# CODA
The Duck, the Rabbit and the Digital Twin
Have universities inadvertently concealed themselves from themselves?Essay
Jelenko Dragisic
Two recent conversations about the future of universities prompted me to revisit a question that has occupied my thinking for many years. Both involved people associated with universities, although from quite different professional backgrounds. They reminded me of numerous other conversations I've had with people working within universities, collaborating with them from outside or simply wondering what place these institutions might occupy in the future.
There is nothing particularly unusual about such conversations. Universities are among the most consequential institutions in modern society. Their significance extends far beyond the people they educate or employ. They generate knowledge, shape professions, influence public policy, contribute to economic and cultural life, and help societies understand themselves and the world around them. Their future, therefore, is not merely a matter for university leaders, academics or education policymakers. It is a societal question.
Universities across the world have been navigating prolonged periods of disruption and uncertainty. Financial pressures, technological developments, changing expectations, shifting demographics and evolving relationships with governments, industries and communities have challenged established assumptions about how universities operate. Numerous explanations and solutions have been offered, yet it remains unclear whether universities have discovered a convincing path towards a sustainable future.
I do not pretend to have such a solution, nor am I dismissing the considerable efforts already made. But I wonder whether something more fundamental deserves attention, something worthy of a strategic gaze. What if universities have inadvertently concealed themselves from themselves? What if they are living in a digital twin of institutional reality?
A digital twin is a virtual representation of a real-world system, enabling us to observe, analyse, model and sometimes simulate its behaviour. Such representations can be remarkably sophisticated and useful, but they are not the systems themselves. They represent selected features of reality through particular assumptions, categories, measurements and relationships. Their usefulness depends not only on accuracy but also on recognising the constraints of the representation.
The difficulty arises when the distinction between representation and reality becomes blurred. I wonder whether something similar has happened to universities.
Like other established institutions, universities have developed elaborate ways of understanding themselves. Their organisational structures, academic disciplines, governance arrangements, institutional histories, performance measures, strategic plans and professional cultures collectively construct a coherent picture of what a university is and how it functions. Over time, these representations become embedded in institutional life, shaping how universities organise themselves, allocate resources, recognise achievements, interpret challenges and imagine their futures.
None of this is inherently problematic. Institutions require structures, identities and ways of making sense of their circumstances. But what if universities have gradually become so proficient at operating within these representations that they increasingly experience the world through them? What if, metaphorically speaking, they have migrated into their own digital twins?
This is not to suggest that universities inhabit an imaginary or deluded world. Their institutional realities are genuine, as are the knowledge and capabilities developed within them. The concern is more subtle: their institutional representations may have become so familiar and convincing that universities find it increasingly difficult to recognise what those representations conceal, including aspects of their own nature.
This brings me to the constraints of institutional understanding. Complex systems cannot be adequately understood simply by identifying their components and examining their interactions. A university is not merely a collection of faculties, departments, research centres, administrative functions, buildings and people. It is a dynamic convergence of relationships, conditions and processes, continuously interacting with a wider society from which it cannot meaningfully be separated.
Yet institutional representations tend to favour identifiable structures, functions and boundaries. They make organisations comprehensible and manageable but may also constrain what can be perceived. Moreover, those responsible for understanding and managing universities are not independent observers standing outside the institutions they examine. They are participants whose experiences, assumptions, identities and ways of thinking have often been shaped by those same institutional environments.
People who spend much of their working lives within universities can develop extraordinary institutional competence. But competence acquired within particular conditions does not necessarily translate into an equivalent capacity to recognise how those conditions constrain one's understanding. This is not an argument against lifelong academic careers, nor does it imply that outsiders necessarily possess superior understanding. It is simply to recognise that experience is always situated and that the conditions in which we develop our capabilities shape how we perceive the world. If an institution's ways of understanding itself are themselves products of that institution, how readily can it recognise what those ways of understanding leave unseen?
What do universities see? The familiar duck–rabbit illusion offers a simple illustration. The image remains unchanged, yet we may see a duck or a rabbit depending on how we interpret it.
Neither interpretation necessarily invalidates the other. The significance lies in recognising that what we perceive is shaped by the conditions through which we perceive it.
This raises three questions about universities. What do universities see when they look at themselves? What do they see when they look at the world beyond them? And what do they believe others see when they look at universities?
