Mess in Science and - Recherche en IA spécialisée au MIT

Mess in Science and
Wicked Problems

Jutta Schickore
Department of History and
Philosophy of Science and Medicine,
Indiana University

This paper discusses the claim that science is “messy.” Part I argues ﬁrst, que
a good portion of today’s discussions about messy science is just a portrayal of
familiar features of science in new terms. In the paper, I refer to this as “messy
science talk.” Second, Part I draws out rhetorical functions of messy science
talk, namely the denigration of science in the popular media and the celebra-
tion of the maverick. Part II identiﬁes one way in which it is enlightening to
think about mess in current science, namely in reference to the problems that
scientists need to address. It also shows that we do not need an entirely new
conceptual inventory to analyze these problems. “Mess” and “wicked problems”
were a theme in operations research and theories of social planning in the
1970s. These older analyses can illuminate important characteristics of
today’s scientiﬁc problems. Wicked problems cut across different disciplines,
engage different stakeholders (including non-scientists), are ﬂuid, and cannot
even be clearly formulated. They are urgent and need to be addressed before
sufﬁcient evidence is in.

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Introduction

1.
Nowadays, we often hear, or read, about “mess” or “messiness” in science. Dans
books like Helga Nowotny’s An Orderly Mess (2017), messiness is described

I presented a very preliminary draft of this paper at the 16th International Congress on
Logic, Méthodologie, and Philosophy of Science and Technology (CLMPST 2019, Prague)
as part of a Symposium of the Joint Commission of the International Union of History and
Philosophy of Science and Technology, organized by Hasok Chang (symposium) and Katie
Kendig (session). I warmly thank the organizers for inviting me and the session participants
for their helpful comments and questions. I am most grateful to Yves Gingras for his
incisive comments on the penultimate version of this paper, which helped me bring the
argument into its ﬁnal form.

Perspectives on Science 2020, vol. 28, Non. 4
© 2020 by The Massachusetts Institute of Technology

https://doi.org/10.1162/posc_a_00348

482

Perspectives on Science

483

as the new background condition of science, society, and our personal lives.
John Law’s After Method: Mess in Social Science Research (2004) calls for new
research methodologies better to accommodate a messy world. Il y a
blogs and articles discussing messy science (Aschwanden 2015; Gould
et autres. 2014). Mess even appears as a lemma in scientiﬁc encyclopedias
(Ferrales 2020). Science educators state that messiness should be fore-
grounded in science teaching (Metz 2005, 2014; Turner and Khalilah
Shamsid-Deen 2005). Sometimes messiness is invoked to suggest that es-
tablished philosophical concepts and arguments are not very useful for the
analysis of science (Currie 2014; Lipton 1999). Nevertheless, the claim that
there is mess or messiness in science is rarely spelled out in detail, et le
implications of messy science for philosophy of science also remain vague.
Is science messy? And if so, is this really a novel insight, or is “messy” just
a new label for well-known features of science? Sometimes, ﬁnding or
devising new concepts for characterizing things, activités, processes, events
etc.. can be enlightening because the new concept captures a feature of that
chose, event, etc.. that had not been noticed or properly understood before.
Sometimes, the adoption of a new analytic term, par exemple., “exploratory experi-
mentation,” is felicitous in this regard. Yet it is not always the case that the
process of giving a new name to a practice generates novel analytical insights
or explanations (Gingras 2010).

The notion of messy science certainly does generate a raft of questions. Is
all science messy or just some? Is current science messier than past science? Is
messy science bad science or good science? Does messiness in science make
philosophical analysis less useful to science, and if so, what could be done to
make philosophy more relevant to science? Does messy science require a
renovation of philosophy of science; does it even make philosophy of science
superﬂuous altogether? These questions sound worthwhile at ﬁrst; still, it is
prudent to ask: Do the designations “mess in science” or “messy” have any
surplus value for science studies?1 Or are they really just re-naming some-
thing we already know and have discussed, are they perhaps even trivial ideas
in a fancy―untidy―dress?

In Part I of this paper, I show that a signiﬁcant part of today’s concern
with mess in science is just shorthand either for familiar characterizations
of scientiﬁc practice or for challenging the normative claims or conceptual
inventory of philosophy of science. In the paper, I refer to this kind of short-
hand as “messy science talk” because it oversimpliﬁes and thus obscures
rather than enlightens. I also draw out the main rhetorical functions of messy

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In this paper, I use “science studies” as an umbrella term for philosophical, histor-

ical, cultural, sociological…analyses of science.

484

Mess in Science

science talk, namely denigrating science in the popular media and celebrating
the maverick.

In Part II, I take my cue from operations research and theories of social
planning in the 1970s. À ce moment-là, it was common to characterize certain
research problems as “messy” or “wicked”―not just hard, complicated, or ill
conceived. Drawing on this literature, I argue that these older analyses of the
features of messes or wicked problems can illuminate today’s science.
Speciﬁcally, they can capture important characteristics of today’s scientiﬁc
problems and help pin down what is special about them. Encore, given the
looseness of current messy science talk, I recommend that we should stick
to the original language and characterize these problems as wicked rather
than messy. In conclusion, I suggest that the philosopher’s problem of
how to analyze science might itself be a wicked problem.

2. A Starting Point
I want to begin with a rather old-fashioned notion of philosophy of science
and its role for science, namely Hans Reichenbach’s notion from Experience
and Prediction. Many philosophers of science today will consider it outdated. je
am not endorsing it, but it is a useful foil against which to clarify and illus-
trate what is at stake in some discussions about messy science, and whether
the recent discussions about it are really bringing up anything new.

According to Reichenbach, science in the making (by which he meant
just thinking, not doing) encompassed “rather vague and ﬂuctuating pro-
cesses [lequel] almost never keep to the ways prescribed by logic and may
even skip whole groups of operations which would be needed for a complete
exposition of the subject in question” (Reichenbach 1938, p. 5). Philosophy
of science “intends to construct thinking processes in a way in which they
ought to occur” (p. 5). Autrement dit, scientiﬁc thinking is deﬁcient, et
philosophy of science provides the best tools to complete the task of science.
As Reichenbach put it, philosophy of science [he used epistemology] gives
“a better way of thinking than actual thinking” (p. 6). He also emphasized
the “great distance” between logic and actual thinking. It would thus be a
“vain attempt” to construct a theory of knowledge that would be at the
same time “logically complete and in strict correspondence” with actual
thought processes (p. 5).

