Doing Interdisciplinary Science: from Complex Systems to Computational Biology to Climate Change—Fireside Chat with Gautam Menon
“Medicine is a social science, and politics nothing but medicine at a larger scale.”
—Rudolph Virchow (1821–1902)
The Power of Perspectives
This famous quote by Virchow, who was convinced that social inequality was a root cause of ill health and that medicine, therefore, had to be social science, foregrounds the argument for bringing diverse perspectives to help understand the world’s challenges today. Virchow argued in his book Cellular Pathology (1858) that the human body was “a cell state in which every cell is a citizen.” By drawing an analogy between a human body and the perfect citizen-state and the cell as the locus for all diseases, Virchow provided a new vision of human physiology. Although some consider Virchow’s analogies between biology and sociology out of date, some of his core ideas still resonate in public health (Mackenbach, 2009). Virchow’s concept of sociomedical causation emphasizes the role of social and environmental factors in the etiology and prevention of diseases (Lange, 2021). The COVID-19 pandemic further corroborated this connection between biology and sociology. COVID-19, in all its dimensions, including incidence, testing, and severity, is known to be associated with social inequalities. Such inequalities are associated with differential exposure to the virus, greater susceptibility to infection, more frequent comorbidities associated with severe outcomes, and disparate access to care (Quantin & Tubert-Bitter, 2022)
Acknowledging Virchow’s idea of the citizen cell and following this argument, Pulitzer Prize-winning oncologist Siddhartha Mukherjee, in his The Song of the Cell: An Exploration of Medicine and the New Human (2022), believes that the evolutionary shifts from unicellular to multicellular life were driven by the idea of citizenry—that he says is the moral of the story of our evolution. Tougher together and division of labor were the two key drivers of this evolutionary shift.
Siddhartha Mukherjee presents a symphony of characters who have each played their roles in unraveling the song of the cell. He presents a compelling tale of the extreme complexity of the cells and the cellular systems, as these cells do not sit in isolation but talk to each other (the song of the cell). The new heretic of today is to understand the interactions between cells and the complex ecology of humans and the entire environments in which we live, and this will empower us. Understanding the song of the cell or wicked problems of any kind-from Climate Change to Disinformation is a challenge that can be better studied through interdisciplinary research.
In this episode of InfoFire, I am in conversation with Gautam Menon, Professor of Physics and Biology and Dean of Research and heads the Centre for Climate Change and Sustainability (3CS) at Ashoka University, who believes that climate change is a settled science and requires an interdisciplinary approach to mitigate its worst consequences. This will involve cutting-edge research into ecological shifts, monitoring local environments, socio-economic issues connected to climate change, sustainable lifestyles, and the development of effective teaching and awareness tools.
Listen to our fireside chat here on the topic of “doing interdisciplinary science.”
The conceptualization of a discipline and what constitutes interdisciplinarity—from multidisciplinary cross-disciplinary to transdisciplinary—constantly evolves, and the consensus is hard to come by. Nevertheless, research areas are dynamic: continually emerging, melding, and transforming. What is considered interdisciplinary today might be considered disciplinary tomorrow (NSF).
Simply put, interdisciplinarity is thinking across disciplinary boundaries to find solutions to scientific and social problems. U.S. National Academies of Sciences, Engineering, and medicine’s report Facilitating Interdisciplinary Research offers a fairly comprehensive working definition of Interdisciplinary research:
“Interdisciplinary Research (IDR) is a mode of research by teams or individuals that integrates information, data, techniques, tools, perspectives, concepts, and/or theories from two or more disciplines or bodies of specialized knowledge to advance fundamental understanding or to solve problems whose solutions are beyond the scope of a single discipline or area of research practice.”
Listen to Dr. Menon, who takes us through his journey and the evolving research interests from a physicist to a computational biologist to a climate scientist and his passion for interdisciplinary research. For Gautam, it all began with his interest in complex systems. What are complex systems?