These are different perspectives shaped by different experiences, expectations and institutional conditions. A university may understand itself primarily as an educational institution, a research institution, a public institution, an economic contributor or a participant in a global knowledge system. Each interpretation may be legitimate, yet none necessarily captures the complexity of the whole. Similarly, how universities perceive the wider world may differ considerably from how that world is experienced by others. Even what universities believe others think of them may be an institutional construction, influencing how they engage with students, industries, governments and communities.
The duck–rabbit reminds us that the same reality can be perceived differently without the reality itself changing. But complex systems present a greater challenge. Unlike the familiar image, where we already know the duck and the rabbit, we cannot assume that all possible interpretations of an institution are available to us. The challenge may not be deciding whether universities see the duck or the rabbit but recognising what their established ways of seeing prevent them from perceiving.
There may be clues in how universities publicly describe themselves. An exploratory examination of Australian university mottos and slogans revealed considerable variation in how institutions communicate their identities and purposes. Among the ten highest-ranked universities in the sample, approximately 70 per cent used historical or non-English motto language, often reflecting established scholarly traditions. Among the remaining universities, roughly 70 per cent used modern English expressions, frequently emphasising opportunity, personal achievement, transformation or the future.
These observations are not evidence that universities have lost touch with reality, and the historical differences are understandable. Older universities have inherited traditions and forms of prestige that distinguish them from newer institutions. Nevertheless, mottos and slogans can reveal what universities choose to preserve, emphasise and communicate about themselves.
Viewed together, these expressions suggest that universities draw upon different institutional narratives while operating within broadly similar understandings of what constitutes a university. Perhaps the more interesting question is not why their slogans differ, but what remains largely unquestioned beneath those differences. What assumptions about institutional identity, purpose and possibility are being preserved, even as the language used to describe universities changes?
Much of the contemporary discussion about the future of universities has been dominated by familiar prescriptions: become more entrepreneurial, commercially oriented, efficient, innovative and responsive to industry. These are not necessarily unreasonable propositions. Each may have merit under particular circumstances, and universities have embraced them to varying degrees.
But I wonder whether their prominence reveals something about the problem itself. Such prescriptions largely proceed from an established understanding of what a university is. The task becomes one of improving performance, diversifying income, strengthening competitiveness or adjusting relationships with the outside world. We begin with an institution whose fundamental nature is assumed to be sufficiently understood and proceed to prescribe how it should change.But what if that assumption is precisely what needs examination? If universities have inadvertently concealed aspects of themselves from themselves, becoming more efficient or entrepreneurial within their existing institutional understanding may simply reinforce the constraints preventing them from recognising other possibilities. This does not invalidate commercialisation, efficiency or industry engagement. It questions whether these responses have emerged from a sufficiently deep examination of the institutions they seek to transform.
There is a risk of becoming increasingly sophisticated at solving problems within an institutional representation without recognising that the representation itself may be constraining our understanding of the problem. Perhaps this helps explain why extensive strategic planning, restructuring and reform can sometimes leave deeper questions unresolved. The difficulty may not be a shortage of strategies, but that the field of possibilities from which those strategies emerge has already been constrained by the institution's understanding of itself.
What if the future is brighter than we imagine? A great deal of the discourse about universities' futures appears framed by necessity: what universities must do to survive, remain competitive, secure funding or respond to external pressures. These are legitimate concerns, but they can encourage an almost predetermined understanding of the future, as though the principal task is to adapt existing institutions to conditions over which they have diminishing influence.
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What seems less prominent is a sense of possibility. Not optimism based on assurances that everything will turn out well, nor confidence derived from believing the future can be accurately predicted. Rather, confidence arising from recognising that universities possess extraordinary capabilities, relationships, knowledge, resources and social significance, some of which may offer possibilities not readily visible through their established institutional models.
What if the future of universities could be considerably brighter than many currently imagine? Not because the challenges are less serious than they appear, but because the possibilities available to universities may be far greater than their existing ways of understanding themselves allow them to recognise.
From the perspective of complexity, the future is not simply a destination towards which institutions must devise an appropriate route. It emerges through changing relationships, conditions and processes, many of which cannot be fully anticipated. The question is therefore not merely how universities can adapt to a future taking shape around them, but how they might participate in creating possibilities that do not yet exist.
I am not proposing another model for universities or offering a ready-made strategy. This thinking piece is an invitation, not a prescription. Offering another strategy at this point would risk repeating the very pattern I am questioning: moving too quickly towards solutions before examining the assumptions through which the problem has been understood.
