ID Predictions: Foundational principles underlying the predictions proposed by Jonathan M. and others.
|April 26, 2011||Posted by no-man under Intelligent Design, Science|
PART I: BASIC PREMISES
Many predictions of ID flow from two underlying hypotheses, both of which are open to scientific investigation and refutation. If you miss these, however, other ID predictions may not make sense, since many arise from them in an important way. It is my belief that much of the puzzlement regarding ID predictions results from not being familiar with these two often unspoken premises.
I consider the first of these to be a basic hypothesis of ID, which is so obvious to ID researchers that they often forget to make explicit mention of it. It is,
1. Creating* integrated, highly functional machines is a difficult task.
This statement seems obvious to many engineers and others who construct complex systems for a living. As an informal statement, it is fairly straightforward. Yet as stated, it is not mathematically precise, since I have not defined “integrated, highly functional machines” nor “difficult task.” ID researchers have long conducted research to define precisely what separates an integrated, highly functional system from one that is not, attempting to define these terms in a quantifiable way. It is a worthwhile research project and their efforts should be applauded, even if these same efforts have met with mixed success. I won’t argue here whether or not they have succeeded in their task, since most of us would agree that if anything represents an integrated, highly functional machine then surely biological forms do. We can also agree that simple things such as rocks and crystals do not. Where exactly the cutoff point lies on that continuum is open to investigation, but hopefully it is reasonable to agree that humans, nematodes, bacteria and butterflies belong to the group labeled “integrated and highly functional machines.”
Now, this hypothesis is contingent, not necessary, since it might have been the case that life (functional machines) could arise easily. Imagine a world where frogs form from mud, unassisted, and where cells coalesce from simple mixtures of amino acids and lipids. We are unaware of anything that logically prevents the laws of nature from being such that they would produce integrated, functional machines quickly, without intelligent guidance. Creating life could have been a simple task. We can imagine laws of nature that allow for life forms to quickly and abundantly self-organize before our eyes, in minutes, and can imagine every planet in the solar system being filled with an abundance of life forms, much like sci-fi novels of decades past envisioned, arising from natural laws acting on matter.
Yet, the universe is not like this. Creating life forms (or writing computer programs, for that matter) is a difficult task. The ratio of functional configurations to non-functional is miniscule. Before the advent of molecular biology, it was believed that life was simple in its constitution, cells being seen as homogeneous blobs of jelly-like protoplasm. If we believe that life forms are simple, then it becomes plausible that a series of random accidents could have stumbled upon life.
We have since learned that life forms are not simple, and creating them (or repairing them) is no simple task. Therefore, where unguided materialistic theories might have received great confirmation, they have instead run afoul of reality.
This basic hypothesis, confirmed by empirical science in the 20th century, underlies much ID thought. I cannot think of a single ID theorist who would disagree with it. If creating life forms were a simple enough task, it would be reasonable to expect unintelligent mechanisms to produce them given cosmic timescales. Conversely, the more difficult this task, then the less plausible unguided, mechanistic speculations on the origin of life become. The difficulty of the task is precisely what places it beyond the reach of unintelligent mechanisms, and leaves intelligent mechanism as the only remaining possibility, since “intelligent” and “unintelligent” are mutually exclusive and exhaustive, much like “red” and “not red” encompass all possibilities of color.
The second hypothesis, much like the first, is so obvious that it often fails to be mentioned explicitly. It is,
2. Intelligent agents have causal powers that unintelligent causes do not, at least on short enough timescales.
Who would argue with such a statement? Even ardent materialists, who view all intelligent agents as mechanical devices, are forced to admit that some configurations of matter can do things that other configurations cannot, such as write novels and create spacecraft, at least when we limit the time and probabilistic resources involved. If this were not the case, then why pay humans to perform certain tasks? Why not simply let nature run its course and perform the same work? Intelligent agents are at very least catalysts, allowing some tasks to be performed much more rapidly than is possible in their absence.
If we hold the second of these premises, namely that intelligent agents can accomplish some difficult tasks that unintelligent mechanisms cannot, and also hold that creating complex machines is a difficult task, then it follows that “creating life” may just be one of the tasks demonstrating a difference in causal powers between intelligent and unintelligent mechanisms. Notice the word “may”; the ID community would still need to demonstrate that intelligent agents, such as humans or Turing-test capable AI, can in fact construct life forms (or machines of comparable complexity and function), and would also need to demonstrate that unintelligent mechanisms are incapable of performing such tasks, even on cosmic timescales. This is where both positive ID work and necessary anti-evolution work arise, as they are required components of such an investigation.
