My mom labored the counters on the State Bank of India when she was my age. She counted payments, served clients, and moved between branches earlier than returning to the mess at residence. Her life was demanding, nevertheless it was legible. Mine, as a freelancer working from my very own desk, is more durable to decipher: a tangle of logins, deadlines, and dependencies that shift sooner than I can observe them.
This is not only a private statement. Life is now lived inside interconnected networks, amongst collected techniques upon techniques.
Complexity is the defining situation of our time. All our lives are marked by occasions in social networks, monetary and public infrastructure, well being, and commodity provide chains. Part of the complexity is interconnected crises—all interacting, all altering, none behaving in ways in which conventional science is absolutely outfitted to clarify.
“At a time which some see as a breakdown of order and many anxieties abound, the embarrassment of complexity is widely felt. It results from the gap between feeling overwhelmed by the sheer scale and scope of problems confronting us, and the pressure to pretend that we can manage them,” writes Science, Technology, and Society Studies scholar Helga Nowotny in the e-book 43 Visions of Complexity.
Within interconnected networks that adapt as they go, when one piece shifts, the results ripple outward in ways in which defy easy cause-and-effect pondering. The reductionist strategy in science, which gave us discoveries in microbiology and particle physics, is not enough to know our complicated world. We want new instruments we are able to apply, not on the micro stage of particular person actors, like cells or particles, nor on the macro stage of the entire system, however on the meso stage—between the 2. We badly want to know the workings of the networks that we reside inside.
Tackling real-world networks in an summary manner is a job for physics and arithmetic. A rising variety of polymaths, physicists, mathematicians and interdisciplinary information scientists are answering the decision to check the science of complicated adaptive networks. These networks could also be organic, social, and even philosophical. Thankfully, there’s a creating subject referred to as complexity science, and it’s coming of age.
Recently, as an EMBO Maria Leptin Science Journalism fellow, I plunged into this new-ish science on the Complexity Science Hub in Vienna, Austria. All summer season of 2025, I requested 25-odd scientists: What is complexity science? And how do you do it?
One of the primary concepts I got here throughout throughout my time on the Hub was written on a sticker.
| Photo Credit:
Aashima Dogra
During the numerous interviews on the Hub, I met scientists learning how ailments unfold, how polarisation in society happens, what chess-playing machines reveal concerning the human thoughts, how we are able to stop habitat loss to guard biodiversity, what an environment friendly transport system appears to be like like, developments in AI adoption, and weak hyperlinks in international provide chains. Attempts to reply these complicated questions have been constructed on the foundational fashions from physics and math. Each researcher noticed a real-world community in an summary manner.
Complexity science is the research of complicated adaptive techniques the place emergent phenomena come up when the entire is ‘greater’, or simply totally different, from the sum of its elements. Complexity science embraces uncertainty and observes how complexity arises from easy interactions. By doing so, it emphasises the place and the way a lot we are able to veer the adapting system.
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Creative Commons
Such an strategy is extremely helpful. Work by complexity scientists on the Hub in Vienna has knowledgeable public decision-making on a number of events. In one mission, researchers on the Hub labored with the Austrian Federal Railways to find a way to minimise delays on the train network. In one other instance, in 2020, a mannequin co-developed and operated on the Hub was utilized by the Austrian government to forecast what number of ICU beds wanted to be reserved for COVID-19 sufferers because the pandemic raged on, week by week. These numbers, in flip, knowledgeable the size and stringency of lockdowns in Austria, in a crosstalk between the federal government and scientists enshrined in Austria’s COVID legislation. By the tip of my residency, the promising scientific work I encountered had really renewed my hope in evidence-based coverage.
Stefan Thurner, the Director of the 10-year-old Complexity Science Hub, is a pioneer in the sector, Stefan has a knack for explaining why the world wants complexity science to check social techniques. “In the many complex systems we study, fundamentally, there are some shared dynamics that have to do with nothing else but how networks are connected. Before a big transition, the networks prepare a little bit,” he stated in an interview, wriggling his linked fingers. “You don’t notice that they are doing that, especially if you don’t look. When you look, you can see little rearrangements here and there as the system prepares, and then you have a BANG. Rapid transitions follow. And rapid transitions in social systems are always associated with crisis and catastrophe,” he stated.