From Complex Systems to Computational biology to Climate Change
According to the all-knowing Wikipedia, “A complex system is a system composed of many components which may interact with each other. Examples of complex systems are Earth’s global climate, organisms, the human brain, infrastructure such as the power grid, transportation or communication systems, complex software and electronic systems, social and economic organizations (like cities), an ecosystem, a living cell, and ultimately the entire universe.” This definition not only captures the essence. scopes out the possibilities and underpins the inevitability of interdisciplinarity. The individual parts—called “components” or “agents”— and the interactions between them often lead to large-scale behaviors which are not easily predicted from a knowledge only of the behavior of the individual agents. Such collective effects are called “emergent” behaviors. Examples of emergent behaviors include short and long-term climate changes, price fluctuations in markets, foraging and building by ants, and the ability of immune systems to distinguish “self” from “other” and to protect the former and eradicate the latter (Mitchell & Newman, 2002).
We see complex systems everywhere: the collective behavior such as V formation and flocking formations of migratory birds to make flight easier and ant foraging and geodesic paths in labyrinths. We see them in the formation of social networks and in the patterns of communication, social capital, and reputation that emerge from them. Siegenfeld & Bar-Yam (2020) summarize the general properties of systems as opposed to the modeling of specific dynamics and pedagogically describe a conceptual and analytic approach for understanding and interacting with the complex systems of our world.
According to the omniscient ChatGPT, studying complex systems often involves using mathematical and computational models and tools from network theory, information theory, and dynamical systems theory. Complex systems science seeks to understand the principles that govern complex systems’ behavior and develop methods for predicting and controlling their behavior.
For Gautam Menon, the problems of complex systems have all the heterogeneity of people, all the varieties of social behavior or physical context, et cetera. And then, within a particular social context within a population, how disease spreads seem to be a question that lay behind his transition to epidemiology—an area that is at the frontier, not just of computer simulations, not just of ideas about complex systems, but also about complex problems in epidemiology.
—Wicked problems cannot be solved by applying standard methods; they demand creative solutions—
The phrase wicked problem originated in social planning. However, its modern sense was introduced in 1967 by C. West Churchman in a guest editorial in the journal Management Science. Rittel and Melvin M. Webber formally described the concept in 1973, contrasting “wicked” problems with relatively “tame” soluble problems in mathematics, chess, or puzzle solving (Rittel & Webber, 1973). They further clarify that they are calling these problems “wicked” not because these properties are themselves ethically deplorable but in a meaning akin to that of “malignant” (in contrast to “benign”). Even though Rittel and Webber framed the concept in terms of social policy and planning, wicked problems occur in any domain involving stakeholders with differing perspectives.
The discussion around this path-breaking conceptualization of wicked problems and the political argumentation needed to resolve them has endured. Intense interest in the nature of wicked problems and the complex tasks of identifying their scope, viable responses, and appropriate mechanisms and pathways toward achieving improvement has continued into the 21st century (Crowley & Head, 2017). Wickedness is not a degree of difficulty. Wicked issues are different because causes are innumerable, tough to describe, and they do not have the right answer. Environmental degradation, terrorism, and poverty—are classic examples of wicked problems (Camillus, 2008). Scholars note that wicked problems cannot be tackled by the traditional approach of problem-solving in sequential steps because there is no clear definition of wicked problems.
Wicked problems cannot be solved by applying standard methods; they demand creative solutions. Nancy Roberts (2000) identified many strategies, such as Authoritative, Competitive, and Collaborative, to cope with wicked problems. A collaborative approach is the best option despite the problems that beset it. Rittel (1972) recommends a systems approach and hints at a collaborative approach, one which attempts “to make those people who are being affected into participants of the planning process. Wicked problems call for collaborative learning. As Conklin (2006) notes, collective intelligence is the creativity and resourcefulness a group or team can bring to a collaborative problem. It is a natural property of socially shared cognition, a natural enabler of collaboration.
Collaborative Networks: “Get the Whole System in the Room”
As Nancy Roberts (2000) notes, wicked problems, and their solutions are socially defined. People construct their meaning. The problem with social definitions is that they vary along people’s personal preferences, backgrounds, educational experiences, and organizational affiliations, predisposing them to see the world differently and believing that “my truth is better than your truth.” Roberts believes in network approaches to resolving wicked problems and endorses Bunker and Alban’s large group interventions strategy (1997). According to her, one way to move people beyond their “my truth is better than your truth” positions is to get “the whole system in the room” so stakeholders can begin to learn from one another.
