A quick guide to post-normal science

By Silvio Funtowicz

Silvio Funtowicz (biography)

Post-normal science comes into play for decision-making on policy issues where facts are uncertain, values in dispute, stakes high and decisions urgent.

A good example of a problem requiring post-normal science is the actions that need to be taken to mitigate the effects of sea level rise consequent on global climate change. All the causal elements are uncertain in the extreme, at stake is much of the built environment and the settlement patterns of people, what to save and what to sacrifice is in dispute, and the window for decision-making is shrinking. The COVID-19 pandemic is another instance of a post-normal science problem. The behaviour of the current and emerging variants of the virus is uncertain, the values of socially intrusive remedies are in dispute, and obviously stakes are high and decisions urgent.

In such contexts of policy making, normal science (in the Kuhnian sense, see Kuhn 1962) is still necessary, but no longer sufficient. We can locate post-normal science in relation to the more traditional problem-solving strategies in the figure below. This has two axes:

  • ‘Systems uncertainties’ which conveys the principle that the problem is concerned not with the discovery of a particular fact, but with the comprehension or management of an inherently complex reality.
  • ‘Decision stakes’ which concerns all the various costs, benefits, and value commitments that are involved in the issue through the various stakeholders.

When systems uncertainties or decision stakes are small, we are in the realm of ‘normal’ science, where expertise is fully effective. When either systems uncertainties or decision stakes rise then skill, judgement and sometimes even courage are required. This is the realm of professional consultancy. And when either or both systems uncertainties or decision stakes are high this is the realm of post-normal science.

In post-normal science the problems are set, and the solutions evaluated, by the criteria of the broader communities that are affected. Nevertheless, post-normal science is a valid form of enquiry – a type of science – and not merely politics or public participation. Post-normal science has the paradoxical feature that in its problem-solving activity the traditional domination of ‘hard facts’ over ‘soft values’ has been inverted.

It is important to appreciate that post-normal science is complementary to applied science and professional consultancy. It is not a replacement for traditional forms of science, nor does it contest the claims to reliable knowledge or certified expertise that are made on behalf of science in its legitimate contexts.

In post-normal science the activity of science encompasses the management of irreducible uncertainties in knowledge and in ethics, and the recognition of different legitimate perspectives and ways of knowing. The epistemological analysis of post-normal science, rooted in the practical tasks of quality assurance, shows that such an extension of peer communities, with the corresponding extension of facts, is necessary for the effectiveness of science in meeting the new challenges of global environmental problems.

Problem solving strategies (Funtowicz and Ravetz, 1993)

Extended peer communities and quality assurance

The dynamic of resolution of policy issues in post-normal science involves the inclusion of an ever-growing set of legitimate participants in the process of quality assurance of the scientific inputs.

When problems lack neat solutions, when ethical aspects of the issues are prominent, when the phenomena themselves are ambiguous, and when all research techniques are open to methodological criticism, then the debates on quality are not enhanced by the exclusion of all but the specialist researchers and official experts. The extension of the peer community can positively enrich the processes of scientific investigation.

Knowledge of local conditions may determine which data are strong and relevant and can also help to define the policy problems. Those whose lives and livelihood depend on the solution of the problems will have a keen awareness of how the general principles are realized in their ‘back yards’. They will also have ‘extended facts’, including anecdotes and informal surveys. While they lack theoretical knowledge and are biased by self-interest, specialist researchers and official experts lack practical knowledge and have their own forms of bias.

Research science, professional practice, and industrial development each have means for quality assurance of the products of the work, be they peer review, professional associations, or the market. For the problems addressed by post-normal science, quality depends on open dialogue between all those affected.

NUSAP – The Management of Uncertainty and Quality in Quantitative Information

The notational system “NUSAP” enables the different sorts of uncertainty in quantitative information to be displayed in a standardized and self-explanatory way. It enables providers and users of such information to be clear about its uncertainties.