This view pinpoints the primary motive we want such a science. Complexity scientists may help study the precursors of disaster and counsel methods to probably alter course.
“As a community, we should not give the impression that we are able to tell the future,” Stefan added. “Wherever possible, we can improve the situation by asking: What will happen when this or that changes? What happens when we change the temperature or social pressure, or say, the density in a network? What will be the consequence of it, or what will be, say, the critical temperature of this system?” stated the physicist by coaching.
A nation of contradictions
As an Indian science author, I felt a powerful urge to see such a scientific strategy to understanding and problem-solving again residence. With a billion-plus individuals navigating rising inequality, caste, language, geography, and speedy digitalisation , India is among the most complicated societies on earth. Its monsoons, energy grids, railways, and public well being networks are all complicated techniques we don’t but absolutely perceive. After returning to residence floor, I continued my interviews—this time with India’s burgeoning complexity science neighborhood.
Sarika Jalan delivered a keynote on the NetSci convention earlier this month in Boston.
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Sarika through NetSci
Sarika Jalan, a complexity scientist at IIT Indore, is a rising star from the Indian complexity neighborhood. She organised the 2025 NetSciX, a global faculty and convention of the International Network Society, and just lately delivered a keynote on the father or mother convention NetSci in Boston. With some others, she is organising the India chapter of the International Complexity Science Society. Sarika is amongst Indian researchers who’ve already made significant contributions to the theoretical side of complicated techniques concept and are wanting to develop fashions utilizing real-world information. In a web based interview, she instructed me, “India provides many different avenues in the study of complex systems. Whether we can actually utilise this kind of research for the country’s benefit is another question.”
Our issues of inequality, ecosystem collapse, catastrophe administration and different such points won’t yield to siloed experience. These are issues of interconnection. Sarika provides an instance: “Suppose there is a threat of floods in Uttarakhand. It may not be possible to solve the problem of evacuations and infrastructure development locally. If you view it through the lens of complexity science, you can take a broader view of the interactions at play. You take all elements into account, including storms, land use, and population. We have various tools in the study of complex adaptive science, like non-linear dynamics and our agent-based models, that we can apply to support a strategy for minimal loss in the case of a flood occurring.”
Complexity science is very good at understanding how parts shift in their interactions and which type of interactions can result in crises. In Sarika’s instance, it is extremely helpful to know the circumstances underneath which the system floods or collapses. And from her scientific perspective, understanding the circumstances that may result in main shifts requires systems-level pondering. She will not be alone in this sentiment.
“Deep mathematics translated to real engineering”
At IIT Madras, combustion engineer-turned-climate scientist R.I. Sujith has been busy understanding and even predicting the Indian monsoons utilizing the Indian authorities’s Indian Monsoon Data Assimilation and Analysis (IMDAA) datasets, amongst others. Sujith is a senior researcher with a number of discoveries and patents underneath his belt. “But I am a baby in complexity science,” he stated. He runs the 2023-launched Centre of Excellence for Studying Critical Transitions in Complex Systems, one of many at the least two devoted teams at IIT Madras that work on complexity science.
Sujith’s view of complexity science is overwhelmingly constructive. “It is deep mathematics translated to real engineering,” he acknowledged. Before his foray into complexity, Sujith was an engineering researcher who made a number of discoveries a few phenomenon often known as combustion instability.
R.I. Sijith in his lab.
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R.I. Sujith
(Here’s Sujith explaining combustion instability as a posh system, and another video exhibiting NASA’s studying curve with the phenomenon.)
He metamorphosed right into a complexity researcher when he realised that the techniques he was learning inside combustors in gasoline generators and rocket engines have been complicated techniques. After collaborations with ISRO and dealing on General Electric engines, he’s dedicating his “second innings” to making use of what he realized about complicated techniques to the Indian monsoon.
