Member Blog: David Zilberman

Understanding Paradigms in Science, Life, and Economics – Based on Kuhn’s The Structure of Scientific Revolutions

I got a wonderful gift from Thomas Reardon, a volume of Thomas Kuhn’s classics. I should have read it before, but I didn’t, and reading it, I understood why it’s a “great” book. It presents a convincing conceptual framework, compelling narrative without excessive jargon, and presents interesting and clear examples. The book presents an original vantage point to understanding scientific progress. Rather than assuming that science advances through smooth accumulation of knowledge, it suggests convincingly that science advances through periodic revolutions that shake the scientific fields. 

Paradigm is a key concept in Kuhn’s analysis. It is a shared framework that defines problems, methods, standards, and exemplars within a scientific community. Once a paradigm exists, most of the scientific work within this paradigm is part of normal science, where scientists solve “puzzles” rather than question fundamentals, refine measurements, extend applications, and articulate theory. Normal science is conservative by design; it aims at precision, not novelty. Over time, anomalies arise. They are empirical findings or conceptual problems that cannot be fully explained within the prevailing paradigm. For a while, these anomalies are ignored, explained away, or treated as measurement errors. But over time, when anomalies accumulate and become persistent, the field may enter a crisis, where confidence in the existing paradigm erodes, competing ideas emerge, and methodological and conceptual disputes intensify. This crisis may lead to a paradigm shift. This is a scientific revolution where a new paradigm replaces the old one. This change is discontinuous, as all the new paradigms may use different concepts, standards, and questions, and the choice between paradigms is influenced not only by data, but also by judgement, persuasion, and community dynamics. Classic examples of shifts are: in physics from Newton’s world to Einstein’s relativity, and the big shift in astronomy from traditional to Copernican. 

With new paradigms, the same data can be interpreted differently, and standards of explanation vary, but there is a strong conviction that you’ll get closer to the truth. Every new paradigm has some holes and therefore, normal science tries to fill them. Paradigms generally tend to explain the range of issues that science can analyze and explain and increase the capabilities of scientific communities. Fascinatingly, Kuhn argues that scientific change is a social process sustained by scientific communities – and therefore persuasion is crucial for a scientific revolution that may take a long time. Education is crucial in establishing paradigms because textbooks that reflect paradigms train new generations of scientists. Frequently, marginal groups in scientific communities play a major role in introducing a new paradigm. Younger members of disciplines tend to be earlier adopters of new paradigms and subscribers to the older paradigm tend to either convert or die :-). Nevertheless, people may believe in and act according to concepts of multiple paradigms. For example, accepting Newtonian mechanics and Einstein relativity. 

Religion is a paradigm

My perspective on religion comes from my familiarity with Judaism. Prior to the emergence of Judaism, there were multiple ancient religions in the Middle East believing in multiple specialized gods responsible for rain, wars, etc. The gods were part of nature and there were ritual activities including sacrifice to satisfy the gods. These religions have their own priesthoods and the religions and priesthoods were supposed to provide insurance (against droughts), healthcare, education, and political legitimacy, among others^[1]. Judaism provided a paradigm shift. It introduced the notion of a universal god, separating between gods and nature. It prescribed a moral law and rituals (Mitzvot), which are the core of religious life. Judaism has the equivalent of “normal science”, which is a continuous scholarly activity, refining and expanding the paradigms. It has a social structure (scholars, teachers, certifiers) that provides multiple services to its adherents. 

While initially, Judaism was linked to Israel and the temple in Jerusalem, the destruction of the temple by the Romans, led to significant paradigm modifications where sacrifice was replaced with prayers and the religion became more global and can be practiced everywhere. Christianity, in my view, is a paradigm shift that retained monotheism and ethics, introducing Jesus as a mediator between God and humanity. It also emphasizes the role of faith vs. the pursuit of practices and emphasizes a pursuit of universal membership. Modern secularism is a paradigm shift compared to the monotheistic religions, but people can hold beliefs and practices associated with both. While with religion, outcomes are governed by the gods, in secularism it’s governed by impersonal laws and much of the content and beliefs are constructed by humans. While religious opinions and actions are governed by faith, tradition, and authority of the church; in secularism perspectives are based on science and evidence, and the truth is revisable. In secular systems, science replaced theology for explaining nature, secular law provides guidance and enforcement, and states replace churches for governance. 

Religion and science are Incommensurable, namely, ask different questions, and use standards of evidence. Therefore, people should be able to subscribe to both in different aspects of life. One of Kuhn’s major contributions is the emphasis of the social aspect of the paradigm. Both religion and modernity lead to institutions, and organizations, and professionals that provide multiple services. They include centers of education, healing and welfare, some are competing, and some are cooperative. Conflicts among religions and modernity led to multiple conflicts. The Peace of Westphalia, initiated a process that ended religious war in Europe and ushered a separation and coexistence of state and church (at least in some countries). So, history, religion, and politics evolved, but Kuhn’s notion of paradigms is really crucial to understand them. 