There has been a growing interest in understanding the potential of networks to confront wicked problems. The positive attributes of networks, such as the capacity to solve problems, govern shared resources, and create learning opportunities, are recognized along with significant literature and considerable scholarship. Collective intelligence is a natural property of socially shared cognition, a natural enabler of collaboration, and the creativity and resourcefulness that a group or team can bring to address a wicked problem are phenomenal (Conklin,2006).
Weber & Khademian (2008) share similar interests and underpin the fundamental challenge of solving wicked problems in network settings as transfer, receipt, and integration of knowledge across participation.
Responding to my question—whether to integrate or transcend different perspectives, knowledge, expertise, et cetera while doing interdisciplinary research, Gautam Menon opines that we must integrate and then transcend disciplinary differences. He says there is a certain order in which it has to happen. First of all, people from different disciplinary backgrounds must come together to find that common ground, that common area in which they can talk and develop a common language by which they can interact. He hopes that the science of the future will be much more integrated, and it is essential to ensure that we train students to interact and collaborate.
Sharing his experience collaborating with others, Menon says there is no secret sauce for good collaboration. It is a question of commitment to collaboration, he says. It is also a question of realizing that you cannot do this on your own and seeking help from others. It is more of an attitude of how we solve this problem together. That your attitude shifts a little bit and changes meaningfully is vital to convey. Everyone figures out their way of dealing with it.
Science is now inevitably a collaborative thing. Take the example of a big experiment, like the Large Hadron Collider experiment, which requires many people to come together. People who design magnets, people who design low temperatures and cooling systems, the theoretical people who model the collisions between particles, and people who work on the phenomenology of looking at particle tracks and understanding a new particle was created in a particular collision at a particular energy. All of these people contribute together to that understanding, and you cannot remove any of them from this and hope to achieve the same understanding.
GST, Systems Science Approach and interdisciplinary Science
There has been a revival of interest in the systems approach for unifying sciences since the turn of the 21st century. General system theory (GST), cybernetics, and complexity science are three significant intellectual sources inspiring this renewal. The complex systems approach is the most recent development of the new paradigm initiated by Ludwig von Bertalanffy and his conceptualization of General System Theory (GST). His mathematical model of an organism’s growth over time, published in 1934, is still in use today. Hofkirchner & Schafranek (2011) explore GST and believe the new paradigm of complex systems has more in common with GST. This also holds for philosophical implications’ epistemological, ontological, and ethical aspects. According to them, aiming for generalizations, GST laid the foundations for a state of science called “trans-disciplinarity.” To re-address enduring questions about the unity of science and the unity of the systems paradigm, Şenalp & Midgley (2023) support the recovery of Alexander Bogdanov’s philosophical and systemic thinking that culminated in his magnum opus, Tektology, which described a new universal science that consisted of unifying all social, biological and physical sciences by considering them as systems of relationships and by seeking the organizational principles that underlie all systems.
Menon on Interdisciplinary approach to solving Wicked problems: Climate and infectious diseases
Gautam Menon also believes that while the complexity of the world around us brought us to this interdisciplinary approach to research, today, being interdisciplinary is absolutely crucial. He gives two examples: Climate Change and infectious diseases such as COVID-19.
When we think about climate change, it is possible to think about it from a purely technical or engineering perspective. We can worry about how humidity might change weather patterns, large-scale circulation, global climate models, et cetera. That would tell you about many scenarios for how climate might change in the future. Furthermore, one can get to increasingly refined ways of understanding this by improving the sorts of models that we have, that we have now been working on for the last 40 to 50 years. We understand the many different components, the atmosphere, the ocean currents, the incoming sunlight from the sun, and how all of these interact. However, other parts are purely social and affect a large-scale change in our climate. We need to be able to move forward on technological innovation and curb our consumption patterns, such as burning up fewer fossil fuels and shifting to more sustainable alternatives. Furthermore, there is the economics of climate science. What are the right incentives that you must bring to bear? There is also the issue of climate change communication. How do you tell people what to do? What are the right nudges to choose in that? For example, how do we expect human health to change with changing climate? Thus one begins to see that the question of climate change is much more subtle than you might initially have thought it to be. It is not just a problem in engineering; it is not just a problem in economics. It is not just a problem in physics, biology, medicine, or anything. It is all of these together. For example, a geo-engineering solution to climate change might mess up other parts: for example, the ecology of life on Earth in ways we have yet to anticipate. That is why it is called a wicked problem. So, to understand and approach these problems, you need, at your core, to think in an interdisciplinary manner, and even if you belong to one discipline, to be able to talk to people across disciplines to integrate what they say.