What I am suggesting is a different starting point, one that asks universities to consider not only what they do and how they might improve, but how their institutional environments shape what they are capable of recognising about themselves. This requires more than conventional introspection. It involves questioning familiar categories, boundaries, identities and assumptions, while recognising that those undertaking the inquiry are themselves participants in the institutional processes they seek to understand.
None of this guarantees a better future, but it may create conditions in which previously concealed possibilities can emerge. If universities have inadvertently concealed themselves from themselves, uncovering what has been concealed may be an essential starting point.
The duck–rabbit reminds us that seeing something differently does not necessarily require the reality before us to change. The digital twin reminds us that even our most sophisticated representations of reality remain representations.
Perhaps universities need to question not simply what they see, but the conditions shaping what they are capable of seeing.
And that leaves me with a slightly mischievous question, but perhaps one worth taking seriously: What happens when a duck, a rabbit and a digital twin walk into a university?
Note: The duck–rabbit illusion, originally published in Fliegende Blätter (1892). Public domain.
There may be clues in how universities publicly describe themselves. An exploratory examination of Australian university mottos and slogans revealed considerable variation in how institutions communicate their identities and purposes. Among the ten highest-ranked universities in the sample, approximately 70 per cent used historical or non-English motto language, often reflecting established scholarly traditions. Among the remaining universities, roughly 70 per cent used modern English expressions, frequently emphasising opportunity, personal achievement, transformation or the future.
These observations are not evidence that universities have lost touch with reality, and the historical differences are understandable. Older universities have inherited traditions and forms of prestige that distinguish them from newer institutions. Nevertheless, mottos and slogans can reveal what universities choose to preserve, emphasise and communicate about themselves.
Viewed together, these expressions suggest that universities draw upon different institutional narratives while operating within broadly similar understandings of what constitutes a university. Perhaps the more interesting question is not why their slogans differ, but what remains largely unquestioned beneath those differences. What assumptions about institutional identity, purpose and possibility are being preserved, even as the language used to describe universities changes?
Are we searching for solutions within the problem?
Much of the contemporary discussion about the future of universities has been dominated by familiar prescriptions: become more entrepreneurial, commercially oriented, efficient, innovative and responsive to industry. These are not necessarily unreasonable propositions. Each may have merit under particular circumstances, and universities have embraced them to varying degrees.
But I wonder whether their prominence reveals something about the problem itself. Such prescriptions largely proceed from an established understanding of what a university is. The task becomes one of improving performance, diversifying income, strengthening competitiveness or adjusting relationships with the outside world. We begin with an institution whose fundamental nature is assumed to be sufficiently understood and proceed to prescribe how it should change.But what if that assumption is precisely what needs examination? If universities have inadvertently concealed aspects of themselves from themselves, becoming more efficient or entrepreneurial within their existing institutional understanding may simply reinforce the constraints preventing them from recognising other possibilities. This does not invalidate commercialisation, efficiency or industry engagement. It questions whether these responses have emerged from a sufficiently deep examination of the institutions they seek to transform.
There is a risk of becoming increasingly sophisticated at solving problems within an institutional representation without recognising that the representation itself may be constraining our understanding of the problem. Perhaps this helps explain why extensive strategic planning, restructuring and reform can sometimes leave deeper questions unresolved. The difficulty may not be a shortage of strategies, but that the field of possibilities from which those strategies emerge has already been constrained by the institution's understanding of itself.
What if the future is brighter than we imagine? A great deal of the discourse about universities' futures appears framed by necessity: what universities must do to survive, remain competitive, secure funding or respond to external pressures. These are legitimate concerns, but they can encourage an almost predetermined understanding of the future, as though the principal task is to adapt existing institutions to conditions over which they have diminishing influence.
What seems less prominent is a sense of possibility. Not optimism based on assurances that everything will turn out well, nor confidence derived from believing the future can be accurately predicted. Rather, confidence arising from recognising that universities possess extraordinary capabilities, relationships, knowledge, resources and social significance, some of which may offer possibilities not readily visible through their established institutional models.
What if the future of universities could be considerably brighter than many currently imagine? Not because the challenges are less serious than they appear, but because the possibilities available to universities may be far greater than their existing ways of understanding themselves allow them to recognise.
From the perspective of complexity, the future is not simply a destination towards which institutions must devise an appropriate route. It emerges through changing relationships, conditions and processes, many of which cannot be fully anticipated. The question is therefore not merely how universities can adapt to a future taking shape around them, but how they might participate in creating possibilities that do not yet exist.