In short: 1) Scientiﬁc activity is essentially “thinking.” 2) Scientists’
thinking is “rather vague and ﬂuctuating.” 3) Scientists’ thinking needs to
be tidied up. 4) It’s the job of philosophy of science to do this, to “replace actual
thinking by such operations as are justiﬁable, c'est, as can be demonstrated as
valid.” (p. 7; emphasis added). The underlying assumption is that the world is
logically ordered and as such, knowable. Philosophical analysis is required to
uncover this order. 5) We therefore should not expect that the ﬁnal

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Perspectives on Science

485

philosophical exposition of scientiﬁc activity will correspond with actual
scientiﬁc thinking.

On Reichenbach’s view, day-to-day science is less-than-ideal science
(“vague and ﬂuctuating” thinking). In what way and why scientists’ thinking
is “vague and ﬂuctuating” are questions outside the scope of philosophy.
Nevertheless, philosophy of science is eminently important to actual science.
Reichenbach envisioned that philosophical reconstruction of scientists’
thinking completes the project of understanding the world and its logical
order, leaving actual scientiﬁc practice behind. The tacit assumption here is
that the world is, in fact, ordered.

3. Night Science
Revisiting the Reichenbachian view is useful because it provides a back-
ground against which we can sort out different charges tied to the claim
that science is messy and against which we can distinguish the well-worn
from the novel. Consider, par exemple, the claim made by science educators
that scientiﬁc practice is messy. If they do not just make the innocuous
point that science activities for kids should be fun, they typically highlight
the difference between the lab class that is part of a science student’s
education and the real-world research lab. The editor of the journal The
Science Teacher observed: “…we all look for straightforward, easy-to-manage
lab activities that verify a scientiﬁc principle, preferably within an hour’s
temps. Labs that produce clear and unambiguous results in a short timeframe
are appealing, but at what cost? Science itself is a messy process… scientists
rarely conduct investigations that can be completed in an hour or so, où
a predetermined answer is achieved simply by following directions” (Metz
2005). Ici, “messy” practice means something like “emulating the real
research world, yet inconvenient for science teachers.” In teaching contexts,
students will typically experience and replicate demonstration experiments
and learn textbook knowledge; they rarely experience the “night science”
that “wanders blind” and “hesitates, stumbles, recoils, sweats, wakes with a
start” ( Jacob 1998, p. 126).2 On this view, messy is a diagnosis of how
science―day-to-day science―is. Day-to-day science is not as well-ordered
or tidy as science textbooks suggest, as non-scientists may assume, or as
misguided ideas about “The Scientiﬁc Method” may lead one to expect.
Actual research is tortuous, not straightforward, produces imprecise and
ambiguous, not clear and unambiguous results; it takes a long time, not just
an hour, and is roving and roaming, not following a discernable linear path.
The diagnosis that actual research is messy is not terribly enlightening.
For professional analysts of science and scientiﬁc practice, the realization that

Jacob owes the distinction between night science and day science to Gaston Bachelard.

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486

Mess in Science

day-to-day scientiﬁc activity falls short of epistemic ideals is old news. Le
science educators’ diagnosis that scientiﬁc practice is messy is in fact a reiter-
ation of the same point that Reichenbach already made about vague and ﬂuc-
tuating scientiﬁc thinking, yet it is couched in new terms and re-evaluated.
Calling science messy is to cast into question those of us who thought that
proper scientiﬁc practice is as well ordered, systematic, and methodical as
the science textbook suggests…but who would still defend these assumptions
nowadays? In the diagnostic mode, the notion “messy” does not pick out spe-
ciﬁc features of objects, concepts or practices. Plutôt, the designation “messy”
for day-to-day practice is typically given ex negativo, messy means not certain,
not uniﬁed, not strictly general, not predictable, not precise, etc.. In the diag-
nostic mode, the term “messy science” reminds us that in day-to-day practice,
scientists don’t always follow a straight investigative pathway; their argu-
ments are not always completely logical, their terminology is not always pre-
cise, research problems are not always well-deﬁned.

This was once an important point to make in science studies, namely in the
early days of ethnographies of laboratory work (par exemple., Knorr-Cetina 1981), de
studies of research notebooks (par exemple., Holmes et al., éd.. 2003), and the discovery
processus (Holmes 1974, 1991). Dans 1979, Bruno Latour and Steve Woolgar, pour
instance, described laboratory life and scientists’ opportunistic and ad hoc
ways of conducting research in (alors) unusual detail; analyzing how the lab
members attempted to create order out of seemingly bewildering conglomer-
ates of materials, devices, and inscriptions (Latour and Woolgar 1979). Ils
teased their readers not so much by providing lots of details but by using eco-
nomic models and anthropological terms for their account of the opportunistic
and ad hoc processes of knowledge generation they reported to have observed
at the Salk Institute, thus provoking all those readers who might have thought
that everyday science is somehow detached from, and superior to other social
pratiques. They nettled some of their readers quite effectively.3

Since the 1970s, lab ethnographers have often described the ad hoc, oppor-
tunistic ways in which scientists approach research problems: how they use
whatever resources happen to be available in the lab to ﬁnd solutions to the
problems they are trying to solve. Inspired by Harold Garﬁnkel’s Studies
in Ethnomethodology (1967) or Claude Lévi-Strauss’s anthropology, ils
introduced various terms to characterize this practice, such as “tinkering” or
“bricolage.”

Aujourd'hui, the larger point―the point that day-to-day scientiﬁc activity does not
have to be, and typically is not, neatly ordered to generate new knowledge―is
widely accepted. Simply describing day-to-day scientiﬁc practice as messy is, dans

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See also Latour’s “Cartesian” study Science in Action, which is modeled―tongue in

cheek―after Descartes’ Principles of Philosophy (Latour 1987).