The second example Menon takes is that of infectious diseases. Here again, how a disease spreads is not just a question of how a virus moves from person to person, but what context do they do? How does society influence the interactions between people? Why do infectious diseases affect some subpopulations much more strongly than other subpopulations? For example, if you are poor or in the United States, are black, belong to disadvantaged groups, et cetera, your chances are falling ill with, say, a COVID-19 infection or any infectious disease is disproportionally more. So how does this combination of social status, economic abilities, et cetera, determine your susceptibility and likelihood of falling ill?
That is, again, not just a question of diseases, not a question of epidemiology; many other components must come together in our understanding. The frontiers now are to understand many of these additional parts, not just biology, which on its own is fascinating. For example, why do some people fall severely and some fall mildly ill? What is the nature of the difference in the host behavior that predisposes some to more severe outcomes versus milder outcomes? Understanding this in a larger framework is only possible to do with understanding society. So, to understand infectious diseases and populations, all of these subjects must come together and collaborate to deepen our understanding.
Quantum information science
Quantum information science is a field that combines the principles of quantum mechanics with information science to study the processing, analysis, and transmission of information. It covers both theoretical and experimental aspects of quantum physics, including the limits of what can be achieved with quantum information. Quantum physics, information theory, and computer science are among the crowning intellectual achievements of the twentieth century. At the dawn of the twenty-first-century dawns, a new synthesis of these themes gave rise to Quantum Information Science (QIS.) It is a field with the potential to cause revolutionary advances in science and engineering involving computation, communication, precision measurement, and fundamental quantum science. The roots of this field go back about twenty years when pioneers such as Charles Bennett, Paul Benioff, Richard Feynman, and others began thinking about the implications of combining quantum mechanics with the classical Turing computing machine.
According to Menon, Quantum Mechanics has introduced many unusual ideas into how we normally describe physical systems. What is fundamental is a quantum state of a system. There are probability amplitudes for the system to be in any number of states it can occupy. Quantum probability is a different animal from classical probability. You can have multiple possibilities that coexist at the same time.
Moreover, the very act of measurement crystallizes one of those possibilities. These are the things one thinks about quantum mechanics, quantum probability, and the implications for how information is transferred using quantum mechanical means from one point to another. What we understand from the early work of Einstein, Podolsky, Rosen, and other people who came after that are the sort of strange quantum mechanical constraints that operate by which you can have two particles that are entangled together but then can be separated very far away, and then making a measurement on one particle automatically tell you something about the other particle. Quantum teleportation is a technique for transferring quantum information from a sender at one location to a receiver some distance away. Menon contends that quantum information theory and its cousin quantum computing, which uses the same sets of quantum mechanical ideas, are essential elements of what might potentially be the future ways of designing equipment, designing new computers, for example, that can do things that classical computers cannot do.
Google and IBM have invested significantly in quantum computer hardware research, leading to significant progress in manufacturing quantum computers since the 2010s. Google Quantum A.I. is advancing the state of the art of quantum computing and developing the tools for researchers to operate beyond classical capabilities. IBM has declared 2023 as a major inflection point in quantum computing as they are getting ready to begin realizing the quantum-centric supercomputer.
Like the song of the cell, we need to understand how to interact and collaborate with other scientists from diverse fields and play a concert to help solve the world’s wicked problems.
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Cite this article in APA as: Urs, S. (2023, March 8). Doing interdisciplinary science: from complex systems to computational biology to climate change—Fireside chat with Gautam Menon. Information Matters, Vol. 3, Issue 3. https://informationmatters.org/2023/03/doing-interdisciplinary-science-from-complex-systems-to-computational-biology-to-climate-change-fireside-chat-with-gautam-menon/