Technological Paradigms

The notion of paradigms is useful in explaining technological evolution and change. Technological paradigms can be viewed through the Kuhnian prism to understand how technological waves can change the problems that are being solved, provide new solutions, and lead to the establishment of skills, institutions, practices, and evolve into a supply chain. 

The printing revolution in the 15^th-16^th century is a paradigm shift. Before, knowledge was transmitted by hand-copied manuscripts or orally, and literacy was scarce. After a long transition, printing allowed a mass reproduction of information, standardization of knowledge, and rapid diffusion of ideas and technologies. Similarly, the industrial revolution in the 18^th and 19^th century, was a shift from old paradigms that relied on artisan production, human and animal power, and localized manufacturing to industries that rely on mechanized production, fossil fuels, and factories and economies of scale. In the 19^th and 20^th century, electrification and mass production were significant paradigm shifts, and in the late 20^th century, we had digital computers and the information revolution. We are now in the midst of artificial intelligence and data-centric revolution, which are based on new learning systems and pattern recognition at scale, and probability decision-making. While we are aware of the occurring transition, we are less aware of its implications. Personally, I realized that if you cannot beat them, join them and this blog post was written with the assistance of AI. From my minimal experience with AI, I learned that you need to be very well-informed to produce useful prompts and to check the reliability of the results. I am also concerned about the capacity of humans and the future of employment in an AI world. 

As an economist, I am particularly interested in the transition from a fossil-based, linear throughput economy to a circular one. In the prevailing paradigm, the central objective has been to maximize output efficiently, with environmental impacts treated largely as externalities. The emerging paradigm instead focuses on how to meet human needs and aspirations within planetary limits.

Under this framework, performance can no longer be evaluated solely by profits or GDP. Assessment must also account for life-cycle emissions, system resilience, and net present value at the whole-system level. The transition entails moving from fossil-based technologies to modular renewable energy systems, and from linear extraction and disposal to circular material flows.

This shift creates value in technologies for recovery, recycling, and reuse; in bio-based materials; and in designs that enable disassembly. It also points toward integrated bio-industrial systems and symbiotic innovation and product supply chains that jointly consider economic, environmental, and resilience attributes.

Such a paradigm shift requires a policy environment that de-risks innovation, coordinates infrastructure, and sets dynamic standards, while preserving space for entrepreneurship and experimentation.

The Evolution of Economics’ Paradigms

Economics’ paradigms have evolved in response to changing technologies, institutional complexity, and societal objectives. While early economic thought focused on markets and efficiency, successive paradigms progressively incorporated uncertainty, institutions, innovation, and governance. 

Classical political economy, associated with Adam Smith and David Ricardo, focused on production, specialization, and long-run growth constrained by land and resources. Analysis emphasized aggregate outcomes rather than the mechanisms through which new technologies emerged and diffused.

The neoclassical paradigm associated Alfred Marshall shifted attention to marginal decision-making, prices, and allocative efficiency. It provided powerful tools for analyzing markets, but innovation remained largely exogenous, and economic success was evaluated primarily through static efficiency. This framework offered limited insight into technological change, scale-up, or long-run adaptation.

Major disruptions—the Great Depression and later stagflation—motivated macroeconomic paradigms centered on stabilization and expectations, most notably Keynesian and New Classical economics. While these approaches advanced understanding of business cycles and policy credibility, they did little to explain how innovation is generated, financed, and commercialized, or why many socially valuable technologies fail to scale.

From the late twentieth century onward, economics increasingly turned toward innovation and institutions. Economic growth theory, led by Robert Solow, Daron Acemoglu, Paul Romer and Philippe Aghion, made technological change central to growth and showed that incentives and policy shape innovation rates. Induced innovation models demonstrated that the direction of technological change responds to relative prices, scarcity, and regulation, an insight especially relevant for agriculture, energy, and environmental technologies.

At the same time, institutional and organizational economics expanded the analytical scope. Ronald Coase and Oliver Williamson explained how transaction costs, uncertainty, and asset specificity shape the governance of innovation, while David J. Teece showed why firm capabilities, complementary assets, and business models determine whether innovations capture value. 

Another recent paradigm is behavioral economics. It represents it relaxes the neoclassical assumptions of fully rational, self-interested agents with stable preferences, replacing them with empirically grounded models of bounded rationality, heuristics, and systematic biases. It integrates insights from psychology and neuroscience, shifting economics from a purely deductive framework to one that is increasingly experimental and evidence-based. This paradigm explains persistent anomalies—such as under-saving, inertia, and loss aversion—that standard models cannot reconcile. As a result, it changes both positive analysis and policy design, justifying interventions like nudges that improve welfare without relying solely on prices or mandates. The transition among paradigms in economics is not stark and several coexist, yet over time, the new paradigms tend to be adopted.  

