Post-Normal Science

Zora Kovacic and Silvio Funtowicz

Related terms: complexity, decision, description, hazard, negotiation, normativity, policy, risk, science, uncertainty

Concept, Context, and Contemporary Relevance

‘Post-normal science’ (PNS) emerged from the study and theorization of strategic responses to the growing inadequacy of traditional scientific approaches in addressing complex, high-stakes societal challenges. Alongside concepts such as “mode 2 science” (Gibbons et al. 1994) and “citizen science” (Irwin 1995), it contributes to rethinking epistemological and institutional alternatives to the positivist ideal of science as an apolitical, objective, and certainty-producing enterprise.

The foundational claim of PNS – that when “facts are uncertain, values in dispute, stakes high, and decisions urgent” (Funtowicz and Ravetz 1993) – has gained increasing salience in a world marked by crises and systemic transformations. PNS has developed in close dialogue with environmental concerns. As Wynne (1992) argues, the goal of preventing environmental damage shifts the science–policy interface away from a situation in which damages are well known and documented ex post, toward a different predicament of partial knowledge, unpredictability, and indeterminacy before potential harms play out.

‘Risk’ is commonly defined as the product of the probability of an event and its harmful impact. Within risk analysis, considerable attention is given to estimating probabilities and assessing the uncertainty associated with these estimates. ‘Uncertainty’ is often framed as a problem of insufficient knowledge or data to produce robust probability estimates, or as the fallibility of the models used to estimate the probability of events that deviate from a normal distribution. Similarly, ‘harmful impact’ must be quantified to calculate risk, which reduces harm to measurable variables. By introducing the concepts of ‘systems uncertainty’ and ‘stakes’ (see Fig. 1), PNS broadens the risk analysis framework and brings issues of values, ignorance, and indeterminacy to the forefront.

Rooted in the critical reflections of Silvio Funtowicz and Jerome R. Ravetz, the term ‘post-normal’ is a deliberate inversion of Thomas Kuhn’s ‘normal’ science - the routine, puzzle-solving research work conducted within a dominant paradigm (Kuhn 1962). In Kuhn’s framework, the paradigm prescribes legitimate problems and acceptable methods and excludes dissenting perspectives. By contrast, contexts characterized by irreducible uncertainty and a diversity of legitimate perspectives are conceptualized as ‘post-normal.’ The societal consequences of science are no longer considered accidental by-products but central to its practice.

The 1993 article “Science for the Post-Normal Age” (Funtowicz and Ravetz 1993) stands as a landmark contribution in the history of science studies and remains the most cited paper in the journal Futures (Groves and van der Duin 2025). Since its publication, successive generations of scholars and practitioners have drawn on and developed the post-normal science framework across a widening range of fields. Despite its growing uptake, PNS remains an alternative and relatively marginal conceptualization of science rather than part of the mainstream, and it has elicited mixed reactions. Over the past decade, debates over scientific integrity, demarcation, and uncomfortable knowledge have spilled beyond academic circles and entered the public arena, exemplified by marches for science, alarms about a post-truth era, and widespread concerns about misinformation.

Some equate PNS and its focus on diverse ways of knowing with a form of relativism – a misunderstanding that is perhaps unsurprising in a context of increasing political polarization, where scientific ‘truth’ is often conflated with a particular political stance. Yet, PNS underscores the distinction between relativism and complexity: it recognizes that the complexity of societal challenges demands a plurality of legitimate perspectives and knowledge forms to address problems that transcend any single disciplinary or cultural framework. Speaking of ‘PNS’ in times of post-truth may even seem hazardous. In this environment, prominent scholars of science studies, such as Bruno Latour, famously changed heart – shifting from critiquing science to explicitly supporting scientific claims about issues like climate change (Latour 2004).

From a PNS perspective, the idealization of science is just as problematic as the rise of post-truth. When difficult political decisions are reduced to technical puzzles to be solved by science, science risks being captured by political agendas. Under conditions of complexity, science does not speak with one voice, and scientific facts alone cannot resolve challenging political issues. Invoking science in such situations tends to foster technocracy at the expense of democracy. The PNS analytical framework, with its emphasis on the interdependence of facts and stakes, provides a way to understand the heightened tensions in science–society relations (Funtowicz and Ravetz 2025).