ID theorists place the task of creating integrated, functionally complex machines in the group of tasks that are within the reach of intelligent agents yet outside the reach of unintelligent mechanisms, on the timescale of earth history. We can call this the third basic premise of ID, as currently modeled. It can be restated as,
3. Unintelligent causes are incapable of creating machines with certain levels of integration and function given 4.5 billion years, but intelligent causes are capable.
While we may dispute the truth of this statement, we cannot argue that it isn’t at least hinted at by the other two basic ID hypotheses. Given the first two premises, it naturally presents itself as a conjecture to be investigated.
PART II: ID PREDICTIONS
In light of these three premises, Jonathan M’s list of ID predictions appears much less ad hoc. Why should we expect functional protein folds to be rare in configuration space? Because if they were abundant, the task of creating novel proteins would be much easier, and by extension, so would be the higher-level task of creating functional molecular machines. Given the first premise, one expects at least some steps of the design process to present difficulties. True, this may not be the actual step that presents the difficulties, but given what we know about the curse of dimensionality, it is the natural place to begin investigation. And in light of what we now know concerning protein configuration space and the rarity of functional folds, such direction is not misleading.
In a similar vein, the prediction of “delicate optimisation and fine-tuning with respect to many features associated with biological systems” follows from the first basic premise of the model. Assume the contrary, for the sake of contradiction. If most configurations of matter and parameter settings result in integrated, highly functional self-replicating machines, then the problem of finding such configurations would cease to be difficult, by definition. Therefore, there must be a degree of specificity involved in life, such that the vast majority of configurations are incapable of functioning as life forms. ID’s basic premises require that the amount must, at minimum, be enough to place the task of finding such living configurations outside of the reach of unintelligent mechanisms given the probabilistic resources provided by a planetary or cosmic timescale. Therefore, a baseline level of fine-tuning is expected, and given the resources provided by a cosmic timescale, this baseline is predicted to be high. Once more, it could have been the case that most combinations of parameters and states would produce living organisms, making the problem of creating life easier, but this state of affairs would have helped falsify a widely-held basic premise of ID.
Evidence for these ID predictions would help confirm the basic ID hypotheses, and evidence to the contrary would weaken or falsify them. Therefore, it would seem fair to categorize them as predictions based on an ID framework. Without knowledge of the basic premises of ID as currently modeled, it is easy to see how confusion can arise when discussing what conclusions follow or do not follow from ID. If we don’t know the premises, how can we know what follows from them? It is my hope that this explicit spelling-out of foundational ID principles will aid in the discussion.
PART III: POSITIVE PREDICTIONS AND COMPOSITE MODELS
Lastly, I would be remiss not to mention the argument from analogy to human design, and how it relates to what is presented here. According to the argument, even if both intelligent and unintelligent mechanisms were capable of producing the effect in question (functional machines), intelligent agency might still serve as the best explanation, based on the similarities between engineered systems and living systems. If we’re fair, we are forced to acknowledge this line of argumentation is possible. Positive ID work could result from such an approach, since knowledge of how intelligent agents design things may shed light on how nature functions, or what to expect in terms of biological system construction. (See, for example, Casey Luskin’s discussion in “A Positive, Testable Case for Intelligent Design” where he describes how knowledge of human designed systems suggests predictions for biological systems.)
The strongest case for ID includes both types of evidence: positive evidence in favor of design, such as similarities to engineered systems and the use of design patterns within biological information systems, as well as evidence of the causal insufficiency of unintelligent mechanisms. If the third basic premise were falsified and intelligent agency was only one of multiple viable explanations, much more positive evidence would be required to make ID the most likely explanation, since we know that nature was operating when life formed, supplying the opportunity. Although ID could survive the falsification of the third basic premise, the case for ID would be severely weakened as a result, and the underlying model would be forced to change significantly, thereby modifying what is predicted by the model.
Some predictions would remain valid, such as those built on positive similarity to human design processes, but many predictions would not, including several presented by Jonathan M. ID as the sole viable hypothesis for the origin of integrated, functional machines differs from ID as one of multiple viable hypotheses, but positive evidence for design is certainly compatible with both models. The ID community currently holds to a model that both includes positive evidence for design and affirms all three basic ID premises outlined above. Therefore, both sets of predictions follow from the model: predictions based on the positive knowledge of human design activity and predictions implied by the causal insufficiency of unintelligent mechanisms.
* Note: The original post used the word “building” instead of “creating”, which caused some confusion among readers, since it was mistakenly taken to mean “the step-by-step assembly of machines” rather than the intended “design and creation of machines.” I use “create” in the sense of engineering, meaning to design and construct, to select from a realm of possible configurations. Thus, we say that engineers create new machine designs and software engineers create new software systems. The assembly process itself may be easy, but this is different than the task of discovering or creating the assembly instructions, gathering the required components, and setting any sensitive parameter values.