Jan C. Schmidt on Synthetic Biology: Self-Organization, Instability and Late-Modern Technology
According to Schmidt the term synthetic biology refers to “harnessing self-organization for engineering purposes” (Schmidt, J., 2015). The central idea to this notion is our ability to initiate and control incredibly unstable and complex biological systems. Effectively, one’s that match the complexity of a living organism. If we are ever able to accomplish this task, we will be dealing with artificially created systems that possess a considerable degree of agency and autonomy. This could imply reduced control and autonomy for us.
Schmidt argues that the onset of synthetic biology is a distinguishing mark of humanity entering the era of late-modern technology. In order to analyze synthetic biology, Schmidt urges for an interdisciplinary approach, one such approach is offered by ProTA — ProTA (prospective science and technology assessment) draws on political science, sociology, philosophy, ethics, history, science and technology studies, as well as physics, biology, informatics, mathematics, and systems sciences. Schmidt concentrates on the technoscientific components in particular.
Late-modern technology is an entire paradigm, a way of conceiving technology and nature. It is a separate ontology that draws on complexity. Chaos Theory, Non-Linear Dynamics, Dissipative Structures, Synergetics etc. present elements of holistic thinking which begin reasoning at an irreducibly complex level and remain essentially non-reductionist.
So what does the blanket term “Synthetic Biology” mean? What are its constituent parts? What promises does it hold? What visions of the future does it portray? What is at stake? How is it to be realized? It is important to pose the correct questions so that we can know what it is that we are trying to achieve during this discussion.
The obvious intuition is that synthetic biology is a merging of engineering with biology. Biology tends to be descriptive and explanatory, whereas engineering tends to be interventionist, changing and re-creating our environment. In this sense it would seem that two distinct, diverging disciplines are beginning to find common ground. And the general theoretical interest that used to underline biology is now transforming into a passion for applied technological innovation.
An underlying feature of synthetic biology is that the objects it studies, though almost identical to things in the natural world, do not occur naturally at all. Bio-systems are exclusive products of the late-modern technological development. It is probably important to remember that any world-views or deductions about the nature of the universe based on this framework would be incorrect, but that would be engaging in an altogether different debate. Two main takeaways here: Synthetic biology is an entirely applied science and it deals with artificial systems that diverge from things that could be encountered in nature. Bio-Nature is different from nature, it is not discovered, it is made.
Synthetic biology is often seen as an extension of biotechnology in general.
The second framework for defining synthetic biology concentrates on the methods rather than the objects under study. One could interpret synthetic biology as an extreme version of genetic engineering which dates as far back as the 1970’s. In this sense synthetic biology is not a breakthrough or a radical innovation, rather the last word of a well-established science.
Defining synthetic biology is under no circumstances simple nor trivial matter. The interdisciplinary nature of the field generates almost as many definitions as there are methods and approaches to it. Not to mention that each definition serves as a label which opens up different directions of possible research in the future.
Despite the level of complexity involved with research in synthetic biology, technological reductionism offers a reductive framework for dealing with developments in this field. Technological reductionists often draw a distinction between bulk technology and molecular technology. The first deals with the elemental constituents of matter (atoms etc.) in bulk, while the latter offers more precise and detailed constructions. Nanotechnology is something that falls within the reductionist paradigm much more readily than synthetic biology, the former is in fact the result and direct expression of techno-scientific reductionism.
Schmidt thinks that both the reductionist and the traditional scientific definitions of synthetic biology fail to account for its most basic features. The author offers instead the concept of self-organization. Automatic self-organization is something that is easily encountered in nature. The question is how this process can be re-deployed in an artificial laboratory setting. What this implies on a slightly more speculative level, is essentially the engineering of life, with some researchers claiming, that something as complex as human consciousness could emerge under controlled settings, if the necessary conditions can be constructed artificially.
