly, what are the theoretical and empirical grounds for thinking that intelligence is indispensable to the origin of biological information? I've begun to address these problems in my book No Free Lunch, but much more work is needed here.

3. Minimal Complexity
Living things are complex systems that consist of complex subsystems that in turn consist of complex subsystems and so on until a level of organization is reached that is chemically simple (for instance, individual amino acids or nucleotide bases). How does pruning away the complexity of such systems affect their ability to perform some function or set of functions (most notably, keeping the organism alive and able to reproduce)? How much can the complexity be pruned down and still preserve function? Once a complexity barrier is reached below which function can no longer be preserved, could coevolution overcome that barrier by switching function? Are there systems that are not only minimally complex with respect to some function, but for which any reduction of complexity eliminates all possibility of biological function? Would such systems provide decisive confirmation of intelligent design?

4. Evolvability
Evolutionary biologists are in the business of drawing evolutionary connections between biological systems. This requires identifying biological systems, relating them according to some similarity metric, and then telling evolutionary stories that, as it were, connect the dots. Yet for large-scale evolutionary changes, these stories tend to be imaginative reconstructions with no firm evidential basis. This is certainly true of attempts to bridge major divisions in the fossil record. It is also true of molecular phylogenies. Evolutionary biology's preferred research strategy consists in taking distinct biological systems and trying to merge them. Intelligent design, by contrast, focuses on a different strategy, namely, taking individual biological systems and perturbing them to see how much the systems can evolve (with and without intelligence). Limitations on evolvability by material mechanisms constitute evidence for design.

5. The Principle of Methodological Engineering
The reason evolutionary biology has lost all sense of proportion about how much evolution is possible as a result of blind material mechanisms (like random variation and natural selection) is because it floats free of the science of engineering. At every crucial juncture where some major evolutionary transition needs to be accounted for, evolutionary biology invokes a designer-substitute (like natural selection, lateral gene transfer, or symbiogenesis) to do the necessary design work. Yet unlike the science of engineering, evolutionary biology does not actually perform the necessary design work or specify a detailed procedure by which it might be accomplished. Intelligent design, by contrast, takes what I call "methodological engineering" as a fundamental regulative principle for understanding biological systems. According to this principle, biological systems are to be understood as engineering systems. In consequence, their origin, construction, operation, break down, wearing out, repair, and above all history of modifications (both designed and accidental) are all to be understood in engineering terms. In the next ten years I foresee academic programs in biotic engineering supplanting academic programs in evolutionary biology.

6. Technological Evolution (TRIZ)
The only well-documented example we have of the evolution of complex multi-part integrated functional systems (like we see in biology) is the technological evolution of human inventions. In the second half of the twentieth century, Russian scientists and engineers studied hundreds of thousands of patents to determine how technologies evolve. They codified their findings in a theory to which they gave the acronym TRIZ, which in English translates to Theory of Inventive Problem Solving. The picture of technological evolution that emerges out of TRIZ maps amazingly well onto the history of life as we see it in the fossil record and includes the following:

(1) New technologies (cf. major groups like phyla and classes) emerge suddenly as the solution of an inventive problem, which requires a major conceptual leap (cf. design).
(2) Existing technologies (cf. species and genera) can, by contrast, be modified by trial and error tinkering (cf. Darwinian evolution), which amounts to solving a routine rather than an inventive problem. (The distinction between routine and inventive problems is central to TRIZ. In biology, irreducible complexity suggests one way of making the analytic cut between these types of problems. Are there other ways?)
(3) Technologies approach ideality and thereafter tend not change (cf. stasis);
(4) New technologies, by supplanting old technologies, can upset the ideality and stasis of the old technologies, thus forcing them to evolve in new directions (requiring the solution of new inventive problems, as in an arms race) or by driving them to extinction.

Mapping TRIZ onto biological evolution provides a potentially fruitful avenue of design-theoretic research that is entirely consonant with the principle of methodological engineering.

I need here to add a footnote about TRIZ. Most design critics, by conflating ID with creationism, see ID as committed to a designer who always designs from scratch and has to get everything right the first time. TRIZ, by contrast, bespeaks an evolutionary process that as much as possible takes advantage of existing designs but then at key moments requires a conceptual breakthrough to move the process of technological evolution along. On this view, the process of technological evolution is itself designed. What's more, within that process, designing intelligences interact with natural forces. Does this mean that designer(s) is/are making things up as they go along? Not necessarily. The conceptual breakthroughs needed to drive technological evolution can be programmed from the start. And what about suboptimal and dysteleological design? These can be explained in part as the result of natural forces subverting an original design plan. Teasing apart the effects of intelligence from natural forces thus becomes a key research question for a TRIZ approach to intelligent design.