The NUSAP system is based on five categories, which allow each aspect of the information to be expressed in a flexible way. By means of NUSAP, nuances of meaning about quantities can be conveyed concisely and clearly, to a degree that is quite impossible otherwise. The name “NUSAP” is an acronym for the categories:

  • Numeral, which will usually be an ordinary number; but when appropriate it can be a more general quantity, such as the expression “a million.”
  • Unit, which may be of the conventional sort, but which may also contain extra information, such as the date at which the unit is evaluated (most commonly with money).
  • Spread, which generalizes from the “random error” of experiments or the “variance” of statistics. Although spread is usually conveyed by a number (either ±, % or “factor of”) it is not an ordinary quantity, for its own inexactness is not of the same sort as that of measurements.

This brings us to the more qualitative side of the NUSAP expression:

  • Assessment, which provides a place for a concise expression of the salient qualitative judgements about the information. In the case of statistical tests, this might be the significance-level; in the case of numerical estimates for policy purposes, it might be the qualifier “optimistic” or “pessimistic”.
  • Pedigree, which is an evaluative description of the mode of production (and where relevant, of anticipated use) of the information. Each special sort of information has its own pedigree. Pedigree is expressed by means of a matrix; the columns represent the various phases of production or use of the information, and within each column there are modes, normatively ranked descriptions.


In this quick guide, I have aimed to set out key insights of post-normal science. If you identify as a post-normal scientist, I would be interested to hear how you have applied these ideas in your work. I would also be interested to hear how they resonate with systems thinkers, inter- and trans-disciplinarians and others who seek to support policy making on problems where facts are uncertain, values in dispute, stakes high and decisions urgent.

To find out more:

Funtowicz, S. O. and Ravetz, J. R. (1993). Science for the Post-Normal Age. Futures, 25, 7: 739-755. Republished in 2020 in Commonplace with a new COVID-19 related foreword. (Online – Open access): https://commonplace.knowledgefutures.org/pub/6qqfgms5/release/1

For applications of post-normal science:

Buschke, F. T., Botts, E. A. and Sinclair, S. P. (2019). Post-normal conservation science fills the space between research, policy, and implementation. Conservation Science and Practice, 1, 8, e73. (Online – Open access): https://doi.org/10.1111/csp2.73

Nogueira, L. A., Bjørkan, M. and Dale, B. (2021). Conducting Research in a Post-normal Paradigm: Practical Guidance for Applying Co-production of Knowledge. Frontiers in Environmental Science. 9. (Online – Open access): https://doi.org/10.3389/fenvs.2021.699397

For an application of NUSAP:

Van der Sluijs, J. P., Risbey, J. S. and Ravetz, J. (2005). Uncertainty assessment of VOC emissions from paint in The Netherlands using the NUSAP system. Environmental Monitoring and Assessment, 105, 1-3: 229-59 (Online – Open access): http://nusap.net/intareseuncertaintytraining/envmonass2005.pdf (PDF 740KB); or, (Online): https://doi.org/10.1007/s10661-005-3697-7

Kuhn, T. S. (1962). The Structure of Scientific Revolutions. University of Chicago Press: Chicago, United States of America.

Biography: Silvio Funtowicz is guest researcher at the Centre for the Study of the Sciences & the Humanities at the University of Bergen, Norway. He is a philosopher of science active in the field of science and technology studies. @SFuntowicz.

20 thoughts on “A quick guide to post-normal science”