I am not proposing another model for universities or offering a ready-made strategy. This thinking piece is an invitation, not a prescription. Offering another strategy at this point would risk repeating the very pattern I am questioning: moving too quickly towards solutions before examining the assumptions through which the problem has been understood.
What I am suggesting is a different starting point, one that asks universities to consider not only what they do and how they might improve, but how their institutional environments shape what they are capable of recognising about themselves. This requires more than conventional introspection. It involves questioning familiar categories, boundaries, identities and assumptions, while recognising that those undertaking the inquiry are themselves participants in the institutional processes they seek to understand.
None of this guarantees a better future, but it may create conditions in which previously concealed possibilities can emerge. If universities have inadvertently concealed themselves from themselves, uncovering what has been concealed may be an essential starting point.
The duck–rabbit reminds us that seeing something differently does not necessarily require the reality before us to change. The digital twin reminds us that even our most sophisticated representations of reality remain representations.
Perhaps universities need to question not simply what they see, but the conditions shaping what they are capable of seeing.
And that leaves me with a slightly mischievous question, but perhaps one worth taking seriously: What happens when a duck, a rabbit and a digital twin walk into a university?
Note: The duck–rabbit illusion, originally published in Fliegende Blätter (1892). Public domain.
Against Hidden Reductionism: Why Complexity Thinking is Not Systems Thinking
Essay
Jelenko Dragisic
There is a great deal of talk these days about systems thinking. Entire libraries are dedicated to it, workshops branded in its name, consultants selling it as the next evolution in leadership or strategy. It is, at first glance, an attractive proposition. After all, who wouldn’t want to understand the world as a system of interconnected parts, delicately balanced and constantly interacting? Yet, I can’t shake the sense that this surge of enthusiasm masks something deeper and problematic. Systems thinking, at least in how it’s widely practised and sold, feels less like an invitation to think differently and more like an old habit dressed in a new language. It is, in many cases, a form of hidden reductionism.
We need to pause and ask: what kind of thinking is truly required when dealing with complexity? Because what passes as systems thinking often stops at mapping parts and their relations—essentially a sophisticated form of disassembly and reassembly. It is a clever way of returning to familiar ground, where we believe that by breaking things down, naming the parts, understanding their function, and then piecing them back together, we will somehow master the system. It’s comforting, linear, and ultimately false. The mistake, I believe, lies in the assumption that every system can be treated the same way, regardless of its nature. Not every system is complex.
We need to pause and ask: what kind of thinking is truly required when dealing with complexity?
We need a way of thinking and diagnosing that respects the irreducibility of complex systems.
Complicated systems—machines, bureaucratic processes, static
frameworks—lend themselves well to this approach. They have parts, those parts
have functions, and when you tweak them, predictable outcomes follow. But when
we are dealing with complex systems, something fundamentally different is at
play. Complexity is not a matter of scale or number of parts. It is about how
the system behaves—its adaptiveness, its capacity for emergence, its
self-organisation, its resilience. A complex system is not a static object
waiting to be understood by pulling it apart; it is a living, dynamic, evolving
entity, irreducible to its individual components.
This is why I find the popular label “complex adaptive systems” both redundant and misleading. A system that is complex must be adaptive. Adaptivity is not an add-on; it is a defining feature. You cannot describe a complex system without acknowledging its capacity to evolve, respond, reorganise, and surprise. To separate adaptivity out as if it were some optional feature suggests a lack of grasp of what complexity actually entails.
The deeper issue, however, is not merely a matter of terminology. It is about the way we habitually think. Our default mode of understanding is analytical—we carve out the world into pieces, categorise them, attempt to grasp the relationship between those pieces, and assume that by assembling this knowledge, the whole will reveal itself. We approach systems, phenomena, even people, as puzzles to be solved by way of dissection. It’s the same whether we are analysing an organisation, an ecosystem, or an individual human being. We disassemble and then hope to reconstruct.
But what if that very instinct is the obstacle? Complexity thinking, as I see it, demands something far more radical. It requires that we resist, consciously and continually, this urge to break things down into discrete, manageable parts. Because in complex systems, the “parts” are not truly parts. They are not independent units with fixed boundaries. Instead, they are better understood as dimensions, as particular lenses or prisms through which the whole system can be glimpsed.
