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In addressing the local pandemics science has never seemed more needed and useful, while at the same time limited and powerless. The existing contract between science and society is falling apart. A new covenant is urgently needed to navigate the days ahead. Co-authors: © David Waltner-Toews, Annibale Biggeri, Bruna De Marchi, Silvio Funtowicz, Mario Giampietro, Martin O'Connor, Jerome R. Ravetz, Andrea Saltelli, Jeroen P. van der Sluijs. NOTE: This article was first posted on the ESRC STEPS Centre blog. The present version is slightly updated, with some additional topical links, from the original STEPS version.
This article was first posted on the ESRC STEPS Centre blog.
The present version1 is slightly updated, with some
additional topical links, from the original STEPS version.
In addressing the local pandemics science has never seemed
more needed and useful, while at the same time limited and
powerless. The existing contract between science and
society is falling apart. A new covenant is urgently needed
to navigate the days ahead.
© David Waltner-Toews [1], Annibale Biggeri [2], Bruna De Marchi [3], Silvio Funtowicz [3], Mario
Giampietro [4.5], Martin O'Connor [6,7], Jerome R. Ravetz [8], Andrea Saltelli [3,9], Jeroen P. van der
Sluijs [3,10]
[1] Emeritus Professor, Department of Population Medicine, University of Guelph, Guelph (Canada).
[2] Professor of Medical Statistics, Università degli Studi di Firenze (Italy).
[3] Centre for the Study of the Sciences & the Humanities (SVT), University of Bergen (Norway).
[4] Universitat Autònoma de Barcelona (Spain).
[5] Catalan Institution for Research and Advanced Studies (ICREA), Barcelona (Spain).
[6] Président & Programme Manager, L'Association ePLANETe Blue (France).
[7] Graduate School BASE, Université de Paris Saclay (France).
[8] Institute for Science, Innovation and Society (ISIS), University of Oxford (United Kingdom).
[9] Universitat Oberta de Catalunya (Spain).
[10] Utrecht University (Netherlands).
On 19 May 1986, The Guardian published an essay entitled “Disasters bring the technological
wizards to heel: Chernobyl, Challenger, and the Ch-Ch Syndrome”. At that time the essay’s authors,
two of whom are co-authors of this article, wrote that it was “no longer feasible for ruling elites to
employ experts for persuading the public that their policies are beneficial, correct, inevitable, and
safe. The Ch/Ch Syndrome amounts to a mortal blow at the scientistic foundation for the legitimacy
of the modern mega-technological State. A new social contract of expertise is now taking shape.”
Not long after this, in 1993, Silvio Funtowicz and Jerry Ravetz published a landmark paper on what
came to be called Post-Normal Science (PNS), a new understanding of science for situations “when
facts are uncertain, stakes high, values in dispute and decisions urgent”. The perspective of PNS –
neither value-free nor ethically neutral – is epistemological as well as practical and methodological.
But after BSE, foot-and-mouth disease, SARS, H1N1, and a string of other, similar disasters that
would have seemed to be exactly the sorts of situations PNS was designed to address, after
energetic debates at scholarly conferences and reputable journals – where is that mortal blow? In
the middle of a COVID-19 pandemic, where is that new social contract?
The “mortal blow” seems to have been followed by a slow agony, but not yet death. Despite the
truly historic mobilization of science, our knowledge in crucial areas is still swamped by ignorance,
especially on the sources of the virus but also on its progress and future outcomes. The expertise
employed in COVID-19 policy advice builds, at best, on speculative assumptions on the virus itself,
and how far it’s possible to control and predict how people behave. Unresolved divergences of
perspective expressed by recognised experts as regards the usefulness, limits and dangers of such
speculations (e.g. Ioannidis, Crane, Taleb), fuel the public’s experience of improvisation and
Known unknowns include, at the time of writing, key elements of epidemiology such as the real
prevalence of the virus in the population; the role of asymptomatic cases in the rapid spread of the
virus; the degree to which humans develop immunity; the dominant exposure pathways; the
disease’s seasonal behaviour; and also key societal factors such the time to deliver global availability
of an effective vaccine or cure; and, above all, the nonlinear (potentially chaotic) responses of
individuals and collectives, at all scales, to the stresses and confusions associated with: the social
distancing interventions; the overload of hospital and public health service capacities; the reduction,
closure or disappearance of businesses and jobs…. Formally, we could speak of instabilities in the
complex system of communities interconnected across multiple scales, with many tipping points,
and hysteresis loops, implying that societies may not be able to rebound to anything like the state
that they were in before the coronavirus interventions took place. These deep uncertainties make
quantitative predictions speculative and unreliable. Correspondingly, reflective commentators signal
deeply contrasting scenarios of plausible futures for humanity.
‘There is no number-answer’
We see here a pattern well known to PNS practitioners. Predictions which purportedly “jarred the
U.S. and the U.K. to action” are obtained by mathematical models that produce crisp numbers, even
though these numbers have been obtained only at the cost of artificially compressing the associated
uncertainties. "There is no number-answer to your question," explodes an angry medical expert to
the politician trying to force a number out of him.
And yet the example of Taiwan shows that the post-normal model of deployment of science in
society, one where trust, participation and transparency are carefully nurtured in the face of deep
indeterminacies, can indeed deliver upon its promises.