  1. I am watching with great interest the discussion between Silvio Funtowicz and David Wojick. Can science be post-normal? Today this is a matter of principle.
    Silvio Funtowicz is right. Modern problems have gone beyond the normal (academic) science. Therefore, from his point of view, science should become post-normal.
    David Wojick is right. It is correct to speak not about post-normal science, but about an abnormal situation in which normal science has fallen.
    In this case, we need to remember that science is represented by people who are carriers of a scientific worldview. Silvio Funtowicz and David Wojick are carriers of original ideas and opinions. But their opinions and ideas are important not only for themselves. Their opinions and arguments initiate the mental activity of other people whose scientific worldview is just being formed or is already ready to change.
    The authors of the document “UNESCO Science Report: towards 2030 – Executive Summary” (p.2) [http://uis.unesco.org/sites/default/files/documents/unesco-science-report-towards-2030-ex-sum-en.pdf] are sure that modern science is divided into four parallel directions:
    – science that carries out fundamental and applied research and produces new knowledge;
    – science that produces knowledge that is in demand in the market;
    – science working in the interests of the public good;
    – science, which is the driving force of commercial activity.
    Which direction can be considered a “post-normal science” or an “abnormal situation” in which normal science has fallen?
    I think that the complex multifactorial problems and situations that Silvio Funtowicz and David Wojick talk about are a distortion of reality near the existing horizon of the scientific worldview. Therefore, in order for unsolvable problems to turn into solvable tasks, it is necessary to expand the horizon of the scientific worldview.
    The metaphor “new horizon” hides a new picture of the world and a new paradigm. In turn, “new” does not mean “completely new”! The new picture of the world may no holistic, but unified. The new paradigm may no longer be an object one, but a system one. The model of the system may not represent a set of elements and their relationships, but rather represent the order that determines this unity. The new paradigm can strengthen normal science with systems transdisciplinarity.
    I am sure that the terms complex or post-normal science should not become independent areas of science. In this case, these directions will serve as a justification for the objective reduction of scientific (academic) rigor and situational risk analysis caused by a lack of scientific knowledge and methodological tools. But these terms should serve as prescriptive “road signs” for the further development of normal science.

    • “it is necessary to expand the horizon of the scientific worldview” I agree. If this expansion will lead to solvable tasks from unsolvable problems is to be seen.
      “Science” continues to be ambiguous & not only because it’s a process & a product but also because it has change meaning along history. Personally I’m not in favour of eliminating ambiguity but I understand that others have a different program.
      I also believe we should focus our attention beyond scientific knowledge, acknowledging a broad range of knowledges.

      • Silvio, thanks for the comment. You’re a philosopher of science. Therefore, the following reasoning will be clear to you. I think our comments should be considered in two directions.
        First of all, as you say, each of us has our own program. You’re a proponent of ambiguity. I am a supporter of unambiguity. In this case, we are the opposite of each other. Therefore, we can watch each other’s failures for a long time.
        Secondly, ambiguity and unambiguity mark the boundaries of the homeostasis of perception of complex multifactorial problems. Within the framework of this homeostasis, our constructive position will allow us to complement each other’s worldview and methodologies. Ambiguity will not allow unambiguity to fall into snobbery. Unambiguity will not allow ambiguity to fall into profanation.
        I’ll give you an example. When a cook prepares a meat dish, he uses unambiguity and ambiguity. The unambiguity lies in the fact that the cook knows the duration of the individual stages and the total cooking time of the meat. This time is strictly limited. The ambiguity lies in the fact that at certain stages of cooking meat, the cook may or may not add certain seasonings. In addition, ambiguity allows the cook to experiment and make the meat tastier. But what to do when it is necessary to solve complex multifactorial problems: environmental, climatic, social, etc.? I think it is necessary to unite carriers of unambiguity and ambiguity. The former can unambiguously describe the “recipe” for the transformation of planetary matter (a temporary and general event scenario of the development of planetary nature, which directly relates to the development of human society). The latter can offer “seasonings” to this “recipe” (to develop a variety of solutions that contribute to achieving the expected result). Wars, socio-economic crises and environmental disasters are a consequence of ambiguity, which can be eliminated by adding unambiguity. Natural disasters are a manifestation of the unambiguity of planetary development, which can be smoothed out by a variety of ways of forecasting and, possibly, prevention.
        I think it’s time to combine the possibilities of ambiguity and unambiguity and thereby gain the necessary broad range of knowledge.

        • I’m in favour of acknowledging a broad range of perspectives. Hybridisation is already happening, and hopefully it will result in better quality processes of knowledge creation than the one resulting from exclusivist positions.