Take, for example, the usual list of attributes associated with complex systems—emergence, resilience, self-organisation, order, chaos, equilibrium, entropy. The common mistake is to treat these as parts that can be isolated, measured, optimised, or corrected. But they are not parts in any meaningful sense. They are dimensions—ways in which the whole system manifests itself when viewed from a particular angle. They are not separable components that can be removed, studied, and then reinserted. Rather, the whole system is always present, visible differently depending on the dimension through which we choose to observe it.
It’s like looking at a human being and thinking you can understand them by cutting off their hand or isolating their ear. Of course, you can describe the anatomy of a hand or an ear. But what you lose in the process is the recognition that the hand only makes sense as part of a living, breathing, whole person. The hand contains a trace of the whole person; it is not merely an object attached to a body. To truly understand a person through their hand, you must see the entire person in the hand—not as a separate part, but as a dimension through which the person reveals themselves.
This is why I find the popular label “complex adaptive systems” both redundant and misleading. A system that is complex must be adaptive. Adaptivity is not an add-on; it is a defining feature. You cannot describe a complex system without acknowledging its capacity to evolve, respond, reorganise, and surprise. To separate adaptivity out as if it were some optional feature suggests a lack of grasp of what complexity actually entails.
The deeper issue, however, is not merely a matter of terminology. It is about the way we habitually think. Our default mode of understanding is analytical—we carve out the world into pieces, categorise them, attempt to grasp the relationship between those pieces, and assume that by assembling this knowledge, the whole will reveal itself. We approach systems, phenomena, even people, as puzzles to be solved by way of dissection. It’s the same whether we are analysing an organisation, an ecosystem, or an individual human being. We disassemble and then hope to reconstruct.
But what if that very instinct is the obstacle? Complexity thinking, as I see it, demands something far more radical. It requires that we resist, consciously and continually, this urge to break things down into discrete, manageable parts. Because in complex systems, the “parts” are not truly parts. They are not independent units with fixed boundaries. Instead, they are better understood as dimensions, as particular lenses or prisms through which the whole system can be glimpsed.
Take, for example, the usual list of attributes associated with complex systems—emergence, resilience, self-organisation, order, chaos, equilibrium, entropy. The common mistake is to treat these as parts that can be isolated, measured, optimised, or corrected. But they are not parts in any meaningful sense. They are dimensions—ways in which the whole system manifests itself when viewed from a particular angle. They are not separable components that can be removed, studied, and then reinserted. Rather, the whole system is always present, visible differently depending on the dimension through which we choose to observe it.
It’s like looking at a human being and thinking you can understand them by cutting off their hand or isolating their ear. Of course, you can describe the anatomy of a hand or an ear. But what you lose in the process is the recognition that the hand only makes sense as part of a living, breathing, whole person. The hand contains a trace of the whole person; it is not merely an object attached to a body. To truly understand a person through their hand, you must see the entire person in the hand—not as a separate part, but as a dimension through which the person reveals themselves.
Similarly, when we look at resilience or emergence in a
complex system, we are not identifying a detachable component. We are seeing
the whole system as it expresses itself through resilience or emergence. Each
dimension reveals a different face of the system, but always the system in its
entirety. It’s a shift from part-thinking to dimensional-thinking.
This is where I believe most systems thinking falls short. Despite all its language about interconnection and feedback loops, it still operates on the premise that if you understand the parts well enough, the system will surrender its secrets. It assumes that by mapping, analysing, and optimising individual elements, the whole can be controlled or predicted. But complexity is not controllable. It is not something that can be reverse-engineered like a machine.
What is needed instead is a way of thinking—and a way of diagnosing—that honours the irreducibility of complex systems. A diagnostic tool that resists the temptation to dissect and instead invites us to observe how the whole system shifts when viewed through different dimensions. Such a tool would not promise easy solutions or control; rather, it would offer patterns, insights, and relational understanding. It would teach us to look, not to fragment.
In a time when every field seems eager to slap the word “systems” onto their strategies, the real challenge is to avoid falling back into the same reductionist traps under a new banner. Complexity thinking is not a brand of systems thinking. It is something else entirely—a discipline of resisting the fragmentation instinct, and learning instead to engage with wholes as wholes, in all their unpredictability and aliveness.
This is where I believe most systems thinking falls short. Despite all its language about interconnection and feedback loops, it still operates on the premise that if you understand the parts well enough, the system will surrender its secrets. It assumes that by mapping, analysing, and optimising individual elements, the whole can be controlled or predicted. But complexity is not controllable. It is not something that can be reverse-engineered like a machine.