7. Autonomy vs. Guidance
Many scientists worry that intelligent design attempts to usurp nature's autonomy. But that's not the case. Intelligent design is merely trying to restore a proper balance between nature's autonomy and teleologic guidance. Prior to the rise of modern science all the emphasis was on teleologic guidance (in the form of divine design). Now the pendulum has swung to the opposite extreme, and all the emphasis is on nature's autonomy (an absolute autonomy that excludes design). Might there not be a mid-point that properly respects both and in which design becomes empirically evident? The search for that mid-point needs always to be in the back of our minds as we engage in design-theoretic research. It's not all design or all nature but a synergy of the two. Unpacking that synergy is the ID research program in a nutshell.

8. Evolutionary Computation
Increasingly it is becoming evident that organisms employ evolutionary computation to solve many of the tasks of living. But does this show that organisms originate through some form of evolutionary computation (as through a Darwinian evolutionary process)? It seems that the immune system, for instance, is a general purpose genetic algorithm that targets an interloper, sets up a gradient that tracks the interloper, and then runs a genetic algorithm specifically adapted to that gradient whose output is a molecular assemblage that vanquishes the interloper. All of this sounds very high-tech and programmed. Are GPGAs (General Purpose Genetic Algorithms) like this actually designed or themselves the result of evolutionary computation. Evolutionary computation occurs in the behavioral repertoire of organisms but is also used to account for the origination of certain features of organisms. It would be helpful to explore the relationship between these two types of evolutionary computation as well as any design intrinsic to them. My work in chapter 4 of No Free Lunch lays out some of the theoretical groundwork here. Besides theoretical work in this area, we need a large contingent of ID computer programmers who can write and run computational simulations that investigate the scope and limits of evolutionary computation. One such simulation is the MESA program (Monotonic Evolutionary Simulation Algorithm) due to Micah Sparacio, John Bracht, and me. It is available on the ISCID website (http://www.iscid.org/ubbcgi/ultimatebb.cgi?ubb=get_topic;f=6;t=000054).

9. Understanding Discontinuity
Evolution is committed to continuity in a broad sense. Its main business is to connect dots. But for dots to be plausibly connected, they need to be reasonably close together. That's why the absence of transitional forms, gaps, and missing links or intermediates constitute a problem for evolution. To be sure, evolutionists do not regard the absence of intermediates as a problem in the bad sense. They regard such discontinuities not as challenges to their theory but as discontinuities that are only apparent and that will disappear once the missing intermediates are found. Consequently, whenever an intermediate is found, it is regarded as a triumph for evolutionary theory (witness the recent excitement over the Toumaï fossil find in Chad).

Evolutionary biology attempts to explain the absence of intermediates from an evolutionary path on the assumption that the intermediates did once exist. But now let’s turn the question around. Suppose that discontinuity is a fact not just about the history of life as we know it but about the history of life itselfin other words, the intermediates never existed. In that case, how did biological forms in all their vast complexity and diversity come about? In asking this question, let's hold off asking for the underlying cause or causes of biological complexity and diversity. Rather, let's merely ask what a video camera would see if it were scouring the past and recording key events in life’s history. There are exactly four possibilities:

(1) Nonbiogenic emergence. Organisms emerge without the direct causal agency of other organisms. In place of life begetting life, here we have nonlife begetting life.
(2) Generative transmutation. Organisms, in reproducing, produce offspring that are vastly different from themselves.
(3) Biogenic reinvention. Organisms reinvent themselves in midstream. At one moment they have certain morphological and genetic features, at the next they have a vastly different set of such features.
(4) Symbiogenic reorganization. Organisms emerge when different organisms from different species get together and reorganize themselves into a new organism.

None of these possibilities is out to lunch. Nonbiogenic emergence had to happen at least once, namely, at the origin of life. Symbiogenic reorganization has been Lynn Margulis's main focus of research, and there is increasing evidence for it. Biogenic reinvention (organisms changing in midstream) is also not that crazy when one considers the life cycles of certain organisms which from one stage to the next are completely unrecognizable (for example, the metamorphosis of the butterfly or, even more extremely, the various forms of the liver fluke). Finally generative transmutation suggests a programmed view of evolution, where, like a computer program that kicks in at a certain time (recall the Michelangelo virus that kicked in March 6th, 1993), organisms change in one generation. French paleontologist Anne Dambricourt has seriously argued for this view in respect to the emergence of Homo sapiens.

With regard to these four possibilities, the crucial question now is this: How does one make sense of these possibilities in light of intelligent design? Clearly, none of these possibilities makes sense without some directed coordination.