    • If PNS refers to policy intensive science then there is no problem to be solved. As with scientific revolutions, the disruption just has to run its course. But I agree there are ways to improve the quality of the reasoning. Keep in mind that most science is not policy intensive, so the PNS issue does not arise.

      Sea level rise provides a good example, as governments around the world are grappling with it. I happen to be familiar with the policy debate in New Jersey. There are scientific estimates of the 2100 rise that range from a harmless one foot or less to a destructive five feet or more. Thus the science is hugely controversial. What policies the State finally adopts is not just a scientific issue.

        • Dear David, there is an important meaning hidden in your comment!
          The great philosopher said that “politics is a concentrated expression of economics.” Modern economists, and hence modern politicians, have faced difficulties in reconciling the needs of the state and the global world economy.
          Modern economists aim to overcome these difficulties. To achieve this goal, they propose to consider the economy as a system (systems economy). Systems economics is a scientific field that considers economics in the aspects of the emergence (creation), functioning, interaction and transformation of economic systems. The system is understood as a relatively isolated and stable (from the point of view of a “public observer”) part of the surrounding world, characterized by external integrity and internal diversity. The creators of the systems economy, who are only forming possible definitions and methodological tools, hope that it will be a more relevant platform for analyzing such features of the modern economy as heterogeneity, instability, multifactoriality, multilevelness, polystructurality, fractality than traditional concepts of neoclassical or institutional-evolutionary theories. It is important to note that within the framework of the systems economy, it is supposed to integrate the provisions of the main economic paradigms and theories of economic systems in the context of the space-time approach. In this context, systems economics has a lot in common with post-normal science!
          Taking into account my comment about unambiguity and ambiguity for Silvio Funtowicz, it can be assumed that internal and external political problems will be solved with the help of systems economics (post-normal economics). However, the problems of the systems economy itself will be solved using models of spatial, temporal and information units of order that are used in systems transdisciplinarity. Thus, I think that the solution of the fuzzy problems of modern society, aggravated by the lack of disciplinary knowledge, can be achieved by an alliance of at least academic (normal) disciplinary science, post-normal science and systems transdisciplinarity.
          Additional literature
          – Mokiy, V.S., & Lukyanova, T.A. (2021). Transdisciplinarity: Marginal direction or global approach of contemporary science? Informing Science: The International Journal of an Emerging Transdiscipline, Vol.24, pp. 001-018. https://doi.org/10.28945/4752
          – Mokiy, V.S. (2020). Information on the space. Systems transdisciplinary aspect. European Scientific Journal, ESJ, 16(29), 26. https://doi.org/10.19044/esj.2020.v16n29p26
          – Mokiy, V.S. (2021a). Information on the Information. Systems transdisciplinary aspect. Universum: Social sciences. 1-2(71). https://doi.org/10.32743/UniSoc.2021.71.1-2.40-48
          – Mokiy, V.S. (2021b). Information on the time. Systems transdisciplinary aspect. Universum: Social sciences. 1-2(71). https://doi.org/10.32743/UniSoc.2021.71.1-2.30-39

  2. I really appreciate the naming of “post-normal science” This phrase resonates: “The dynamic of resolution of policy issues in post-normal science involves the inclusion of an ever-growing set of legitimate participants in the process of quality assurance of the scientific inputs.” In my experience, I have not seen a policy issue related to inter-generational poverty or health inequality resolved. Rather I have seen attempts rise and fall without sufficient resolution. Perhaps I am not defining resolution the way you are, or perhaps my sense of time is too short. Can you elaborate what you mean by the “dynamic resolution of policiy issues”?
    Thank you.

    • Thank you for your comment which enables me to clarify the meaning of the statement. The actual sentence reads “dynamic of resolution…” I use resolution to signify a process rather than solution, a product. In this sense, recognising the unavoidable existence of conflicts of values and power differentials, some policy issues might not be soluble. In other words, under post-normal conditions, policy issues don’t have neat technoscientific solutions as scientism assumes.