From Micro and Macro Paradigms to a Supply-Chain Systems Perspective

The evolution of economic paradigms can be interpreted not only as a sequence of intellectual shifts, but also as a growing recognition of the limits of narrow analytical lenses. A useful distinction is between macro paradigms, which focus on aggregate outcomes such as growth, employment, and inflation, and micro paradigms, which focus on individual decision-making, market interactions, and price formation. Much of modern economics has been built on micro paradigms that abstract from the physical world and treat economic performance as emerging from a relatively small set of transactions, prices, and equilibrium conditions.

Traditional neoclassical microeconomics, and many of its extensions, rely on simplified representations of production and consumption in which technologies are summarized by production functions and environmental feedbacks are largely ignored. Even when uncertainty and expectations are introduced, as in rational expectations or information economics, the physical transformation of materials, energy, and biological resources remains peripheral. Behavioral economics has enriched this framework by relaxing assumptions of full rationality, introducing bounded rationality, heuristics, norms, and biases. While behavioral insights improve predictions of individual and market behavior, they often remain disconnected from the biophysical systems in which economic activity is embedded.

In contrast, macro paradigms—Keynesian, growth, and institutional approaches—have focused on aggregate dynamics, long-run development, and systemic constraints. Yet these paradigms also tend to treat technology and production structures in highly aggregated ways, limiting their ability to address coordination failures, scale-up bottlenecks, and sustainability challenges that arise at intermediate levels of organization.

This course advances a different perspective, one that is more closely aligned with real-world economic and environmental systems. We argue that economies are better understood as networks of multiple, symbiotic supply chains—both of innovation and of production—that transform raw materials through successive stages of discovery, development, processing, distribution, and consumption. These multistage supply chains explicitly incorporate biophysical constraints, behavioral responses, and institutional arrangements, and they generate not only valued goods and services but also residues that are sources of pollution and environmental stress. Forever, more than 90% of innovations don’t end up as commercial products and innovation and product supply chain are subject to random shocks and uncertainties that have to be considered as we analyze them.  

Viewing economic systems through this lens allows economists to better explain past patterns of technological change, anticipate future transitions, and design effective policy interventions. In particular, it provides a way to address classic chicken-and-egg and coordination problems—where valuable feedstock are not developed because there is no infrastructure to utilize them. Such problems arise in sustainable energy, bioeconomy development, and circular material systems—where prices alone fail to induce efficient outcomes. By embedding economic behavior within interconnected innovation and product supply chains, this paradigm offers a more realistic and policy-relevant foundation for analyzing economic performance in a world facing tight environmental constraints and rapidly evolving societal demands.

Conclusion

The Kuhnian paradigm perspective provides a powerful framework for assessing the evolution of human thought and action systems, including science, religion, technology, and economics. History reveals recurrent revolutionary patterns in which established ways of thinking and doing are fundamentally transformed, often accompanied by profound social and organizational change. 

Kuhn provides a powerful lens for understanding the evolution of economic thought and practice. Periods of “normal economics,” in which analysis focuses on marginal adjustments within established frameworks, are periodically disrupted by deeper transformations driven by technological change, social pressures, and binding biophysical constraints. Today’s transition from a fossil-based, linear throughput [רפ4] economy toward a circular and bio-based system reflects such a moment of paradigm change. Traditional economic metrics and analytical tools—centered narrowly on prices, profits, and aggregate output—are increasingly insufficient for guiding decision-making in a world facing climate change, biodiversity loss, and heightened demands for resilience and equity.

Viewing economic systems through this broader paradigm enables economists to better explain historical patterns of technological change, anticipate future transitions, and design more effective policy interventions. In particular, it highlights the critical role of government initiatives—often characterized as industrial policies—including investments in research and development, physical infrastructure, workforce training, and, in some cases, targeted subsidies. These interventions do not replace markets; rather, they enable markets to function by empowering the private sector, overcoming classic coordination failures and chicken-and-egg problems, and accelerating the emergence of new technologies and supply chains. Such challenges are especially acute in domains such as sustainable energy, bioeconomy development, and circular material systems, where price signals alone frequently fail to induce socially efficient outcomes.

Embedding economic behavior within interconnected innovation and product supply chains offers a more realistic and policy-relevant analytical foundation. This perspective explicitly links discovery, development, scale-up, and diffusion to material flows, environmental externalities, and behavioral responses. It also clarifies how economic and biophysical systems co-evolve, producing both valued goods and unavoidable residues that must be managed. By integrating these dimensions, the emerging paradigm moves economics closer to the physical world it seeks to explain and influence.

Ultimately, ideas originating in agricultural, environmental, and resource economics—fields long considered peripheral—are now central to shaping this transition. Their multidisciplinary orientation and sustained engagement with climate change, food security, and biodiversity preservation position them to contribute to a new economic paradigm. If successfully translated into policy and institutional change, this paradigm has the potential not only to enhance sustainable development but also to support greater global stability, cooperation, and harmony.