Recently, Sujith collaborated with a bunch of monsoon scientists whose work “yielded good results on predicting the seasonal average of Indian Summer Monsoon Rainfall 18 months in advance,” he says. He labored on the bodily rationalization behind this profitable long-lead prediction utilizing synchronisation concept, part of complexity concept, which examines how totally different techniques modify their rhythms to function collectively.
His use of complexity concept to know the Indian monsoon is just getting began. “We are able to monitor and declare the onset of monsoon at every location in the country. We are working on a prediction scheme to predict it, possibly a couple of weeks in advance.”
Another mannequin he labored on predicts the seasonal common for Northeast Monsoon in Tamil Nadu with a 10-month lead.
His pleasure concerning the huge potential of complexity science was mirrored in a 2016 paper on early detection of essential transitions in complicated techniques, in which he and the opposite authors have been quoted in a Nature article, suggesting: “their observations can be applied to spot similar tipping points in other domains, such as finance.” Sujith was pleasantly stunned when the paper was cited by Dominic Cummins, then the chief advisor to British Prime Minister Boris Johnson, in an open call for scientists to function coverage specialists for the UK authorities.
Data woes in India
“We have a huge scope in India, but one of the obstacles in India is the difficulty in getting good-quality data,” Sarika remarked, interrupting my fever dream of complexity-backed decision-making in India.
She recollected the time when she tried to assemble information to mannequin the results of storms on India’s energy grid. “I require very basic data on the latitude and longitude of transformers,” she instructed me. She contacted a number of companies that maintain this information, however bought no response. Eventually, she discovered a smaller on-line database and determined to work with it. “Then the problem was that there was no latitude and longitude in the data, only names of places,” she remembered. This meant her PhD college students spent a month manually figuring out the latitudes and longitudes of these locations. “The scholars in my lab had to spend their time cleaning up data rather than developing their critical ideas on complexity science,” Sarika added.
“There is a lack of awareness of complex systems research in India among PhD students,” says Sarika Jalan, pictured right here together with her college students.
| Photo Credit:
Sarika Jalan
Indian complexity scientists like Sarika converse wistfully of their colleagues in Europe, North America, South Korea, New Zealand, and Singapore, the place public companies allow easy accessibility to real-world information and devoted institutes have been established to check complexity science.
The problem of getting one’s fingers on interoperable information (clear information that can be utilized for numerous functions) to use complicated system theories in India begins with establishing a knowledge infrastructure for scientific use. There have been efforts, however these don’t meet the size wanted to nurture a thriving complexity science neighborhood.
Consider the case of Jawaharlal Nehru University-affiliated well being and agricultural economics researcher Anirban Chakravarty, who has been a part of efforts to construct such information alternate frameworks. Since his PhD days, he has been in inequality in India. He has been learning social disparities in India as a posh system with interacting and adapting influences of well being, agriculture and economics. Outputs of his work embody apps that assist farmers make knowledgeable selections about value volatility and market indicators.
He sums up his analysis premise in this fashion: “If I am a government agency, how do I ensure that there is less inequality and the distribution of wealth is uniform. We work with historical data that we collect from different agencies, and then we use machine learning techniques to do predictive analysis.”
An enormous quantity of knowledge is required for such a activity. And that has been a giant problem. Teaming up with scientists from the Institute of Mathematical Sciences in Chennai, the TERI School of Advanced Studies in Delhi, and others, Anirban just lately utilized for a mission grant underneath the ANRF Mission AI for Science and Engineering to construct a repository of databases on well being and social indicators from totally different companies just like the National Sample Survey Office, National Family Health Survey (NFHS) and others. “We want to collate all the available data, clean it, and make it available to develop foundational models for what we are calling quantitative health economics,” he stated.
If they obtain the grant, the group hopes to arrange datasets to be used by numerous stakeholders and policymaking companies. Anirban instructed that discussions are ongoing in the neighborhood on learn how to facilitate information sharing and enhance coordination amongst companies.