    • I tend to think the term “post normal science” is misleading, in a way that has given it some bad press. Kuhn defined normal science as the period when the paradigm guiding a community was not controversial. His book was about a non-normal period, namely scientific revolutions. The situation described above as post normal is a different sort of non-normal one, where the science is policy intensive.

      The two non-normal cases share features. For example, Kuhn points out that proponents of different paradigms “talk past” one another, meaning they cannot come to grips with their differences. This is certainly true of the policy case as well. One of the things I study is conceptual confusions in science laden policy issues and these are common. In fact they are often required.

      The term post normal science sounds like a claim of successorship, that this form of science should somehow replace normal science. I presume this is a false confusion, because such a claim would surely be false, but it is one that detractors seem to assume. Post normal science as described above is simply an important case of non-normal science. Except the description seems to encompass the policy issues as well, which is not science at all. So I am still not clear what the scope of post normal science is. Perhaps that has yet to be determined.

      • Thank you for taking the time to read and comment. During the last 30 years, many have discussed the name and you’ll find similar criticisms to yours in the PNS Wikipedia page.
        I can add that PNS is a development of Alvin Weinberg’s trans-science (1972) in relation to policy-relevant research, and that it does not aspire to become a new normal, Method or paradigm.

        • My comment was an explication not a criticism. I do what I call “issue analysis” which describes the reasoning in a policy issue, especially (1) the arguments and (2) conceptual confusions. I suspect from what you have written that my issue analysis science is a kind of PNS. If so then I am here doing the PNS of PNS.

          Complex new ideas almost always create conceptual confusion and PNS is no exception. This confusion is the price of progress. It sounds like PNS is the science of the science in the policy issue, or perhaps the science of the entire issue. My issue analysis science is the latter. What is the scope of PNS?

          • Quite right. I really appreciate your comments helping to clarify ambiguous ideas expressed quite succinctly. I think that PNS isn’t the only proposal to reconsider science’s role when dealing with complex societal issues.

            • Surely the reasoning is central to PNS. My approach captures the different perspectives as part of a complex interacting system of ideas. NUSAP seems more piece by piece.

              As to the role of science, several basic aspects come to mind.
              1. In normal science the paradigm determines which questions are most important, while in the policy case it is the policy issues that drive the research. For example, in pure sea level rise research the amount of rise in 30 years is not particularly important but it is a central policy question which makes it a top scientific question.
              2. Research relevant to major policy issues will get extraordinary analysis and criticism, especially from those who oppose the policy. Policy is a harsh realm, where strong opinions are often held based on slight evidence. This is very different from normal science.

              This will also be true for NUSAP. The degree and nature of uncertainty are often hotly contested issues. In fact there may be more epistemic issues than scientific ones.

        • Silvio, in our discussion above you say “On NUSAP, see Funtowicz, S & Ravetz J 1990, Uncertainty and Quality in Science for Policy. Open access in https://bit.ly/3b1RLOI”

          This is a 238 page book so well beyond the scope of the present discussion. Reading a bit up front suggests the following observations.

          First, NUSAP estimates will be subject to the same disagreements and uncertainties as other research results in the policy debate. In fact the degree of uncertainty is often the greatest uncertainty. Those who favor the policy say there is sufficient certainty while those who oppose it say there is not. Sea level rise is an excellent example.

          Second, complex science intensive policy issues typically involve several thousand distinct claims, in an issue tree structure, most of which are controversial. It is hard to imagine that adding NUSAP estimates to each of these claims would be useful, much less decisive. In simple cases yes, but not in the typical complex policy case.

  3. I love this – highly relevant to our area – thank you. Our group is seeking to address the issues you are talking about through better valuation (quant/econ, but also qual and in its broadest sense), clear understanding of decision-making across range of actors (inc. timing, underlying values, motivations, interests, etc.), and targeted intervention and evaluation. An area we’ve skirted around repeatedly, but yet to bring in fully, is risk/risk management. https://www.tandfonline.com/doi/full/10.1080/23748834.2020.1811480 / I’ll pass this on to our group.


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