Perspectives on Science

487

fact, black-boxing it, thereby obscuring the more speciﬁc insights analysts have
gained about it in the last few decades.4

4. Normative Philosophy of Science is Presumptuous
There is another brand of messy science talk that is directed against normative
philosophy of science. Encore, it is helpful to consider this charge against the
background of the Reichebachian position. On Reichenbach’s view, science
needs philosophy of science as an aid to realize its goal to provide an accurate,
complete epistemic account of the natural world. Philosophers of science
complete the task of science by making scientiﬁc thinking even less “vague
and ﬂuctuating” than scientists’ own reconstructions of their arguments do.
The notion that science is messy sometimes encapsulates the claim that
normative philosophy of science is presumptuous in its goal to tidy up scientiﬁc
thinking and to complete the task of science.

What is at stake here is who is in a position to decide what messy or properly
ordered science is. Who has that authority―scientists or non-scientists? Et
what warrants this authority? In this context, the notion of messy science
strikes me as gratuitous. Analysts of science do not have to subscribe to any
particular notion of messy (or indeed well-ordered) science to reject normative
philosophy of science.

Notably, in some areas of gender and identity studies, this move against nor-
mative frameworks for knowledge-making takes on a more iconoclastic function,
as it is combined with a charge against the framework itself and against efforts to
apply and enforce it. The concern about the legitimacy of normative philosophy
re-emerges in gender studies as a broader challenge against “binary logics.” The
International Encyclopedia of Human Geography, par exemple, features an entry
“Mess.” In it, the practice of focusing on mess is described as a methodological
choice and as a critical stance from which to characterize established (“Western”)
ways of knowing and seeing and to identify these “binary” and “linear” logics as
practices of ordering, tidying up, controlling, et, as such, acts of suppression
(Farrales 2020, p. 62; see Manalansan 2015). Ici, the critique of logicist frame-
works for the reconstruction of knowledge becomes an act of unmasking the
hidden ideological purposes of certain methodological assumptions – their power
to suppress certain social groups and their practices. Logicism and formalism are
revealed as norms that dominate, override, or annihilate.5 Mess is presented as a

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4. A similar point can be made about “messy data”, another term that has recently gained
traction. Messy data covers a multitude of characteristics that the careful analyst may want to
keep separate: incomplete, noisy, uncertain, ambiguous data or data from diverse sources. Et,
as in the case of messy science, we do not have a clear sense of the complement – what is “good”
data? And who has the authority to validate?

Feyerabend’s methodological anarchism in Against Method belongs in this category.

For him, method stiﬂes progress (Feyerabend 1975).

488

Mess in Science

good thing, embracing mess as a liberating act; yet again, the focus is on the
norms and their functions, not on the mess itself: The point here is that binary
logics do, but should not, model how all of us should think. But does anything
else go? If not, we are still left with the question: who can legitimately claim
normative force over scientiﬁc thinking and practice?

Familiar Territory

5.
So far, we have covered familiar territory: Each variant of the claim that
science is messy discussed so far could be rendered in more traditional
analytic terms, and the resulting point was innocuous or widely accepted
or both. As a diagnosis, the claim that the process of knowledge generation
is messy does not have any surplus value. If we question the normative phi-
losophers’ conviction that they are in a better position than the scientists to
put science in order, the designation “messy” for knowledge in the making is
gratuitous. The point that scientists themselves have the authority to nego-
tiate what properly ordered science is does not become more convincing if we
insist that science is messy. The Reichenbachian picture of knowledge and
its generation is not being replaced, but the different elements of the picture
are being re-evaluated and the scope and tasks of (philosophical) analyses of
science are being redeﬁned in the process.

Other concerns are about the traditional conceptual inventories of phi-
losophy of science. If the analysis of messy science, night science, vague and
ﬂuctuating thinking, science in the making, or whatever we want to call it
falls within the scope of philosophy of science, and not, as Reichenbach
thought, outside it, then the disciplinary boundaries between philosophy
of science and history or sociology of science are called into question. If phi-
losophy of science morphs into history or sociology, what analytic frame-
work should be used for analyzing science?

The underlying worry that is sometimes couched in messy science talk is the
following: There is no reason to think that philosophical conceptions, stripped of
their normative function, are particularly suitable tools for the job of analyzing
scientiﬁc activity in its entirety. If we want to analyze scientiﬁc activity in toto,
warts and all, traditional philosophical frameworks are simply too narrow, comme
scientiﬁc activity comprises more than just thinking and argumentation. À
analyze practices of doing research, research methods and methodologies, aussi
as social interactions among scientists and between scientists and other social
groupes, we need to develop, or adopt, additional conceptual tools. And perhaps,
to paraphrase Philip Kitcher, le (messy) workings of science exceed “the thin
fantasies of philosophical imagination” (Kitcher 2014, p. 109).6

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In the paper in question, Kitcher commented on the “messiness of life” more

generally―it exceeds the “thin fantasies of philosophical imagination.”

Perspectives on Science

489

The worry is exacerbated if we, as analysts of scientiﬁc knowledge and
pratique, aim to contribute to science. Here the worry is that even if analysts
focused more on stuff and doing things, philosophical logics, concepts, et
distinctions are too clean, too precise, too formalized and thus too remote
from actual, messy science to be useful or informative to scientists. Messy
science talk invokes the concern that the most developed philosophical
positions are out of touch with real-life scientiﬁc issues and only of interest
to professional philosophers. The worry is that the tools that philosophy of
science provides cannot serve to resolve issues arising from actual scientiﬁc
practice in such a way that the solutions have a bearing on that practice.

