Unintelligent Design
Why Evolution is not an Intelligent Design Process
Why Evolution is not an Intelligent Design Process
Perfection: The Enemy of Evolution | Duke Pratt School of Engineering
In my book, The Unintelligent Designer: Refuting the Intelligent Design Hoax, I pointed out that evolution differs from intelligent design in three major ways:
- Prolific waste. Clever design is economical to make and use.
- Unnecessary complexity. Clever design is minimally complex.
- Lack of a clear purpose beyond producing more copies of itself.
The analogy is shooting arrows at a target and going with whatever method gets you closest to the bullseye, instead of discarding anything that doesn't hit the bullseye dead center. Only evolution doesn't even have a bullseye to aim at because there is no direction or required outcome.
But not so of a design process, of course, even a design process based on trial and error, because an intelligent design process will have a bullseye to aim at, and a preconceived idea of the ideal or optimal solution to the problem the design is intended to solve.
Creationism's putative divine designer, whom most creationists equate to the god of the Bible, Torah and Qur'an, being reputedly both omniscient and omnipotent, would not need trial and error, and would hit the bullseye, dead centre every time, so anything designed by it would never be sub-optimal, inefficient, or utilitarian. To a perfect designer, near enough is never good enough.
One of the many examples of unintelligent design I cited in my book is that of the enzyme known as RuBisCo (Ribulose-1,5-bisphosphate carboxylase/oxygenase), an essential component in photosynthesis. RuBisCo is so sub-optimal that it is the reason there is so much greenery around - plants need tons of the stuff to make enough sugar. Instead of the thousands of reactions per second that most protein enzymes are capable of, RuBisCo manages about four per second and frequently 'mistakes' a molecule of oxygen for a molecule of carbon dioxide, producing a toxic byproduct, wrecking the process, and costing the plant considerable lost energy and slowing the entire process down even further. But, because evolution can only work with what it already has, plants, and everything dependent on plants (i.e., almost all living things on Earth) are stuck with RuBisCo - probably the most abundant organic molecule on Earth and taking an appreciable proportion of the energy it produces in the form of glucose, to make.
Now, in an interesting paper published in the journal Biosystems, Adrian Bejan, the J.A. Jones Distinguished Professor of Mechanical Engineering at Duke University, Duke University, Durham, NC, USA, explains why a 'genetic algorithm', in other words, copying the evolutionary process, may be a better approach than the traditional aiming for perfection approach. A slightly less than perfect solution to a problem is easier to achieve and allows the design process to build on that solution and move on to the next step.
In it, Professor Bejan argues that chasing perfection is a constraint on design while accepting suboptimal solutions frees up more opportunities to explore possible improvements - just like the iterative process of evolution does.
The press release from Duke University explains:
Scientists are often trained to seek out the absolute best solution to a given problem. On a chalk board, this might look something like drawing a graph to find a function’s minimum or maximum point. When designing a turbojet engine, it might mean tweaking the rotor blades’ angles a tiny degree to achieve a tenth of a percent increase in efficiency.No doubt creationists will argue that, if this is a better way to design, then their intelligent designer would use it. But they are then unable to argue that their putative divine designer is omniscient, since it would then know in advance what 'near enough' solution is going to be best and that solution would have become its bullseye. If it has to wait and see what works best and go with that, it isn't omniscient and instead is a mere observer of a natural design process outside its control.
Adrian Bejan, the J.A. Jones Distinguished Professor of Mechanical Engineering at Duke University, was busy demonstrating the former for a class full of students when a thought struck him: this is not how nature operates. Evolution is a sequence of design changes happening on their own in a discernible direction; it never weds itself to a single point on a drawing board. An evolving system or animal is free to simply go with what works. Not so much that its performance suffers greatly, but enough that it opens access to other options near the so-called optimal design.
With science often looking to nature for clues to solve challenges, Bejan wondered if he might look the opposite way, to predict nature before looking at it. If problem solvers and builders were free to miss the absolute highest mark, how much greater might be the range of designs they consider plausible?If one is wedded to the idea of the absolute best, nothing new will ever be created.
ADRIAN BEJAN
That’s the question that Bejan posits in a new paper published online May 16 in the journal Biosystems. Using two relatively simple examples — walkways ferrying passengers off a train and a bird flapping its wings — he discovers that the answer is, “quite a lot.”
“In engineering, design, theater, architecture or even the organization of this university, any form of design benefits from the ability to make good but imperfect decisions and the freedom to move on and contemplate other opportunities for improvement,” Bejan said. “If one is wedded to the idea of the absolute best, nothing new will ever be created.”
In the paper, Bejan first looks at the example of passengers arriving by train and walking across a room with many exit points. With the total area of the room remaining constant but the length and width of the room free to change, he solves for the optimal shape of the room to get all passengers where they’re going the quickest. With the solution equations in hand, he shows that providing even 1% wiggle room for imperfection away from the best performance opens the design space by 28%.
The teaching of science should go hand-in-hand with the freedom to take a shot, hit the vicinity of the mark and move on. The end goal isn’t just to hit a bullseye, but to keep more arrows in your quiver to keep taking shots over a long period of time.
ADRIAN BEJAN
In his second example, Bejan looks at the flapping motion of birds at nearly constant altitude and speed. Considering the various forces involved — drag during gliding, lift created by wing size, speed and body size, among others — he formulates an equation for the rhythm of wings needed to maintain constant speed with minimum effort. While an optimal answer does exist, Bejan once again shows that allowing for just 1% imperfection above the theoretical minimum effort opens the design space by 20%.
Bejan says that he chose these examples because they involved changing only a single variable, a single degree of freedom — the shape for a room or the flapping rhythm for a wing. In more complex examples that involve many variables, these tiny tolerances for imperfection create an even wider range of “good enough” solutions.
The lesson learned is that science now has a predictive idea of how nature works. By focusing less on finding absolute optimal designs, researchers may use the freedom to iteratively move toward entirely new design concepts that wouldn’t otherwise have been within their sight. It also gives designs, methods and entire fields of study the ability to adapt to a changing world.
“The doctrine of chasing the best design is not helpful,” Bejan said. “The teaching of science should go hand-in-hand with the freedom to take a shot, hit the vicinity of the mark and move on. The end goal isn’t just to hit a bullseye, but to keep more arrows in your quiver to keep taking shots over a long period of time.”
Though doubtless they will try, creationists can't have it both ways in all honesty (not that all honesty has even been a consideration for a creationist argument).
Thank you for this excellent article and the new ideas in it.
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