What is needed instead is a way of thinking—and a way of diagnosing—that honours the irreducibility of complex systems. A diagnostic tool that resists the temptation to dissect and instead invites us to observe how the whole system shifts when viewed through different dimensions. Such a tool would not promise easy solutions or control; rather, it would offer patterns, insights, and relational understanding. It would teach us to look, not to fragment.
In a time when every field seems eager to slap the word “systems” onto their strategies, the real challenge is to avoid falling back into the same reductionist traps under a new banner. Complexity thinking is not a brand of systems thinking. It is something else entirely—a discipline of resisting the fragmentation instinct, and learning instead to engage with wholes as wholes, in all their unpredictability and aliveness.
What is Climate Anxiety an anxiety about?
Essay
Jelenko Dragisic PDF ︎︎︎
Hippocrates’ On Airs, Waters, and Places is possibly the oldest surviving text that links climate and human health. Yet outside niche circles in the health profession, few are even aware of it. The text is seen as antiquated, part of a distant past, while modern medicine dazzles us with technologies like what physicist Richard Feynman once referred to as “swallowable surgeons”: tiny devices capable of performing internal organs repairs.
Despite this technological leap, the intersection of climate and health has re-emerged, not merely as the interest of a few informed individuals, but as a field of institutional concern. While there is a long record of research papers stretching back to the mid-20th century, two key points stand out about the history of research in the area. First is the emergence of a few critical texts in the early 1990s and second is a rapid rise in scholarly publications in the past 20 years.
The two seminal texts appeared roughly 35 years ago: the Intergovernmental Panel on Climate Change (IPCC)’s 1990 and 1992 Assessments, and the World Health Organization (WHO)’s Potential Health Effects of Climate Change. The IPCC warned that health impacts would be especially severe in urban areas, a prescient observation considering that, at the time, most humans still lived in rural environments. The report also reminded us of our capacity to adapt, perhaps the most defining human trait. But, as it warned, adaptation has limits and a cost. What neither the IPCC nor the WHO could fully anticipate was the psychological toll this unfolding reality might exact, not only fear of the changes themselves, but a growing sense of isolation in the face of them.
Notably, the report made no mention of climate anxiety.
Perhaps it couldn’t have. Few at the time could have foreseen that, within a
generation, significant segments of society would suffer from psychological
distress directly linked directly to climate change.
The WHO report was presented ‘not as an exhaustive treatise
for the expert’. Its baseline projections included the suggestion that average
global surface temperature could increase by 3 degrees Celsius by the year
2030, and sea level could rise by at least 0.10m by 2050. Current data suggest
that, at the current rate, WHO’s predictions might have been too conservative
in regard to sea level rise and overstated in the case of global temperature
rise, despite the fact that both have increased. The scenario becomes even more complicated
when we consider that CO2 emissions have risen by 20% in the past 30
years and if that trend persists, we can expect a further 10% increase from the
current record level.
Climate anxiety is tapping into our deepest fears: isolation, exclusion and disconnection.
It also indicated that the occurrence of extreme weather events might have a more profound impact overall than average changes. The working group at the time was yet to witness the events that marked the early 21st century and established an entirely new narrative around natural disasters.
The frequency of extreme weather events increased by more than 50% in the same period. Natural disasters have affected more than half of the world’s population with no reprieve in sight. For an increasing number of people in Australia, as well as globally, natural disasters or extreme weather events have become portals into climate change, so much so that many choose to ignore scientific facts; and simply rely on what they experience firsthand. This is a vital point in how we communicate, discuss and adapt to climate change when things appear too much to metabolise and make sense of.
The evolution and maturing of our knowledge about climate change and its effects on human health was perhaps best served with the publication of Planetary Overload: Global Environmental Change and Human Health (1993), by late Australian epidemiologist A. J. McMichael. McMichael wrote an open letter shortly before his passing in 2014 in which he said, “In the long run, the harm to human health from climate change is more than an avoidable burden of suffering, injury, illness and premature death. It signals that our mismanagement of the world’s climate and environment is weakening the foundations of health and longevity.” That message effectively not only demands a sense of urgency to act but also hints, however unintentionally, at anxiety-induced lack of resolve.