If relevance to scientiﬁc practice is the goal, the criticism encapsulated in
messy science talk is plausible. After all, philosophical discussions have the
tendency to get ever more narrowly focused on quite detailed problems.
Even if they are occasioned by problems arising in scientiﬁc practice, over
temps, philosophical contributions no longer respond to scientiﬁc issues but
to other philosophers’ arguments.7 Contributors to these discussions may
end up with very sophisticated answers to certain very speciﬁc problems that
originated in messy science, but a million other issues remain unresolved.
And faced with those sophisticated expositions and solutions, we most likely
need to turn to HOPOS to uncover the scientiﬁc issues that occasioned
philosophical discussions. De plus, philosophical discussions have the
tendency to generate several different answers to philosophical problems,
whereby none of these answers is without drawbacks. Encore, even though
the original problem may have emerged in scientiﬁc discussions, each of the
solutions creates its own momentum, and none of them wins. Many articles
in the Stanford Encyclopedia of Philosophy illustrate this: there are good reasons
to embrace (or reject) realism as well as antirealism, Bayesianism as well as
frequentism, et ainsi de suite. In each case, we have a number of different answers
to a question, all more or less plausible, none ultimately satisfactory, so how
should these answers possibly help scientists resolve their day-to-day issues?
Yet again, calling these issues messy does not illuminate the situation.

In Praise and Contempt of Messy Science

6.
Calling science messy serves other purposes beyond describing the practice
of doing science or challenging philosophy’s authority and conceptual
inventory. Notably, the term messy is so equivocal that it can be put to

7. The concept of explanatory power, par exemple, was introduced in the 1960s to
better capture criteria and processes of theory choice. Since then, the concepts have mul-
tiplied and become ever more speciﬁc. Philosophers of science seek to specify formal con-
ditions of adequacy (Schupbach and Sprenger 2011), explicate explanatory power in a
Bayesian framework (Cohen 2018), or seek to distinguish different dimensions of goodness
of explanation ( Ylikoski and Kuorikoski 2010), Par exemple.

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use for the opposite purposes. Dictionaries tell us that messy means: involving,
accompanied by, or generating disorder; untidy; dirty; disorganized or
otherwise imperfect. According to the dictionary deﬁnition, messy implies
something unpleasant or not quite right, something that should be avoided
or tidied up. In actual contexts of use, cependant, messy is a much more equiv-
ocal term than the dictionary deﬁnitions suggest. While calling something
“messy” is often meant as a criticism and a request for tidying up, it is some-
times an endorsement of sorts.

Consider, par exemple, the article “Are Scientists Too Messy for Antarctica?»
published in Scientiﬁc American (1993). The author, John Horgan, complains
that scientists sometimes make a mess in the literal sense: They pose a danger
to the environment. Human interlopers dump food waste, junked machinery,
PCBs and radioactive waste on land and sea around the South Pole, causing the
degradation of the delicate continent. Horgan raises a serious concern, but he
does not pose a difﬁcult theoretical or philosophical problem. He just
demands, very legitimately, that scientists need to clean up after themselves.
The opposite view is that it is fun to mess around. It is cool to muck about
with Erlenmeyer ﬂasks, chemicals, and agar-agar in petri dishes. The phrase
“messy science” frequently comes up in the context of K-12 science educa-
tion. The hope is that, having done the Mentos and Diet Coke experiment
and similar activities in science class, kids may decide to take up a science
career in the future. Both notions of mess are innocuous and uncontested.
There is the notion that messing around has a liberating function―
encapsulated in the popular idea of the “creative chaos” that is the birth-
place of the next big breakthrough. This is a claim about the generation of
new knowledge. In the Reichenbachian framework, this would be the
claim that actual thinking (and doing) replaces operations and arguments
we previously assumed were justiﬁable and could be demonstrated as valid
with new arguments and operations. Instead of assuming that “vague and
ﬂuctuating” thinking needs rectiﬁcation through proper reconstruction,
one would say that loose, associative, unrestrained thinking leads to entirely
new frameworks, superseding the old ones.

To cash this out in a theory of creativity, one would need to demonstrate
that mess, confusion, Jacob’s experience of “night science” is not just an
occasional or a frequent, but indeed a necessary step for theoretical or
methodological innovation. Given the numerous attempts to elucidate
processes of discovery and human creativity, I doubt that this can be easily
demonstrated.

An alternative to praising messiness and celebrating mavericks is to
suggest that science never gets out of the quagmire; it’s messy through
and through. In the popular media, “messy” is often equaled with “broken”
(Balling 1994). Such articles on the alleged “messiness” of science insinuate

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that there is something wrong with science today; that scientists do not
quite know what they are talking about; that they are confused, at a loss,
unable to agree; or even that they deliberately abuse their scientiﬁc work to
promote a certain political agenda. The allegation is that because science is
“messy” in this sense, it does not deserve funding and should not form the
basis for policy decisions.

The bad popular image of messy science has evoked responses in defense of
messiness–not necessarily in terms of praise, but aiming at rectiﬁcation of
popular misunderstandings. Those responses often come from scientists
(Aschwanden 2015). There are numerous blogs and articles in popular science
journals showing that this negative image of “messy, broken science” rests on
common misunderstandings of how science really works8―it rests on a
misguided idea that everyday science, ou, more broadly, science in the making,
is governed by formal, logical and mathematical principles or follows the
notorious “steps of the scientiﬁc method”: Purpose/Question – Research –
Hypothesis – Experiment – Data/Analysis – Conclusion.9 Here current
scientists are working through ideas that scholars in science studies―and,
en effet, past scientists―have examined for a long time.

Nevertheless, even though the insights about the characteristics of labo-
ratory activities are not new, there is one important general point to take away
from reading those popular discussions about messy science. We need to
realize that we, as analysts, are part of the context we are analyzing. Reﬂecting
on the rhetorical uses of the term “mess” helps us see that introducing or
using suggestive or provocative labels for science and scientiﬁc practices
comes with responsibility. Who is supposed to learn or beneﬁt from the anal-
ysis of science – scientists? Non-scientists? Professional philosophers, politique
makers, or potentially any responsible citizen and member of the public? Are
analysts of science doing their work as a service to science or as a service to
humanity? Whatever their purposes are, are they well served by calling
science messy? What is our responsibility as analysts, are we obliged to
consider the long-term consequences of our analyses; are we even in a position

8. Inversement, scientists who say of their colleagues that they made a mess do so to
insinuate that these colleagues don’t know how to do science properly (“you won’t believe
how messy that research is”). Perhaps not surprisingly, I only have anecdotal evidence for
ce; it is not something one would say in a publication. This seems to be how scientists
typically understand the term. For other scientists, messy science is just something they
think they can’t deal with (“that’s just messy”).

