Scientist Michael Behe has argued in a series of books that living organisms are too complex and organized to be the mere products of Darwinian evolution. He argues that there must have been some intelligent agency driving the appearance of living things. Much of Behe's reasoning is based on biochemistry, the complexities of which are over the heads of most people.
But Behe has a nice simple analogy that he has used for many years to advance his main argument. He often evokes an analogy in which complex biological innovations are compared to a mousetrap. Behe cites a mousetrap as an example of what he calls irreducible complexity. He defines irreducible complexity as some functional innovation that requires all of its parts to exist and to be arranged in the right way. According to Behe, a mousetrap is an example of irreducible complexity, because every one of its parts is needed for the mousetrap to work. Behe reasons that there are very many components in organisms that are like mousetraps, in the sense that they require all of their parts to be functional.
This analogy of a mousetrap is one that has received widespread attention, as has the phrase "irreducible complexity." But the mousetrap analogy is not a very good one, and the phrase "irreducible complexity" is a clumsy and ineffective way of describing the stupendous order, complexity and organization of living things.
Let us look at some impressive characteristics of large living organisms:
(1) They are information rich. Contrary to a widely circulated myth widely spread to serve the ideological purposes of Darwinists, it is absolutely untrue that living organisms carry around in their cells or DNA any blueprint or program or recipe for making such organisms. The DNA in cells merely contains low-level chemical information such as the amino sequences to make the polypeptide chains that are the starting points of protein molecules. But while DNA does not contain any specification of anatomy, it is at least information-rich. The essence of information is the use of representational tokens, in which some individual tokens (low-level semantic units) stand for or represent some larger physical or conceptual thing. DNA does qualify as information, because it is a series of nucleotide base pairs, and particular combinations of these base pairs stand for particular amino acids used to construct proteins. A human DNA molecule has 3 billion nucleotide base pairs, and these 3 billion units qualify as both information and representational information. So because a human is carrying a huge amount of information in each of his cells, we can call a human information-rich. Other simpler organisms also carry very high levels of information in their DNA, so every organism is information-rich.
(2) They are enormously organized. The degree of organization in large living organisms is greater than the organization of anything humans have constructed. A single cell is so organized that is has been compared in complexity to a factory or a city.
(3) They have a hierarchical organization. The organization of large organisms is extremely hierarchical. Subatomic particles are organized into atoms, which are organized into amino acids, which are organized into protein molecules, which are organized into protein complexes, which are organized into organelles, which are organized into cells, which are organized into tissues, which are organized into organs, which are organized into organ systems, which are organized into organisms.
(4) They are gigantically dynamic. Humans have known for centuries about two ways in which organisms are dynamic: first, the fact that organisms can move, and second that organisms grow from a small size to a large size. In recent decades, scientists have come to understand a third way in which organisms are dynamic: the fact that internally organisms are enormously dynamic, both because of constant motion inside in the body, and also because of a constant activity inside the body involving cellular changes. Just one example of this enormously dynamic activity is that fact that protein molecules in the brain are replaced at a rate of about 3% per day. A large organism is like some building that is constantly being rebuilt, with some fraction of it being torn down every day, and some other fraction of it being replaced every day. The analogy comparing a cell to a factory gives us some idea of the gigantically dynamic nature of organisms.
(5) They reproduce. Scientists understand how human females can become pregnant, but they do not at all understand how large organisms are able to reproduce. Scientists cannot even credibly explain how a single cell is able to reproduce. Scientists lack any credible explanation of how a speck-sized egg is able to progress to become the enormous organization of a large organism with so many different types of cells and organs. There is no truth to the claim that organisms reproduce because some blueprint or recipe for making the organism is read from the organism's genome or DNA. No such blueprint or recipe exists in DNA, which merely contains low-level chemical information such as the amino acids sequences of a protein molecule. Once you study all the very many types of incredibly dynamic and fine-tuned chemical and cellular choreography going on in the body, continuous intricate processes necessary for life, you may start to realize how childish is the very idea that an organism with such enormously dynamic internal activity could ever be specified by a blueprint (a plan for constructing static immobile things). We take for granted the miracle of reproduction because it almost always happens under a certain set of conditions. Similarly, if you could always conjure up a delicious 10-course meal by saying "Abracadabra," you might take such a thing for granted, and think it nothing very special. Without resorting to misstatements such as false and childish claims that organisms reproduce by a reading of a DNA blueprint for making the organism, evolutionary biologists are unable to explain the reproduction of large organisms.