However, things have moved on rapidly and not necessarily in
a reassuring way. The body of research in the space of climate change and
health has grown and expanded in various directions. We know a lot more about
it now, to a point where the lack of concrete action is mildly baffling. Survey
after survey shows climate anxiety is real. All too real, especially for some
members of the community. The Lancet Commission on Climate Change in 2009
concluded that “climate change is the biggest global health threat of the
21st century”.
To complicate the picture further, and without going into a
great deal of sifting through economic data, the cost of climate-induced health
problems is genuinely frightening. Sustainability Victoria has estimated that
extreme heat alone costs the Australian economy over A$8 billion per annum.
Globally, some projections forecast an annual loss of US$2.4 trillion dollars
by the end of this decade. The burden on the economy globally by the end of the
century could be up to 4% of global GDP. As if these figures are not worrying
enough, last year the World Economic Forum projected that within 25 years,
climate change could result in US$12.5 trillion in economic losses. For
comparison, that is more than the combined total economic output of Australia,
Canada, the UK and Japan.
From those early days of expressing concern and formulating
what today is a solid body of knowledge, little real-term advancement has been
made in practice. As a group of experts pointed out in The Lancet (perhaps
the most influential peer reviewed medical journal) a few years ago (in the
midst of COVID), “To date, there are few examples of implementation science
studies that help guide climate-related health adaptation.” The authors
warn in their Advancing Climate Change Health Adaptation Through Implementation
Science paper, that “As the urgency of the climate crisis escalates,
with increasing morbidity and mortality from climate change-fuelled extreme
weather and climate events, proactive and effective interventions to protect
public health against the risks of a changing climate are crucial.”
Climate anxiety is a term used synonymously with solastalgia or climate distress to describe all of the emotions and experiences that come with increased awareness of the effects of climate change
The warning might serve as a subtle or perhaps naïve
question: what is climate anxiety an anxiety about? Could there be something
that makes people anxious in a way that also interferes with their ability to
spring to action? The evidence is clear. The threat is real. So why so little
action? Why no decisive action in sight? To be fair, we know that important
work has been done by many governments in the form of releasing strategies for
health and climate change. Here in Australia, the first such strategy was
released just over a year ago. A promising start. And worthy of note given that
the majority of countries have not made that step as at present. Yet, as is widely recognised, strategies, by
themselves, are just that. At the risk of virtue signalling, strategy
implementation demands major resourcing, education, programme implementation
and, last but not least, a cultural paradigm shift. Given how complex climate
change is and how its impact makes human health more vulnerable, it pays to
consider how we narrate that space.
For instance, the term ‘climate anxiety’ is not mentioned in
the strategy implementation plan. That omission isn’t necessarily a flaw. But
it does raise a pressing question: if climate anxiety, or as many experts call
it, ‘climate change anxiety’ (CCA), is now widely used in daily discourse,
particularly among younger populations, will such a strategy be inclusive and
capable of genuine engagement? This is not a petty question. It is a pragmatic
one, given how difficult it is to mitigate the mental health side of climate
and health.
Given all that, it might be helpful to consider that anxiety
is a form of response to fear - two closely related but critically different
phenomena. One is a response to the other, so to speak. We fear things when we
know the object of fear and feel anxiety when that object is obscure. Clearly
there is a lot more to this, but it is a helpful way to frame some very
critical questions in regards to the way people make sense of anxieties that
arise from climate change-related events.
The picture of climate anxiety becomes further blurred at
the exact place where climate and psychology intersect. It threatens with a
fast evolving and at times incredibly simplistic narrative that leaves
historical, sociological and philosophical context completely out of the frame.
It leads to less not more quality discussion. It simplifies the answers to
complex problems. Recklessly so even.
Climate and anxiety are perhaps most prolifically found amongst young
people. While not exclusive to that
segment of society, it certainly has gained more traction than elsewhere.
Social psychologist Jonathan Haidt dubbed Gen Z ‘the anxious generation’. This is also the generation that has voiced its
concerns about a climate impacted future in an emblematic way, using the
ubiquitous power of social media. The
response has not led to a meaningful grasp of deeper underlying processes that
affect not only one generation. This
invariably has paved a way for ‘solutions’ that appeal on some level but come irresponsibly
close to pop psychology and self-help informed ideas about anxiety.