9. The notion that there are discernible steps of the scientiﬁc method is, in fact, pro-
mulgated by science educators (see Helmenstine 2020). A quick search on Google turns up
countless colorful diagrams, depicting the six―or four, or ﬁve, or seven, or eight, ou
nine―steps of the scientiﬁc method. For a historical treatment of the concept of scientiﬁc
method in educational contexts, see Rudolph 2005.

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to consider them? Following Justin Biddle and Rebecca Kukla’s terminology,
we could say that analysts of science offering accounts of science are faced with
phronetic risks (Biddle and Kukla 2017, p. 217).10

7. Messy Worlds
The last section showed that some commentators on science exploit the term
“messy” to denigrate science. Those who want to undermine the authority of
science insinuate that properly ordered science (whatever this is supposed to
être) will never be fully realized. Others exploit the ambiguity to celebrate a
certain scientiﬁc persona, the maverick genius, who will create a new order.
Yet others, worrying about the bad image that science has in the popular
media might insist that scientists’ thought is never vague and ﬂuctuating
(there is no mess to begin with). In each of these perspectives, the underlying
assumption is that (proper) science is fundamentally a process of ordering, et
that properly ordered science is the goal that needs to be reached or at least
approximated for science to merit our support and our funding.

This assumption underlies not only popular discourses on science. C'est, dans
fact, one of the orthodoxies of Western science and philosophy. The tacit
assumption is that proper science needs to be a process of ordering because
the world is, fundamentally, ordered―logically ordered, and as such,
knowable, as Reichenbach presumed. That idea has permeated philosophical
theories of science and knowledge for centuries. Until today, philosophers, laboratoire
ethnographers, and other analysts of science of different stripes keep providing
various conceptual frameworks that are supposed to help account for the
process of creating order. Whether “messy science” is good, bad, or just the
way day-to-day science is, finalement, that mess will, and should, disappear, comme
scientists stabilize their experiments, give support for their hypotheses or
abandon them, and come to agreements about what theories and models to
accept. The common assumption is that science strives for the creation of order
out of mess: Night science will become well-argued and well-ordered day
science; young experimenters will become serious scientists; ad hoc and oppor-
tunistic lab activities will be regularized and presented in well-argued papers
of standardized format, et ainsi de suite.

Alas, this point is a little too general to be instructive. Consider, par exemple,
three wildly different accounts of order in science are Paul Hoyningen-Huene’s
work on systematicity (2013), Philip Kitcher’s program of well-ordered science
(2001), and Michel Foucault’s archeology of the order of things (1971). C'est

10.

STS scholars, notably Bruno Latour, have begun to reﬂect on the Science Wars in
this vein (see Kofman 2018). Some scientists are beginning to reﬂect on their responsibil-
ities as tellers of stories about science (see Wilson 2017).

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not a very enlightening exercise to try to pinpoint what these approaches
have in common.

Let us try out a different question. Do we really have reason to suppose
that science is concerned with ordering? Is there perhaps something wrong
with the intuition that good science is properly ordered science? This idea
informs radically different approaches to science, ranging from Nancy
Cartwright’s philosophy of physics (1999) to John Law’s theory of the social.
In After Method: Mess in Social Science Research, Law asks: “If [le social
monde] is an awful mess…would something less messy make a mess of de-
scribing it?» (2004, p. 1). Is messy science good science because only messy
science can adequately describe messy phenomena in a messy world? Law’s
suggestive question evokes the idea that only messy science could adequately
deal with its (messy) cible. Disregarding for a moment the claim that messy
science is good science, it is quite plausible to think that the social world is
not well ordered―this is more plausible, in fact, than the opposite.

Cartwright’s claim is less provocative and more profound because she
challenges our fundamentalist intuition that the basic laws of physics apply
partout. What if the world is a messy place? Along these lines, the term
“messy world” is used as a generic term, implying that traditional philoso-
phy of science concepts of law or explanation need to be rethought (Lipton
1999; see Rueger and Sharp 1996; Currie 2014).11 All in all, cependant, le
question of whether the world is messy or well-ordered is another very
general question that it is hard to discuss it in a meaningful way. So let us
return to messy science.

8. Wicked Problems
References to “messes” are frequent in the recent literature on issues in
science policy and environmental studies. Examples for messes include
environmental research on ﬂooding (Donaldson et al. 2010); the challenge
of deciding upon policy interventions to support community resilience
(Forrester et al. 2019); the study of water (Jackson and Buyuktur 2014);
ﬁeld research in human geography (Davies et al. 2012); and legislative
issues related to climate change (Lazarus 2009). All these studies focus
on particular kinds of problems―problems that are complex, urgent,
cut across many different ﬁelds, require input from the biomedical or

11.

I should add that Law’s question is a red herring because it implies a realist, rep-
resentational account of science. En fait, he is trying for something much more radical. Il
offers an ontological interpretation of science whereby scientists, through their activities
qua scientists, co-construct the world they investigate, describe and explain. Law has pre-
decessors in social constructivist theories of science who made similar suggestions without
couching them in the language of mess.

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physical and chemical sciences as well as the social sciences, and engage and
involve non-scientists. Such entangled problems are the interesting messes
in today’s science.

In After Method: Mess in Social Science Research, Law discusses social
phenomena such as alcoholic liver disease, its causes and treatment; le
introduction of water pumps in a developing country; or fallout monitoring
after a nuclear disaster, claiming that the social sciences are ill-equipped for
analyzing them. In contrast to Law, I think that the older literature in the
social sciences does provide resources for dealing with those interesting
messes. The social science literature from the 1970s offers some conceptual
resources that strike me as still valuable for this purpose. À ce moment-là, it was
common to characterize operations research and social planning as “messy” or
“wicked.” I think that these older analyses of the features of messes can illu-
minate not just legislative or policy interventions (Lazarus 2009; Forrester
et autres. 2019) but important characteristics of today’s scientiﬁc problems more
generally.12

In the 1970s, theorists of social planning proposed to distinguish the
social sciences from the natural sciences because the kinds of problems
treated in each domain seemed to be so different that the research methods
had to be different, aussi. In a classic article on social planning, Horst Rittel
and Melvin Webber claimed that the natural sciences dealt with problems
which were “deﬁnable and separable and may have solutions that are ﬁnd-
able” (Rittel and Webber 1973, p. 160). According to the authors, it was a
misunderstanding to think that problems in the social science resembled
natural science problems, and it was therefore wrong-headed to measure
the social sciences against the natural sciences. The social scientists needed
to leave the mindset of the natural scientists behind; “the social professions
were misled somewhere along the line into assuming they could be applied
scientists―that they could solve problems in the ways scientists can solve
their sorts of problems. The error has been a serious one” (Rittel and Webber
1973, p. 160). Social planners needed to realize that their problems were
inherently different from problems in the natural sciences.