There is an acronym we can use to remind us of some of these characteristics. The acronym is HIRDREOC, which stands for Hierarchical Information-Rich Dynamic Reproducing Enormously Organized Complexity. Almost all large visible biological organisms are examples of HIRDREOC. To describe humans, we might use the acronym CHIRDREOC, which stands for Comprehending Hierarchical Information-Rich Dynamic Reproducing Enormously Organized Complexity.
Now, let us look at Michael Behe's analogy of the mousetrap. Does such an analogy describe most of the impressive HIRDREOC characteristics I have listed? No, the analogy fails to do that. Mousetraps do not contain any information, and no part of a mousetrap stands for or represents something else. Mousetraps are slightly organized, but they are not at all enormously organized. Mousetraps do not have any hierarchical organization. Mousetraps do not reproduce. Mousetraps are only very slightly dynamic. The only movement that occurs in a mousetrap is when the trap slams shut. Even when organisms are resting, there is an enormous amount of dynamic activity inside of the organisms. There is no such incessant activity for a mousetrap, which only moves once.
So the mousetrap analogy does a bad job of suggesting the enormously impressive aspects of living organisms. Inside organisms are parts and systems a million times more impressive than the minimal functional organization of a mousetrap. But you might argue: at least the mousetrap explains the idea of irreducible complexity pretty well. But such a phrase of "irreducible complexity" is not a very good one to be using if you are trying to show the shortcomings of Darwinian explanations.
There are two problems with the phrase "irreducible complexity." The first is that merely appealing to "complexity" is not very convincing. One definition of "complexity" is "having many parts." But there are many natural things that accidentally appeared, and have many parts. A pile of rocks that arose from a landslide can be said to have complexity, in the sense of having many parts. But we know that such a thing can easily arise accidentally. The mere word "complexity" does a poor job of describing things that are functionally organized to achieve a particular result. If you want to argue that organisms have characteristics that they could not have obtained through accidental processes, it is better to use more specific terms such as these:
- functional complexity
- organization
- highly organized complexity
- fine-tuned complexity
- IRDREOC (Information-Rich Dynamic Reproducing Enormously Organized Complexity)
- HIRDREOC (Hierarchical Information-Rich Dynamic Reproducing Enormously Organized Complexity)
The second problem with the phrase "irreducible complexity" is that it is a mistake to put too much emphasis on a situation in which every part is needed for something to function. Systems that need every one of their parts to function seem to be pretty rare. But it is extremely common for there to exist some arrangement of parts too difficult to appear accidentally, with most but not all of the parts being necessary for function.
Below are some categories of innovations. These categories are not mutually exclusive.
Name |
Description |
Example(s) |
Type A Innovation |
Innovation requires all of its parts to have any functional benefit |
Mousetrap, probably some biological units |
Type B Innovation |
Innovation requires almost all of its parts before any functional benefit |
Jet aircraft, many protein molecules. Suspension bridge. Television, digital computer. |
Type C Innovation |
Innovation requires most of its parts before any benefit |
Cells, most protein molecules, an automobile (which doesn't need its roof, doors or seats or car hood or bumper to be functional), electric fan (which gives some benefit even if the cage and stand are missing), cardiovascular system |
Type D Innovation |
Innovation requires a series of sub-components, each of which is useless until mostly completed. |
Office tower. Each floor provides a benefit. But the construction of each floor requires many new parts, and no floor is useful until mainly completed. Also porcupine barbs (each barb is useful). |
Type E innovation |
Innovation may have some use in a relatively simple fractional form, but then requires many more parts organized in the right way to achieve a higher level of usefulness |
Vision systems (?) |
Type F innovation |
Innovation requires an arrangement of several complex parts before becoming useful, with at least 25% of its part existing and well-arranged until functionality is achieved |
|
Type G innovation |
As each small simple part of the innovation is added, usefulness is slightly increased |
Roof insulation, but almost nothing in the world of biology. |
Most of the impressive innovations in biology seem to be Type B innovations or Type C innovations. Such innovations are not credibly explained as being the results of blind accidental processes, and are not credibly explained by any ideas of evolutionary biologists. But such Type B innovations and Type C innovations are not "irreducibly complex" in the sense of requiring all of their parts to be functional. So such innovations are not appropriately described by an analogy of a mousetrap.
The most common biological innovations are protein molecules, which consist of hundreds of amino acids arranged in the right way to achieve a functional end. Humans have more than 20,000 types of protein molecules, and in the animal kingdom there are billions of types of protein molecules. The average human protein molecule has about 480 amino acids, and some proteins have more than 700 amino acids. Most protein molecules have more than thirty times as many parts as a mousetrap. Most protein molecules require most or almost all of their amino acid parts to be functional, but probably can still function if one or two of those amino acids are missing. So we should not be describing such molecules as "irreducibly complex," in the sense of requiring every one of their parts. But such molecules can be credibly described as "accidentally unachievable," for there is no credible scenario under which such molecules can arise because of random natural processes. The boast that scientists have figured out the origin of species is one that arose long before scientists understood the complexity of protein molecules, and is a boast that should have been retracted as soon as the complexity of protein molecules was discovered in the middle of the twentieth century.
