One of the least appreciated contributions of evolutionary theory to biological studies has been to slow its progress. In my last three articles (here, here, here), I explained how the theory predicts that living systems should not appear designed to achieve purposeful goals. And any semblance of design should typically appear clumsy and inefficient. Following these expectations, biologists have often falsely concluded that structures or systems were nonfunctional or suboptimal if investigators could not immediately understand all their features. Emily Reeves wrote several excellent articles highlighting examples (here, here, here). Fortunately, the collaboration between engineers and biologists over the past few decades has helped overturn these false premises.
Here I will address how engineers helped to correct an additional false assumption. Evolutionary theory predicts that biology should resemble human engineering only marginally at best. Yet, life frequently embodies the very same design logic and motifs. The main difference is that life displays far superior levels of complexity, efficiency, and ingenuity.
Evolution and Rube Goldberg Machines
The logic of evolution dictates that the components of complex biological structures and traits came together haphazardly without the benefit of foresight or goal-direction by an intelligent agent. Entities (e.g., proteins) that served one purpose linked with other entities serendipitously to achieve a different collective goal (e.g., ATP synthase recharging ATP). The lowest-level pieces originated first, so the final product represents “bottom-up” design.
In reality, bottom-up design still requires designing the components and properly linking them together, but I will overlook this inconvenience for the sake of argument.
Such composite systems should resemble Rube Goldberg machines. Rube Goldberg was an American inventor and cartoonist who drew contraptions that performed a simple task through a series of unrelated devices awkwardly interconnected. The action of one device would trigger the next, which would trigger the next, and so on, to achieve some goal not directly connected to any of the individual components. The entire mechanism was comically inefficient and cumbersome.
Evolutionist Jerry Coyne emphasized in his hatchet-job review of Michael Behe’s Darwin Devolves how life should display similar bottom-up design:
Indeed, the uniform experience of scientists who work on these [biological] systems is that they embody an absurd, Rube Goldberg-like complexity that makes no sense as the handiwork of an engineer but makes perfect sense as a product of a long and unguided historical process.
Coyne’s critique of Behe lacked intellectual honesty and scientific accuracy (here, here), but his insight into what evolution should produce was entirely correct. Of crucial importance, Coyne referenced no examples of Rube Goldberg-like complexity in life because none exist.
Biology and Engineering
In contrast, systems biologists now recognize that biology demonstrates top-down design where an overarching goal and corresponding design constraints dictate the engineering of a complex trait. Each component of a structure or system perfectly integrates with other members to achieve a predetermined goal with astonishing efficiency.
Thus, life does not resemble Rube Goldberg-type machines but human engineering. The stark contrast between the actual higher-level organization of life and evolutionary expectations has created tension within the biological community. The authors of System Modeling in Cellular Biology (SMCB) commented,
An often noted reservation against the type of analogies between biological and engineered systems we brought forward states that these two types of complex systems arise in fundamentally different ways, namely through evolution versus purpose-driven, top-down design (see, for example, Bosl and Li (2005)).SMCB, p. 32
Engineering Motifs in Life
Biology does not simply resemble human engineering generically, but it contains the very same design frameworks. The System Modeling authors explain:
At a more abstract level, we see highly organized and structured networks that facilitate global and coordinated responses to variations in the environment on all time scales, using local and decentralized mechanisms. … The basic framework is employed in many advanced technological systems. … Clearly, from an engineering point of view, biology is a marvel of technological “design.” We argue that analogies with engineered systems, in particular regarding how to generate appropriate responses to variations, are one major requirement on all highly integrated systems that can help us grasp biological complexity.SMCB, pp. 26-27
The authors further argue that design motifs employed in life are known to represent the most effective strategies for achieving target goals,
From engineering, it is known that feedback control (plus feedforward control) enabled by fast and if possible remote advanced-warning sensing is the most powerful mechanism for providing robustness to fluctuations in the environment and the component parts. The heat-shock response in E. coli appears to employ exactly the same principles as shown by detailed modeling and subsequent model reduction to the core elements (El-Samad et al., 2005).SMCB, p. 39
Equally striking, Reeves and Hrischuk (2016) identify a cell as an embedding computing system since human and biological computing systems share numerous components. Examples of shared components include the following: processing engine, information code, primary memory, secondary memory, memory addressing, low-level memory layout, memory management, cache, timer, randomly accessed persistent storage, high-level data formatting, and the list goes on. These components also share many of the same functional interrelationships. Computer engineers would attest that such systems can only operate if most elements exist and properly interconnect.
How Biology Differs from Engineering
The most philosophically astute materialist scientists recognize the hazard of too closely comparing biology to engineering. Not only does engineering embody intelligent design, but engineers have developed a deep intuition of what incremental processes can and cannot achieve. And they recognize that the design patterns pervasive in life could not possibly have emerged through any gradual, undirected process.
Biologists wedded to scientific materialism have argued that life is so different from human artifacts that they can dismiss engineers’ conclusions about organisms’ limited evolvability. The central fallacy in this argument is that nearly every difference between human creations and life makes the latter ever more challenging to design. And the challenges translate into more daunting obstacles for any evolutionary scenario.
Design motifs such as four-bar linkages and control systems must meet exacting requirements whether implemented in a space shuttle or a fish (here, here). Many of these requirements operate largely independently of the constituent materials that compose them or the exact methods they employ in their operation. Moreover, the distinctive nature of living systems entails many additional requirements and even stricter constraints. Not only must a biological element function properly, but an organism must also manufacture, maintain, and operate it.
For instance, the vertebrate eye must conform to many of the same or comparable requirements seen in digital cameras. And its construction requires a highly coordinated manufacturing process in embryology directed by a meticulously engineered genetic control system. Neither the overarching design nor the construction process could have emerged incrementally (here, here).
In addition, the fundamental differences between human and biological engineering reflect the superiority of the latter. For instance, Frølich et al. (2017) detailed the extraordinary ingenuity associated with the materials that organisms manufacture. And M. L. Simpson et al. (2004) stated:
Genetic and biochemical processes are highly functional and dense systems. Cells perform highly complex functions regulated by genetic circuits and networks much like engineered systems, only at far greater densities, complexity, and capabilities. Silicon-based technology cannot come close to the kinds of integration seen at the bacterial scale, for example.
Researchers increasingly employ engineering (aka design) insights, tools, and language to understand living systems, and this trend “shows no sign of slowing down.” Those who argue that intelligent design does not result in fruitful research, leading to a deeper understanding of life, demonstrate that their own understanding of the biological literature is twenty years out of date.