It was then, that the concept of mess entered the discussion of social science
research methods. In his 1974 study Redesigning the Future, Russell Ackoff
proposed the concept of “mess” as a term for a “system of problems”―urgent

12.

In Scenes of Inquiry, Nicholas Jardine has argued for a problem- and question-
centered approach in the study of science, but this is not quite what I have in mind. Jardine
investigates “the ways in which new questions are brought into being and old ones dis-
solved” ( Jardine 1991, p. 3); in other words, he shifts the analytic attention from processes
of validation and justiﬁcation to processes and contexts of knowledge generation. My sug-
gestion, by contrast, is that we should understand messy problems as particular kinds of
problems.

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societal problems that needed to be addressed, such as “the race problem,
the poverty problems, the urban problem, and the crime problem” (Ackoff
1974, p. 21). Independently, Rittel and Webber described these kinds of
challenging social problems as “wicked” (Rittel and Webber 1973,
p. 155). They argued that social planners dealt with inherently wicked
problems, problems that have no unambiguous formulation and no unam-
biguous solution.

This is different from the notion that scientiﬁc knowledge is prelimi-
nary, fallible, and open to revision. The point that scientiﬁc knowledge is
fallible is typically treated as a deep epistemological point that does not
threaten our ability to act on our research outcomes. In practice, we could
be reasonably certain that our results and theories, once agreed upon, sont
sound; at any rate solid enough to base further research and actions on
eux. The notion of wicked problem challenges this relative certainty.
Reversing the arguments for division the 1970s, I propose that we utilize
the notion of a wicked problem more in our analyses of current science.
The notions of mess and wicked problems as they were introduced in
the 1970s help us grasp more ﬁrmly what is special about large portions
of today’s science. Many problems in the natural sciences today are in fact not
so different from those planners’ problems―they, aussi, are inherently wicked.
Bien sûr, science has always been entangled with society, and histo-
rians and sociologists of science have examined this entanglement for
decades. They have shown that seventeenth century natural and experi-
mental philosophers had to please wealthy patrons and to deal with the
Church or that eighteenth century experimenters put up spectacular shows
for the public and that pubs and clubs were venues for science, aussi. Nine-
teenth century researchers had to face critical and suspecting members of
the public who questioned science and scientiﬁc research because they
seemed unethical (like vivisection) or theologically presumptuous (like
evolution) or pointless (like foundational physics for its own sake). Arguably,
cependant, the problems that these researches dealt with were more easily
recognizable as scientiﬁc problems―funded, encouraged, or restricted
by society and with societal implications―than, say, stem cell research,
gene editing, research on orphan diseases or stream restoration. Wicked
problems are such that the difference between science and the public domain
becomes elusive.

For Ackoff, messes have a number of common features.13 The problems
in the mess are interrelated; a mess does not inherently break down into
simpler problems but different researchers will break down the situation

13. Ackoff acknowledges the pragmatist tradition, especially Dewey, as a source of

inspiration.

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differently; attempts to solve the simpler problems independently of one
another will often intensify the mess; and problems and solutions are always
in ﬂux, “problems do not stay solved” (Ackoff 1974, p. 31). Last but not least,
messes require cooperation from diverse stakeholders.

Rittel and Webber’s characterization of mess overlaps with Ackoff’s but is
more detailed; they describe altogether ten properties of wicked problems.14
Like Ackoff, Rittel and Webber emphasize that wicked problems are ill
deﬁned, never deﬁned deﬁnitely, and “never solved. At best they are only
re-solved-over and over again” (Rittel and Webber 1973, p. 160).15 Because
wicked problems are both unique and elusive, the assessment of solutions
also presents a challenge: There is no immediate solution, yet little oppor-
tunity to learn by trial and error, as the problem keeps shifting. Like Ackoff,
Rittel and Webber also stress that wicked problems do not exist in isolation;
each can be “considered to be a symptom of another problem.” Finally, ils
remind us of the ethical dimensions of social research, noting (with a side-
long glance to Popper) that the planner “has no right to be wrong” (p. 166).
The notion of “wicked problem” strikes me as a productive extension of
the established conceptual inventory in science studies. Wicked problems
can be usefully contrasted with Joan Fujimura’s (1987) “doable problems”.
En outre, the notion of wicked problems is a useful complement to dis-
cussions in philosophy of science and cognitive science about heuristics,
bounded rationality, and inductive risk.

Doable problems are hard, multifaceted problems, which require artic-
ulation and the organization of work. Fujimura introduces the notion of
doable problems to draw attention to the broader contexts of scientiﬁc re-
recherche: It takes more than just good instruments, techniques, and methods
to solve a research task. She argues that “technology alone does not make
problems doable” (Fujimura 1987, p. 258). The framework of doability
assumes that it is an important part of scientiﬁc work to align the exper-
iment, the laboratory, and the social world. A doable problem requires
proper alignment of all three levels of organization. By putting the artic-
ulation tasks in the foreground of the analysis, Fujimura presents the
scientist as the main agent in the nexus of organization; it is the scientist
who orchestrates the alignment.

