The latest issue of American Scientist features some superb reflections by Robert L Dorit on the limitations of reductionist thinking in the biological sciences. They have clear parallels for social sciences and, by extension, for social policy. Selected extracts are below.

Despite Descartes’ contention that we could not distinguish a well-made automaton of an ape from an actual ape (“were there such machines exactly resembling organs and outward form an ape or any other irrational animal, we could have no means of knowing that they were in any respect of a different nature from these animals”), the relations of parts to wholes in living systems is entirely different from that in machines—and most unclocklike. If anything, living systems consistently violate all of the criteria for reducibility. The number of elements that compose any living system—an ecosystem, an organism, an organ or a cell—is enormous. In living systems, the specific identities of these component parts matter. Unlike chemistry, for instance, in which an electron in a lithium atom is identical to an electron in a gold atom, all proteins in a cell are not equivalent or interchangeable. Each protein is the result of its own evolutionary trajectory. We understand and exploit their similarities, but their differences matter to us just as much. Perhaps most importantly, the relations between the components of living systems are complex, context-dependent and weak. In mechanical machines, the conversation taking place between the parts involves clear and unambiguous interactions. These interactions result in simple causes and effects: They are instructions barked down a simple chain of command.

In living systems, by contrast, virtually every interesting bit of biological machinery is embedded in a very large web of weak interactions. And this network of interactions gives rise to a discussion among the parts that is less like a chain of command and more like a complex court intrigue: ambiguous whispers against a noisy and distracting background.

As a result, the same interaction between a regulatory protein and a segment of DNA can lead to different (and sometimes opposite) outcomes depending on which other proteins are present in the vicinity. The firing of a neuron can act to amplify the signal coming from other neurons or act instead to suppress it, based solely on the network in which the neuron is embedded. The disappearance of a single species can stabilize an ecosystem or send it spinning into chaos, depending on (you guessed it) the network of interactions that surrounds that species. This extensive and subtle connectivity, which gives meaning to the behavior of the underlying components, turns out to be a consistent feature of living systems.

The recurrent evolution of these networks of weak interactions suggests that they may allow biological systems to incorporate information from the environment while also maintaining stability in the face of constant perturbation. This general feature of living systems also has clear methodological consequences for modern biology. Once this gossamer web is taken apart in search of the smallest components we can study, the process of putting it back together bears no resemblance at all to reconstructing a clock. Thus we find ourselves, early in the 21st century, with extraordinarily detailed descriptions of the components of many biological systems. But reconstructing those systems is proving to be a monumental and consistently surprising enterprise.

The promise of reductionism rested on the belief that an intelligent dissection of complex phenomena would not only yield progress, but would eventually reduce any problem to its component parts. Complexity, we naively hoped, was simply a by-product of incomplete understanding, an illusion that would fall away once the parts were fully understood. But this is the dirty little secret of contemporary biology: Despite our reductionist successes, the central conceptual problems of biology have not yielded to study. We have revealed the elegant workings of neurons in exquisite detail, but the material understanding of consciousness remains elusive. We have sequenced human genomes in their entirety, but the process that leads from a genome to an organism is still poorly understood. We have captured the intricacies of photosynthesis, and yet the consequences of rising carbon-dioxide levels for the future of the rain forests remain frustratingly hazy. We are, in short, the king’s horses and the king’s men: We stare at the pieces, knowing what Humpty should look like, but unable to put him together again.

How does one deal with such complexity? In living systems, Dorit argues, the component parts are always embedded in an intricate web of interactions. Such complexity appears at multiple levels of organisation as shown in the three illustrations below: a network of interactions among 1,700 different human proteins (top), a food web in a Puerto Rican rain forest (middle) and a neuronal network in a mouse brain (bottom).

Dorit continues:

the days when we could have blind faith in the power of reductionist deconstruction are over. Humpty lies in fragments. Fortunately for us, a new approach is taking shape to replace the seductive appeal of reductionism. We biologists may have bought a little too much of what Descartes had to sell, but as the limits of naive reductionism become more obvious, additional methods emerge for understanding the complexity of life. This new, interactionist perspective on living systems, with its emphasis on the interplay of parts, has benefited from new computational tools and experimental approaches. Whole new subfields in the life sciences, as well as productive interactions among existing disciplines, have emerged. Systems biologists, complexity theorists and newly minted biologists now attend as carefully to the ways in which parts come together as they do to the parts themselves. In the process, features of living systems that we once carelessly overlooked (or destroyed) in our haste to deconstruct now snap into focus. We are, for instance, beginning to understand that modularity and redundancy are inherent features of all levels of biological organization. These features characterize systems that are simultaneously resilient and capable of evolving.

Read the full article here.


Join the conversation! 1 Comment

  1. Well, it pretty much requires that the idea of Development (with a capital D) is thrown out (probably both the baby and the bathwater). It requires letting go of notions of Utopias and static development plans. It requires letting go of (linear) thinking A causes B causes C. Those sorts of things blind us to what is.

    Love this: “In the process, features of living systems that we once carelessly overlooked (or destroyed) in our haste to deconstruct now snap into focus.”


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About Ben Ramalingam

I am a researcher and writer specialising on international development and humanitarian issues. I am currently working on a number of consulting and advisory assignments for international agencies. I am also writing a book on complexity sciences and international aid which will be published by Oxford University Press. I hold Senior Research Associate and Visiting Fellow positions at the Institute of Development Studies, the Overseas Development Institute, and the London School of Economics.


Biology, Evolution, Innovation, Knowledge and learning, Networks, Reports and Studies