The possibility of economic collapse, with associated social breakdown, is quite real, and is now (late
March 2020) a matter of daily, if not hourly, commentary in every daily news outlet. And in fact, we
seem to be far away, in our technology and governance prowess, from societies that would be
capable to guarantee an absolute prediction and control over whatever types of perturbations we
may experience in the future. Given this, it would likely be much more effective to run our societies
on the basis of a quest for resiliency and not under the assumption that our resources should be
allocated according to a strategy of prediction and control.
Everywhere, we are seeing a breakdown of the epistemic consensus required to make normal
science ‘work’. This is happening not only in the fields you might expect – behavioural psychology,
sociology, and ethics – but also in virology, genetics, and epidemiology. In other words, when
‘applied scientists’ and ‘professional consultants’ are no longer in their comfort zones but find
themselves in a ‘post-normal’ context, fitness for purpose changes meaning. Today, even in
established fields, disagreements can’t be hidden (or consensus enforced) from broad audiences: so
dissent and controversy abounds around the question: are the present draconian measures justified
or not?
More data (even ‘reliable data’) and better predictive models cannot resolve the ‘distribution of
sacrifice’ which involves, among other things, the arbitration of conflicts and dilemmas that appear
at every scale. Hiding behind some general notion of science, or behind the ‘lack of data’ – as if data
had the power to resolve these dilemmas – is feckless, feeble and confused.
How do different perspectives help?
Normal Science has demonstrated great power in identifying viral structures, attachment sites, and
pathogenic mechanisms. All these are essential for medical diagnostic and treatment regimes.
However, to answer questions related to managing these technologies, including setting priorities
when, for instance, respirators and hospital beds reach their limit, and for identifying how to
reorganize institutional structures, Normal Science offers no guidance at all.
The design of the campaign, with the balancing of imponderable costs and benefits, will engage a
variety of legitimate perspectives and valuations; political leadership is required for choosing among
the resultant policies. The ripple effects through the levels of policy and consciousness, may well
become much more severe than the initial dangers. How will existing social tensions, as between
elites and anti-elites, be refracted through this crisis?
The new, still-emerging social contract calls on us to pause in our vocal desperation to make the
square peg of normal science fit a round hole for which it was never intended, and to re-shape our
activities to fit the new reality. What if we experience, this time, more so than previously, that we
are not in control? Are we condemned to do “more of the same” forever until we’re forced to do
something else by the events (because of a collapse)?
In response to this conundrum, PNS suggests considering a new objectivity, one obtained (we
daresay constructed) by listening to different stories and viewpoints. The PNS diagnosis asks for
more, not less, deliberative democracy. It asks for mobilizing and engaging everyone affected in a
situation of crisis into an ‘extended peer community’, fostering individual and collective agency for
social learning, instead of technocratic optimization of disempowered people into the virtual reality
of assumption-laden model projections under deep ignorance and based on a very limited set of
institutionally-privileged forms of expertise.
Under post-normal conditions, the knowledge base should be pluralized and diversified to include
the widest possible range of high-quality potentially usable knowledges and sources of relevant
wisdom, without enforcing the demand for science to speak with one voice. "Robustness is sought
here primarily in policy strategy and not in the knowledge base: which policies are useful regardless
of which of the diverging scientific interpretations of the knowledge is correct." An illustration of
this approach in the context of the present discussion came when the Council of Europe usefully
contested the evidence and the policy of the World Health Organization in relation to the H1N1
influenza, and – according to some researchers – did so using a post-normal-informed analysis.
WHO polices were later considered as ill-advised, and possibly biased, by industrial stakeholders.
What does a post-normal approach look like?
The inevitability of accidents and epidemics is ‘uncomfortable knowledge'. Confronting it is a moral
act as much as a policy decision. Through PNS, we imagine strategies based on a wise monitoring
and anticipation obtained by a combination of non-equivalent perceptions of our interaction with
This cannot be delivered by artificial intelligence, algorithms and models alone, nor can the
dystopian aspects of these latter be redeemed by the results of the Chinese response to COVID-19.
We need to pursue an adaptability based on attention to “weak signals”, preserving diversity and
flexible management.
Until now, science has been used to improve the quality of life for some social groups, give people an
edge on their competitors (for some social groups and countries) and to replace religion as the
source of legitimization of power (ditto). It has now become apparent that specific social groups
that have enjoyed the ride so far are now fighting with every political and economic weapon possible
to regain control and direct the narrative.
Nonetheless, this pandemic offers society an occasion to open a fresh discussion on whether we now
need to learn how to do science in a different way. Conscientious scientists and engaged citizens
cannot allow this opportunity to pass.
In PNS, the whole world becomes an extended peer community, as the appropriate behaviour and
attitudes of individuals and masses become crucial for a successful response to the virus. This
extended peer community is the opposite of a technocratic, number and model-based decision
strategy. It’s a community where all those with an interest have a say, from the experts of various
scientific disciplines, to stakeholders, whistle-blowers, investigative journalists, and the community
at large.
Coauthors’ Websites & Twitter accounts:
David Waltner-Toews
Annibale Biggeri
Bruna De Marchi
Twitter : @BDMarchi
Silvio Funtowicz
Twitter: @SFuntowicz
Mario Giampietro
Martin O'Connor
Jerome R. Ravetz
Andrea Saltelli
Twitter: @andreasaltelli
Jeroen P. van der Sluijs
Twitter: @Jeroen_vdSluijs
ResearchGate has not been able to resolve any citations for this publication.
Ravetz www.jerryravetz
  • R Jerome
Jerome R. Ravetz