The heuristic diagram of PNS (Figure 1) – mapping systems uncertainty against decision stakes – illustrates how, in the transition from routine research to professional consultancy and to the extended realm of post-normal science, the recognition of the limitations of scientific knowledge in society results in different practical configurations of science–society relations. In domains with high uncertainty or high stakes, neither textbook science nor expert consultancy is sufficient. Instead, post-normal conditions call for the inclusion of extended peer communities: ordinary people who bring valuable experiential and contextual knowledge. These communities do not merely receive scientific information; they co-create it, challenge assumptions, and shape the framing of problems and solutions (Kovacic and Funtowicz 2024).

One illustrative domain is that of popular epidemiology, where communities affected by environmental contamination have mobilized to investigate health hazards and challenge official accounts (Fjelland 2016). In such contexts, non-expert actors gather data, reinterpret scientific findings, and assert the credibility of lived experience. These practices exemplify the analytical and normative core of PNS: under high uncertainty, the distinction between expert and non-expert knowledge blurs, and the quality of decision-making depends not just on scientific evidence but on processes of inclusive deliberation (Bidwell 2009; Haklay 2023). PNS is operationalized on two levels: analytically, it theorizes science outside of normal practices; normatively, it calls for the extension of peer communities.

Yet the shift toward inclusion, diversity, and participatory engagement is not without its own difficulties. Conflicts may emerge between established authorities and new voices, as entrenched actors resist sharing power or altering fixed decision-making structures. Within communities themselves, divisions rooted in historical grievances, unequal influence, or differing worldviews can disrupt efforts toward resolution. In some cases, individuals or institutions may be perceived as obstructive or illegitimate – not just due to past associations, but because their continued involvement deepens mistrust and polarizes discourse. These tensions challenge the stability and cohesion of participatory processes. Moreover, the complexity and open-endedness of many post-normal problems defy resolution through singular policies or fixed solutions. They demand long-term engagement, repeated compromises, and a willingness to revisit assumptions, goals, and alliances in response to evolving conditions and understandings.

At the science–policy interface, institutions such as the United Nations Environment Programme (UNEP), the European Commission Joint Research Centre (JRC), and the European Environmental Agency (EEA) are increasingly incorporating PNS insights and language. As UNEP (2025) emphasizes, the post-normal nature of today’s environmental challenges demands policy responses that bridge scientific knowledge with societal needs. Addressing such issues requires not only technical expertise but also the inclusion of diverse stakeholder perspectives and adaptive governance capable of responding to evolving conditions. In the context of polycrises and systemic risk, institutions such as the European Commission and the EEA have shown openness to PNS framings – although PNS may not be seen as an alternative to be embraced, but a necessary and perhaps temporary remedy that helps navigate times of crises. The JRC’s Science for Policy Handbook (2020), the SAPEA report Making Sense of Science for Policy Under Conditions of Complexity and Uncertainty (2019), and the EEA’s Governance in Complexity (2024) all reflect an opening toward more open, iterative, and deliberative forms of research and governance – moving beyond linear, expert-driven models to embrace the complexity of real-world problems.

‘Complexity’ is defined in post-normal science as an epistemic condition created by the existence of multiple non-equivalent representations of a problem (Rosen 1977), which are not reducible to one another. The oft-cited idea that in a complex system, the whole is more than the sum of its parts, speaks of the need of multiple representations (of the whole and of the parts) and of the non-equivalent insights produced by each representation (the parts produce a total as well as something more, which can be characterized as emerging properties, non-linearity, feedback loops, etc). From this perspective, real-world complexity is not just a reference to interlinked challenges such as compounding environmental, economic, geopolitical, and health crises. Real-world complexity is also an epistemic challenge: it emerges when science does not speak with one voice, when complex problems lack a unique solution, and when participatory deliberative processes fail to produce consensus.