14. They called them wicked in an attempt to stay away from moral discussions,
likely in response to West Churchman’s brief reference to wicked problems as mischievous
and evil (Churchman 1967). Rittel and Webber use the term “not because these properties
are themselves ethically deplorable. We use the term ‘wicked’ in a meaning akin to that of
‘malignant’ (in contrast to ‘benign’) or ‘vicious’ (like a circle) or ‘tricky’ (like a leprechaun)
or ‘aggressive’ (like a lion, in contrast to the docility of a lamb)» (Rittel and Webber 1973,
p. 60).

15. Law’s notion of ﬂuid problem situations resonates with this idea.

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Wicked problems, by contrast, are such that the scientist’s agency is limited
by other stakeholders outside the laboratory as well as by other agents who con-
ceptualize the problem differently and have a different understanding of its
overall signiﬁcance. De plus, wicked problems contrast with doable problems
in that not only the problem deﬁnition but also the problem situation keeps
shifting. Problem situations are ﬂuid, diffuse, slippery, and changing.16

The concept of “wicked problem” also strikes me as a useful addition to
recent discussions about inductive risk. In the last few years, analysts of
science have plausibly argued that inductive risk is just one type of a broader
set of phronetic risks (Biddle and Kukla 2017). The interpretation of certain
problems as wicked captures another lingering impression from the induc-
tive science literature, namely that these risks arise more often in some con-
texts than in others. It shifts the focus to the kinds of situations that put the
scientists at phronetic risk.

De la même manière, by changing the focus to the kinds of tasks that need to be tack-
led, the notion of wicked problem complements discussions about heuristics
and complexity in science. In epistemological perspective, complexity has
mainly been discussed in two ways: as a generative force (par exemple., by Stuart
Kauffman) and as a constitutive feature of biological and physical systems
that necessitates heuristic strategies of reasoning (par exemple., by Bill Wimsatt).
Stuart Kauffman characterizes a creative strategy for approaching difﬁcult
problems, the “patch procedure.” He assumes that a hard task can be divided
into “a quilt of nonoverlapping patches,” whereby the patches are then tack-
led separately (Kauffman 1995, p. 252). Like the theorists of social planning,
he assumes that those patches are interdependent and that a solution in one
patch will affect others. Yet the emphasis is different. Theorists of social
planning worry about the extent to which complex issues can be actively
managed. Kauffman’s emphasis is on the generative power of the patchwork
quilt. He argues that: “if the entire conﬂict-laden task is broken into the
properly chosen patches, the coevolving system lies at a phase transition be-
tween order and chaos and rapidly ﬁnds very good solutions” (Kauffman
1995, p. 253). Accordingly, Kauffman has termed this domain the domain
of the “adjacent possible,” the expansion of what we already know by recom-
bining it with novel elements from adjacent domains.17 On this view,
the emergence of novel knowledge is largely a contingent process. Le

16. The distinction between complicated and ﬂuid problem situations can be extracted
from Law’s work. The world is complicated, there are too many parameters; our knowledge
remains partial and piecemeal, situated and indexed. Situations are ﬂuid, diffuse, slippery,
changing, while our accounts are static snapshots. There are thus two different reasons
why the world exceeds our capacity to know it.

17.

See Nowotny 2017, p. 55. Rheinberger describes this process as hybridization of

experimental systems (Rheinberger 1997).

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framework of wicked problems shifts the emphasis to the conditions, needs,
and pressures that constrain the play of the patches and to the possibility that
we may not be in a position properly to choose the patches. Because wicked
problems are urgently in need of solutions, the framework of patching and
local optimization―with unanticipated outcomes―strikes me as too opti-
mistic to account for these problems. Kauffman assumes that the patches
“coevolve to ﬁnd excellent solutions” (Kauffman 1995, p. 267); the notion
of wicked problem acknowledges that we cannot wait for the excellent so-
lution to a problem that we may not even have speciﬁed correctly.

Wicked problems are complex in a way that resonates more with Bill
Wimsatt’s approach to complexity (which is itself informed by economic
and social theorizing from the 1960s and 1970s). Like Rittel and Webber,
and following Herbert Simon, Wimsatt emphasizes that complexity implies
limited possibility of decomposition into component parts and a plurality of
possible decompositions with no deﬁnitive way of choosing among them
( Wimsatt 2007, pp. 179–186). The notion of wicked problem adds to
the work on heuristics and bounded rationality because it emphasizes the
ﬂuidity of problems as well as the fact that many research problems nowa-
days concern diverse stakeholders and require multiple kinds of expertise.
De plus, paying attention to wicked problems as the target of heuristic
strategies can put the urgency of our research questions in focus. These prob-
lems must be solved on the basis of insufﬁcient evidence. The inductive risk
literature describes many situations in which we cannot afford to wait until
we have reached even relative certainty. Heather Douglas’s now classic study
of research on the carcinogenic power of dioxin (Douglas 2000), lequel
kicked off the recent revival of debates about inductive risks, discusses the
intrinsic uncertainty of research on dose-response relations testing the poten-
tial harms of certain pollutants such as dioxin. We may be conﬁdent that if
the scientists could only go on studying the issue, ils, and we would end up
with a reasonably certain assessment of the potential harms―but in the
meantime people may have died from cancer or else the industries bearing
the costs of the regulations have been negatively impacted. Along these
lines, other contributions to the inductive science literature have empha-
sized the urgency of problems that force us to act before enough evidence
is in.

The problem of climate change is a wicked problem in every sense dis-
cussed here.18 Climate change is a highly complicated thing with a mul-
titude of factors to monitor and measure, which generate a wealth of data
and models that need to be understood, evaluated, and pooled. Patching

18.

En fait, in policy contexts, climate change has been described as a super-wicked

problem, precisely because of its urgency (Lazarus 2009; Levin et al. 2012).

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does not seem to be a promising strategy both for pragmatic reasons (le
different model outcomes need to be combined) and because the assess-
ment of societal, politique, and ethical implications of climate change re-
quires input from people with very different skill sets and expertise. Food
and water insecurity, damage to ecosystems, potential health impacts, et
economic inequalities need to be taken into account in decisions about
what to monitor and measure and whom to entrust with this task. Ampli-
fying feedback of warming effects and tipping points whose impact on cli-
mate we cannot exactly calculate might change the entire problem
situation. Et, bien sûr, as the current political discussions about climate
change make painfully clear, different stakeholders have vastly different
views about how to approach these decisions.