10. Steganography
Finally, we come to the research theme that I find most intriguing. Steganography, if you look in the dictionary, is an archaism that was subsequently replaced by the term "cryptography." Steganography literally means "covered writing." With the rise of digital computing, however, the term has taken on a new life. Steganography belongs to the field of digital data embedding technologies (DDET), which also include information hiding, steganalysis, watermarking, embedded data extraction, and digital data forensics. Steganography seeks efficient (that is, high data rate) and robust (that is, insensitive to common distortions) algorithms that can embed a high volume of hidden message bits within a cover message (typically imagery, video, or audio) without their presence being detected. Conversely, steganalysis seeks statistical tests that will detect the presence of steganography in a cover message.

Consider now the following possibility: What if organisms instantiate designs that have no functional significance but that nonetheless give biological investigators insight into functional aspects of organisms. Such second-order designs would serve essentially as an "operating manual," of no use to the organism as such but of use to scientists investigating the organism. Granted, this is a speculative possibility, but there are some preliminary results from the bioinformatics literature that bear it out in relation to the protein-folding problem (such second-order designs appear to be embedded not in a single genome but in a database of homologous genomes from related organisms).

While it makes perfect sense for a designer to throw in an "operating manual" (much as automobile manufacturers include operating manuals with the cars they make), this possibility makes no sense for blind material mechanisms, which cannot anticipate scientific investigators. Research in this area would consist in constructing statistical tests to detect such second-order designs (in other words, steganalysis). Should such second order designs be discovered, the next step would be to seek algorithms for embedding these second-order designs in the organisms. My suspicion is that biological systems do steganography much better than we, and that steganographers will learn a thing or two from biology -- though not because natural selection is so clever, but because the designer of these systems is so adept at steganography.

Such second-order steganography would, in my view, provide decisive confirmation for ID. Yet even if it doesn't pan out, first-order steganography (i.e., the embedding of functional information useful to the organism rather than to a scientific investigator) could also provide strong evidence for ID. For years now evolutionary biologists have told us that the bulk of genomes is junk and that this is due to the sloppiness of the evolutionary process. That is now changing. For instance, Amy Pasquenelli at UCSD, in commenting on long stretches of seemingly barren DNA sequences, asks us to "reconsider the contents of such junk DNA sequences in the light of recent reports that a new class of non-coding RNA genes are scattered, perhaps densely, throughout these animal genomes." ("MicroRNAs: Deviants no Longer." Trends in Genetics 18(4) (4 April 2002): 171-3.) ID theorists should be at the forefront in unpacking the information contained within biological systems. If these systems are designed, we can expect the information to be densely packed and multi-layered (save where natural forces have attenuated the information). Dense, multi-layered embedding of information is a prediction of ID.

Research questions from William Dembski

Here is a list of research questions that could use a bit of pondering as we empirically apply ID.

  • Detectability Problem -- Is an object designed? An affirmative answer to this question is needed before we can answer the remaining questions. The whole point of (2) and (3) was to make an affirmative answer possible.
  • Functionality Problem -- What is the designed object's function? This problem is separate from the detectability problem. For instance, archaeologists have discovered many tools which they recognize as tools but don't understand what their function is.
  • Transmission Problem -- What is the causal history of a designed object? Just as with Darwinism, intelligent design seeks historical narratives (though not the just-so stories of Darwinists).
  • Construction Problem -- How was the designed object constructed? Given enough information about the causal history of an object, this question may admit an answer.
  • Reverse-Engineering Problem -- In the absence of a reasonably detailed causal history, how could the object have come about?
  • Constraints Problem -- What are the constraints within which the designed object functions optimally?
  • Perturbation Problem -- How has the original design been modified and what factors have modified it? This requires an account of both the natural and the intelligent causes that have modified the object over its causal history.
  • Variability Problem -- What degree of perturbation allows continued functioning? Alternatively, what is the range of variability within which the designed object functions and outside of which it breaks down?
  • Restoration Problem -- Once perturbed, how can the original design be recovered? Art restorers, textual critics, and archaeologists know all about this.
  • Optimality Problem -- In what sense is the designed object optimal?
  • Separation of Causes Problem -- How does one tease apart the effects of intelligent causes from natural causes, both of which could have affected the object in question? For instance, a rusted old Cadillac exhibits the effects of both design and weathering?
  • Ethical Problem -- Is the design morally right?
  • Aesthetics Problem -- Is the design beautiful?
  • Intentionality Problem -- What was the intention of the designer in producing a given designed object?
  • Identity Problem -- Who is the designer?


Campana's investigation into Cosmic revolutions

What precipitated the advent of the complexity and information "revolutions" that have occured in the universe? How did these events originate and proceed? Can a design inference be applied to these events? (Everyone please keep in mind we are asking questions here, not providing answers. We are being scientific investigators.)
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