Consider, for example, the long-standing controversy over radioactive waste disposal at the Sellafield site in the UK. Technical uncertainties, combined with deep public mistrust and value-based disputes over safety, equity, and environmental justice, created a governance challenge that could not be resolved by expert analysis alone. The case became a landmark in demonstrating the importance of extended peer communities and participatory processes, as recognized in early PNS literature (Wynne 1992; Funtowicz & Ravetz 1994). Another illustrative case is provided by Giatti’s work on participatory research in Brazil, where knowledge co-production processes engaged marginalized communities, scientists, and public institutions in addressing socio-environmental challenges. These efforts emphasized dialogic learning, reflexivity, and the empowerment of local actors through shared inquiry and situated knowledge (Giatti 2019). In both contexts, the application of deliberative approaches consistent with post-normal science has served to enhance the quality, legitimacy, and resilience of decision-making under conditions of complexity and contested values.

PNS does not reject the idea of truth; rather, it repositions it within a more modest, situated, and inclusive conception of knowledge – one that treats quality as contextual, dialogic, and negotiated. In a world where scientific claims are contested not only on empirical grounds but also on social, ethical, and political ones, this repositioning is not a weakness but a source of strength. PNS does not offer ready-made solutions to complex problems. Instead, it proposes taking seriously modes of engagement attuned to situations that are uncertain, value-laden, and charged with high stakes. Scientific practices, from this perspective, are considered high-quality not because they produce certainty or consensus, but because they are self-aware, responsive, and open to plural viewpoints and ongoing revision. Here, ‘quality’ emerges through practices that ask critical questions: How is knowledge produced? By whom? For what purposes? And under whose terms? In doing so, PNS – particularly in its normative interpretation – advocates for a more democratic, reflexive, and humble practice of science: one capable of meeting the challenges of a post-normal age.

Understanding the contexts in which science operates today requires addressing the convergence of multiple, interlocking disruptions that span ecological, economic, social, and institutional domains. Rather than unfolding as discrete events, these crises compound over time, feeding into each other and magnifying systemic instability. A clear example is the ongoing deforestation of the Amazon rainforest. Driven by global commodity markets, agribusiness expansion, weakened environmental governance, and political contestation, deforestation accelerates biodiversity loss, intensifies climate change, and disrupts the hydrological systems that sustain agriculture and energy production across South America. At the same time, it threatens indigenous livelihoods and fuels social conflict. Addressing such complex and contested issues requires interfaces between science and society that go beyond conventional expert models –incorporating local knowledge, ethical reflection, and participatory engagement (Guimarães Pereira et al, 2006). Similarly, Turnhout, Dewulf, and Hulme (2016) emphasize that policy-relevant knowledge for global environmental problems like Amazon deforestation must be reflexive, co-produced, and responsive to plural values. These insights resonate with the broader framework of dynamic sustainability proposed by Leach, Scoones, and Stirling (2010), who stress the need for adaptive and socially just approaches to navigate uncertainty and contestation. In such contexts, PNS offers both a diagnostic and a normative stance: recognizing the limits of prediction and control, while fostering inclusive, deliberative, and context-sensitive responses.

PNS does not seek to define ‘science’ as a fixed or universally participatory endeavor. Rather, reflexively rethinking ‘science’ calls for engagement with complexity as a means of studying knowledge creation practices in all their diversity – to stay with the uncertainty, the diversity, and the discomfort that accompany real-world governance. Under post-normal conditions, governance must be iterative and adaptive, involving not only technical judgement but also humility, pluralism, and openness to alternative ways of knowing. Rather than pursuing closure through premature consensus, the PNS framework supports approaches that foster collective learning – approaches that remain sensitive to power differentials, competing values, evolving understanding, and the contingencies of lived experience. Shifting the terms of the debate about science and its responsibility in facing humanity’s challenges away from choosing between collapse and transformation may help us navigate the spaces in between, where small shifts, negotiated compromises, and shared responsibilities take root.

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