In the context of the recent Dharali, Uttarkashi disaster, a renewed debate has begun over the causes and responsibility for such events. Politicians, journalists, meteorologists, and many others are presenting their own opinions. Based on these mixed viewpoints, various factors are being cited — nature, divine will, politicians, policymakers, the general public, land mafias, JCBs, unplanned development, and more.
T his situation is reminiscent of the well-known parable in which ten blindfolded people are asked to identify an elephant; each touches a different part and gives a fragmented answer. Similarly, our current debate is a patchwork of partial perspectives. The real question is: Is there any scientific or reliable system that can truly identify the “elephant” and provide a better alternative to the endless blame game?
For centuries, the epistemology and philosophy of science have sought to understand ultimate truth in the language of mathematics — modeling reality into theories and hypotheses, predicting extreme events or phenomena, and improving these models over time for a more accurate reflection of truth. Yet, this philosophical approach in both science and the humanities has been dominated by Newtonian thinking, which is deterministic, mechanistic, linear, and reductionist.
Vedanta philosophy, the Upanishads, and modern disciplines such as quantum physics, neuroscience, and quantum computing all challenge this Newtonian worldview as rigid and overly deterministic.
In recent decades, complexity science has emerged as a promising alternative for scientists, humanities scholars, and computer scientists alike, closely aligning with modern quantum science. This approach studies truth, phenomena, and systems in their entirety — focusing on the deep interconnections and interdependencies between all components of a system. Complexity science is now proving transformative in fields as diverse as biology, computer science, economics, financial markets, and public policy. The 2021 Nobel Prize in Physics was awarded for work rooted in this perspective.
Climate, weather, disasters, pandemics, economies, and socio-political systems are all complex adaptive systems — deeply interconnected networks where interactions between components can give rise to sudden crises (emergence). For example, a tiny virus originating in a remote lab or wild habitat triggered the COVID-19 pandemic, affecting global systems in unpredictable ways — the so-called “butterfly effect.” Such events highlight the limits of human knowledge and the inherent unpredictability of ultimate truth.
Yet, our existing models — in climate science, weather forecasting, governance, and public policy — are still grounded in Newtonian thinking. They break complex systems into isolated parts (reductionism) and seek simple linear cause-and-effect explanations, which cannot capture the full picture. As Albert Einstein observed: “We cannot solve our problems with the same thinking we used when we created them.”
In public policy, complexity science offers a transformative lens for contextual, adaptive, and co-evolutionary policymaking that accounts for sustainability and system sensitivity.
Therefore, blaming any single group for disasters like the one in Dharali is like wearing a blindfold in the elephant parable. However, the Government of Uttarakhand and its policymakers bear a statutory responsibility. Uttarakhand’s special state status was not granted merely to receive central funds and concessions while dismantling the Himalayas, but to pursue sustainable development in this highly sensitive mountain region.
If state leaders ignore the extreme vulnerability of the Himalayas, then central economic and policy support will depend more on political bargaining than on reason and evidence. Policymakers must recognize that the cost of a flood in the plains or a new road in the Himalayas is far higher and more complex in a mountain state.
For Uttarakhand, adaptive, co-evolutionary, and sensitivity-driven policy is not optional — it is essential. This requires collaboration between scientists, meteorologists, geologists, think tanks, policymakers, and local communities to create an integrated development policy and an actionable roadmap for its implementation.
Deepak,
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