It is also illuminating to think of the CRISPR-Cas9 technology of genetic
editing as wicked problem. D'une part, it promises numerous scientiﬁc,
technological, and medical applications including editing of disease-causing
genes and producing resilient fruit crops. On the other hand, the technology is
in itself not completely understood. Like climate change, CRISPR-Cas9 tech-
nologies raise numerous questions about risks and long-term effects of their
application, ethical and political concerns about inequity and inequality of
access to treatments, and so forth. More examples can easily be found,19 mais
these two may sufﬁce for the purposes of this paper.20

As these examples show, the concept of wicked problem cannot be strictly
deﬁned, and the boundaries between wicked and (simplement) hard problems are
not rigid. But deﬁning the term is not the point. Plutôt, the properties or
characteristics of wicked problems that Rittel and Webber identiﬁed serve
asinstructive heuristic tools for the analysis of similar problems, et, je

19.

See the literature cited at the beginning of this section, Horn and Weber (2007,

p. 3), and recent studies of inductive risk for more examples.

20.

I wrote this paper before the Covid-19 pandemic hit. It is instructive to think
about the recent developments in terms of wicked problems. Finding the structure of
the virus SARS CoV-2 is not a wicked problem. It appears that the task was not even par-
ticularly hard because the researchers could make use of established approaches and tech-
nologies (see Walls et al. 2020). Understanding and dealing with the pandemic, cependant, est
a wicked problem. It is urgently in need of solution, yet we know little about the spread of
the virus, the fatality rate, and effective protection. The problem situation changes―almost
daily, it seems. Understanding the pandemic poses phronetic risks for scientists who need to
consider the implications of the concepts they choose to report their ﬁndings, of the background
assumptions they use in their models, and of the choices they make when they include or ex-
clude certain data. Understanding and dealing with the pandemic requires multiple kinds of
expertise and involves numerous stakeholders with vastly different interests―including vulner-
able and not-so-vulnerable groups of the general population, national public health institutes,
government leaders and agencies, educational institutions, businesses small and large, alors que
global coordination of research and data management is needed.

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contend, prove to be useful. By highlighting urgency, ﬂuidity, the limits of
decomposition, and the multiplicity of stakeholders, the conceptual inven-
tory of “wicked” problems allows for an informative answer to the question
of what is special about today’s scientiﬁc inquiry.

Conclusion: Wicked Problems and the Philosopher’s Predicament
9.
Science can be, et a été, described as messy in many ways: there are
fun activities for kids; tortuous research paths; ad hoc, opportunistic prac-
tices; ﬂuid, hybrid, complicated objects; ill-deﬁned and complex research
problems, and sometimes scientiﬁc work creates environmental hazards.
Science can be, and has been called messy for many purposes: to undermine
its authority, to unmask and weaken the normative power of philosophical
frameworks, to distinguish processes of knowledge generation from their
presentation, and to celebrate creative genius. It is sobering to remind our-
selves of the diverse and even opposing rhetorical functions of messy sci-
ence talk. As a diagnostic tool, by contrast, the notions of mess and messy
science are gratuitous; sometimes they obscure rather than illuminate our
understanding of scientiﬁc practice.

The concept of “wicked problem” has the surplus value that messy science
talk lacks. Not only does it pick out features of current science that are
unprecedented, but it also comes with additional conceptual tools that are
helpful for its analysis. Wicked problems share a number of features: Ils
are not just hard―i.e., difﬁcult to answer―but we are not even sure how to
ask the right question. Wicked problems are not inherently divided into
simpler, smaller problems. Taking a piecemeal approach to these problems
is typically not an option. Wicked problems concern numerous groups of
stakeholders with multiple interests and require input from experts with
diverse kinds of expertise, whereby these groups will often frame the prob-
lem differently. Wicked problems are urgent, which means that they need to
be solved before enough evidence is in; we cannot wait for a “play of patches”
to unfold. Wicked problems are ﬂuid; the problem situation changes before
we have found a satisfactory solution to the problem.

Earlier I described some of the concerns about messy science as a repe-
tition of old discussions about the scope and normative power of philoso-
phy of science. We could characterize these discussions as boundary work
(Gieryn 1983) because they involve negotiations about disciplinary author-
ville: At stake is who and what belongs to a certain ﬁeld or does not belong;
who is, and who is not, allowed to publish in philosophy journals, présent
at certain conferences, and so forth. If we think of the negotiations as an
attempt to solve a wicked problem, it is possible to give a richer account of
what is at stake in this boundary work.

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501

It is by no means clear how we, as analysts, should deal with scientiﬁc
research problems that are wicked in the sense outlined above. Which strat-
egies or analytic approaches are open to us as we are dealing with a wicked
problem? Should analysts try to insert themselves into wicked problem situ-
ations as additional stakeholders with unique expertise? Are philosophers of
science in a position to determine what properly ordered science is and how it
can or should be implemented? Would the epistemic ideals that philosophers
are so fond of defending be genuinely helpful to those dealing with wicked
problems and trying to ﬁnd workable solutions? After all, the nature of wicked
problems is such that the unrestrained process of clariﬁcation, more clariﬁca-
tion, and even further clariﬁcation of concepts, theories, or standards of evi-
dence, the compartmentalization of the issues, etc.. appears futile or even
counterproductive. Should we, as analysts, just stand back and try to under-
stand for its own sake what science is and what scientists do, rather than in-
tervene in the process?

Those questions can be considered wicked because they cannot be tack-
led in isolation, none of them can ever be solved; the target (science) est
elusive and ever-changing; and the discussions about science engage dif-
ferent stakeholders, including science analysts and scientists from different
ﬁelds and at different career stages, scientists, broader publics, and univer-
sity administrators. These stakeholders will have very different ideas about
the nature, task and scope of philosophy of science. Admittedly, the wick-
ed problem of how best to analyze science is a rather modest specimen of
its kind, as it is far less urgent than those wicked problems I considered
earlier. It is relevant to our careers and scholarly pursuits, but the fate of
humanity does not depend on its solution.

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