Michael Behe's latest book is entitled "A Mousetrap for Darwin." By sticking to the lame and clumsy analogy of a mousetrap, Behe has made things too easy for his critics. We can imagine their thoughts:
"Why my job is not too hard -- all I have to do is explain how life could accidentally get things as complex as a mousetrap. That shouldn't be too hard; mousetraps aren't very complex."
Is there a better analogy we could use to replace this not-very-good analogy of a mousetrap? As I mentioned above, the impressive things about organisms is that they are examples of HIRDREOC, which stands for Hierarchical Information-Rich Dynamic Reproducing Enormously Organized Complexity. A car of the future might be an example of such a thing. If we imagine a car of the future, we can get an analogy for something that is HIRDREOC.
Let's consider each of the words in that acronym:
Hierarchical: Today a car has an organization that is somewhat hierarchical. A car has two wheeled axles, each of which is composed of smaller components (a wheel and an axle). The engine of a car has a somewhat hierarchical organization. Each engine is composed of several pistons and several cam shafts. Each seat unit consists of several parts, when we consider the position adjustment lever and the seat belt. We can imagine a car of the future that is even more hierarchical. Each window might be a complex unit consisting of many sub parts, such as parts that automatically cause the window to become visible despite rain or dust, and parts that automatically reduce the window's visibility when you yell "reduce my visibility to others" or "too much sun." Each seat in the car might consist of many different parts, including its own individual video screen and sound system, allowing three different passengers to enjoy three different movies while the car is driving.
Information-Rich: In the 1960's a car would be information rich only in the sense that there would almost always be maps in its glove compartment. Nowadays there may be no such maps, but many cars are information-rich in the sense of having computerized components that use information. We can imagine a car of the future being very information rich, with a built-in GPS and mapping system, so that your current location (on a map) is always displayed on a small screen on the car dashboard. Such a car might also have information that warns you of upcoming bad weather on the route you are driving, or information that warns you to slow down whenever you drive though some zone with a lower speed limit (such as a school zone).
Dynamic: A car is dynamic in the sense of being very mobile, and in the sense of having engine parts such as pistons that are constantly in motion. We can imagine a car of the future that would be even more dynamic. It might, for example, have tires that automatically repair themselves when punctured. Or it might have an automatic vacuuming system that cleans up food spills instantly. Or instead of just having air bags, the car of the future might have air balls that instantly inflate when a collision occurs, protecting you from both head-on collisions and side collisions. We can also imagine a car of the future having many additional dynamic features, such as (1) automatically self-cleaning windows; (2) an ability to hook itself up automatically to a gas pump or a fueling unit, allowing the owner to refuel without getting his hands dirty, or (3) an ability for the car to contract and reduce its own size to fit into a smaller parking space, or (4) an ability to change itself into a convertible, so that the roof of the car slides out of view when you tell it do so.
Reproducing: Cars currently lack the ability to reproduce, but we can imagine some super-fancy car of the future that might have the ability to reproduce. It might have the astonishing ability to split into two different cars, which would be useful when you and your wife want to drive in different directions.
Enormously organized: Cars are enormously organized, consisting of a fine-tuned arrangement of thousands of parts to achieve a particular functional end. Nowadays there are some 30,000 parts that make up a car. We can imagine a car of the future with millions of parts.
The thing is that natural is not the same as artificial. In an artificial object what you see is what you get, since this is what a human consciousness with visual qualia put there. This is not the same in a natural entity. A protein is not necessarily only made out of aminoacids. This is only what we see using our visual qualia. But our human consciousness didn't evolve visual qualia to be useful for that level of reality. So it might well be the case that there are other aspects of reality involved in a protein that are simply beyond our consciousness to perceive them. So even the analogy with a future car is not good, since a future car will still be artificial, so what you'll see will still be what you'll get. Not the same for a natural entity.
ReplyDeleteMy purpose was to create a artificial thing analogy that better signified the complexity of living things. I realize that all such analogies are imperfect and leave something to be desired, since non-living things are not living things. The idea you suggest that a protein molecule may have undetected parts invisible to our instruments is an interesting speculation. But if that were true, it would seem to make protein molecules even more complex, and even harder to explain by natural processes.
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