The underlying point being that synthetic biology as an instance of late-modern technology marks the gradual erasure of differences between natural and artificial systems. It is when technology becomes most similar to life. “Late-modern technology does not resemble our established perception and understanding of technology and technical systems. From a phenomenological perspective, it is a new type of technology which appears as (bio-)nature and displays nature-like characteristics; it appears “un-technical” or “non-artificial” ” (Schmidt, J.C. 2015).
There is an entire field of interdisciplinary engineering that attempts to reap the benefits of self-organization processes, where synthetic biology is only one approach. Some keywords around these disciplines include: self-assembling, nonlinearity, complexity, autopoiesis, emergence, instability, sensitivity, chaos, deterministic chance, interactivity, flexibility, adaptivity, evolutionary process.
The mathematical descriptions for self-organizing systems both in nature and in artificial settings are exactly the same. This is part of what Schmidt describes by the term nomological convergence. Nomological convergence implies a convergence, that is strong similarity, between technological and biological systems. Both can be modelled in terms of systems thinking. Systems thinking usually rejects all reductionist approaches to self-organization and complex systems.
The term “self-organization” was first coined by Immanuel Kant in 1790 in the Critique of Judgment. Schelling further developed the notion in his Speculative Physics (1801). One consistent position throughout philosophy since Aristotle and until today, has been the sharp separation between natural beings and human artefacts. It was thought that self-organization as a process of recursive, periodic emergence of novelty was an exclusive feature of things found in nature and that no human creation could ever possess the same level of autonomy. We seem to be approaching an epistemic revolution in this area.
On the other hand, it is still problematic to speak of bio-nature in the sense that self-organizing systems are by definition unstable. We cannot control a system which admits of true novelty and in this sense, either the divide between natural and artificial systems remains intact or we might create something well beyond our intellectual and technical capacities. This is precisely Schmidt’s definition of self-organization. “The basic answer that I propose is that instabilities are essential for self-organization phenomena” (Schmidt, J.C. 2015). But if instability implies chaos or incomplete information, can we really say that this negative definition is more than a failed attempt at a definition? This will take us too far into questions of entropy and the paradoxes of the 2nd law of thermodynamics, which would be well beyond the present domain of inquiry.
The idea of instability can be explained in terms of sensitivity to initial conditions. Or in other words, there is very little or virtually nothing in the cause that could allow us to predict its effects. There is an asymmetry between prior and posterior events. Instability means disruptions, discontinuities and unpredictability. But it does not entail destruction and this is an important distinction. A complex system is not one that might “go off at any moment” or self-annihilate at any given second. It is more than that: Self-organization implies that the system moves towards unlikely outcomes, that it can acquire irreducibly complex features that are not derivable from its previous states. It can perform a “leap of faith” toward a higher level of order, and therein lies the paradox. An unstable system can become a super-stable system based on its ability to adjust. Order out of Chaos, so to speak.
Synthetic Biology aims to understand and master this process. “The positive view of cognate phenomena such as noise, randomness, stochasticity, and fluctuations comes close to the positive appreciation of instabilities. Instabilities can, in fact, be regarded as a source of law-based white noise” (Schmidt, J.C., 2015). The question of how an absence of information can be positive, law-like and constitutive, is an enigma that bioengineers will have to tackle.
The nomological convergence therefore implies an incorporation of instability. This is the challenge today and the deciding factor in whether the boundary between nature and technology will disappear. The dangerous implications of trying to tame far-from-equilibrium systems have been well illustrated in Sci-Fi horror movies since the 1980’s. Hopefully, developments in Synthetic Biology will take these possibilities into account and secure our civilization from such a troubling fate.
- Kant, I. (1931). Critique of Judgement (p. 66104). London: Macmillan.
- Schelling, F. W. (2012). Ideen zu einer Philosophie der Natur. Jazzybee Verlag.
- Schmidt, J. C. (2015). Synthetic biology as late-modern technology. In Synthetic Biology (pp. 1–30). Springer, Cham.