“Data has been a challenge in India, whether it is health data or economic data,” he stated. “There is a lack of data of different granularities…meaning that often, only country-level data is of good enough quality. It becomes difficult for us to compete with other advanced regions like Europe because we lack proper documentation. For economic indicators or social governance indicators, we do not have data at the state level, and it’s even worse, district-wise. If you want to do some statistical analysis or machine learning modelling, you have to train your data on the past or historical data, and that’s when we face the challenge that we don’t have very long time series,” he added.
A time collection is one information sort that may do wonders for some complexity scientists. Time collection evaluation helps them study the circumstances underneath which an occasion occurred in a community, and assess dominoes that fell on account of that occasion. Niraj Kushwaha, a researcher from Boisar, Maharashtra, was finishing his PhD work on the Hub after I met him. He had spent the final 4 years creating a statistical mannequin to see how armed conflicts on the African continent are linked. “When you zoom out and look at the sites of armed conflicts on a map, there is a definite pattern. The dataset contains only a time series of armed conflict events and the locations where they occurred. And, hence, it is free from any ethno-political biases,” he instructed me.
Niraj seen presenting his work.
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Niraj Kushwaha
For his analysis, Niraj took the map of Africa and broke it down into random blocks. He then encoded in his mannequin a time collection dataset of armed battle occasions in the area that he bought from a global, impartial database. As he defined, I noticed colored dots seem on a map on his laptop computer. “These are in no way sporadic events, and heuristic approaches to understanding armed conflict might not be useful for managing or preventing them,” he discovered. Heuristic approaches are people who depend on expertise, instinct, or sensible guidelines of thumb to resolve issues or make selections, quite than following a hard and fast, systematic methodology.
His outcomes present that conflicts observe the identical sample as avalanches: a single occasion can set off a direct cascade of comparable occasions, every one feeding the following “Conflict avalanches,” he calls them. Niraj agreed that one may, in precept, apply his mannequin to any area of the world.
Is returning to India on the playing cards for him? I requested Niraj. “That would be a dream! But not any time soon,” he stated. He added that our nation wants systematic quantitative research and a thriving neighborhood to help such work in fixing our societal and financial issues.
Understand, then predict
In 2021, a staff of researchers from IIT Kanpur and IIT Hyderabad got here up with the Susceptible, Undetected though infected, Tested positive, and Removed Analysis (SUTRA) mannequin of the then-raging COVID pandemic. “Natural immunity provides significantly better protection against infection than the currently available vaccines,” the mannequin, which was endorsed by the Indian authorities, concluded.
Soon after the mannequin was publicised, different researchers identified its flaws. Eventually, the mannequin wrongly predicted that the pandemic and its influence on India would quickly finish. Researchers criticised the mannequin for endorsing the federal government’s makes an attempt to prematurely have a good time its COVID measures that, in reality, proved to be inadequate, ensuing in the deaths of many Indians.
The failure of the SUTRA mannequin serves as a cautionary story. Several complexity scientists I spoke to warned in opposition to counting on complexity science for predictions. What it provides is arguably extra helpful: the power to ask ‘what if’. This capability may help us see, earlier than a system breaks, the quiet rearrangements that sign an incoming disaster. Using this data, researchers can promote resilience in our techniques. Simply put, complexity science can equip good planning.
Complexity science will not be a crystal ball, cautions Stefan Thurner. “By definition, it seeks to understand systems that one cannot predict. That implies that complexity science could not predict anything. And I think that’s right, since complexity science wants to understand systems… not predict them, but to manage them,” he stated.
Being inherently interdisciplinary, complexity science is well-suited to our fashionable instances. New analysis questions are more and more adopting AI instruments to scrub and reconstruct datasets. Equipped with new instruments and wealthy in theoreticians of complicated adaptive techniques, India’s Complexity Science neighborhood is poised to undertake fruitful scientific endeavours.
The world will not be going to get easier. And a rustic of India’s scale and ambition can’t afford to manipulate complexity with Twentieth-century devices. As one of the complicated societies, India’s stakes in getting this proper are huge.
Aashima Dogra is a science author; she co-founded the feminist science media portal thelifeofscience.com and is the co-author of the current e-book Lab Hopping, which investigates the realities behind the gender hole in Indian STEM.
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