The way climate anxiety could be forming in society is
through things we recognise; extreme weather events being perhaps the most
obvious example. Most people are not inclined to read lengthy IPCC reports. But
when, as noted by the recently concluded Senate Select Committee on Australia’s
Disaster Resilience, 70% of Australians were living in a local government area
(LGA) impacted by a disaster event, with half of LGAs in a disaster-declared
zone, it becomes apparent that natural disasters are immediate and logical
prompts for people to think about climate change. While we know that not all
people will automatically conclude that natural disasters are a direct outcome
of climate change, we do know that a very high percentage of people wonder
about a connection. Some surveys have shown that people who have been affected
by an extreme weather event are almost twice as likely to worry a great deal
about climate change compared to those who have not. Furthermore, those
affected by extreme weather events are far more likely to believe that climate
change effects such as global warming are already happening.
Why does this matter? To begin with, we can observe how
people are making sense of climate change through their lived experience of
extreme weather events. This needs to be recognised and incorporated into
mitigation strategies. If the community, including researchers, practitioners,
and leaders, speaks in terms of climate change anxiety, then policy must
respond in kind. It’s not a trivial matter; it’s a practical one. Failing to do
so risks leaving people to cope in isolation. Climate anxiety, in this sense,
may not just be about rising seas or searing heat, but about being left alone
to face them.
In other words, climate anxiety might be tapping into our
deepest fears: isolation, exclusion, and a profound sense of disconnect in the
face of threats we cannot yet fully comprehend. It is worth remembering that,
while anxiety can be mitigated with the assistance of psychologists and be
viewed strictly from a clinical perspective, this response may fall drastically
short of the actual need. Moreover, failing to grasp the fact that anxieties
have complex and deep-rooted causes, including isolation in the face of
threats, can easily become a failure to account for the powerful role a sense
of belonging and social capital have in preventing anxiety from arising in the
first place.
We can invest in training more psychologists ready to offer
help to those whose climate anxiety is preventing them from living well, or we
can also equally focus on helping communities to better grasp climate change.
That is, help them identify the objects of fear and identify strategies for
dealing with those threats.
If anxiety thrives in isolation, then the antidote is not
only psychological but cultural. We must not only train more professionals, but
rebuild shared meaning, helping communities to see, name, and respond to
threats together. Adaptation has always been our strength, but only when we
adapt with greater unity.
Climate anxiety, then, may best be understood as a signal, not
just of ecological crisis, but of the need for renewed connection and meaning. What transpires from there is open to each
community to explore and define.
Climate anxiety, then, may best be understood as a signal, not just of ecological crisis, but of the need for renewed connection and meaning.
Against Hidden Reductionism: Why Complexity Thinking is Not Systems Thinking
Essay
Jelenko Dragisic
There is a great deal of talk these days about systems thinking. Entire libraries are dedicated to it, workshops branded in its name, consultants selling it as the next evolution in leadership or strategy. It is, at first glance, an attractive proposition. After all, who wouldn’t want to understand the world as a system of interconnected parts, delicately balanced and constantly interacting? Yet, I can’t shake the sense that this surge of enthusiasm masks something deeper and problematic. Systems thinking, at least in how it’s widely practised and sold, feels less like an invitation to think differently and more like an old habit dressed in a new language. It is, in many cases, a form of hidden reductionism.
We need to pause and ask: what kind of thinking is truly required when dealing with complexity? Because what passes as systems thinking often stops at mapping parts and their relations—essentially a sophisticated form of disassembly and reassembly. It is a clever way of returning to familiar ground, where we believe that by breaking things down, naming the parts, understanding their function, and then piecing them back together, we will somehow master the system. It’s comforting, linear, and ultimately false. The mistake, I believe, lies in the assumption that every system can be treated the same way, regardless of its nature. Not every system is complex.
We need to pause and ask: what kind of thinking is truly required when dealing with complexity?
We need a way of thinking and diagnosing that respects the irreducibility of complex systems.
Complicated systems—machines, bureaucratic processes, static
frameworks—lend themselves well to this approach. They have parts, those parts
have functions, and when you tweak them, predictable outcomes follow. But when
we are dealing with complex systems, something fundamentally different is at
play. Complexity is not a matter of scale or number of parts. It is about how
the system behaves—its adaptiveness, its capacity for emergence, its
self-organisation, its resilience. A complex system is not a static object
waiting to be understood by pulling it apart; it is a living, dynamic, evolving
entity, irreducible to its individual components.
This is why I find the popular label “complex adaptive systems” both redundant and misleading. A system that is complex must be adaptive. Adaptivity is not an add-on; it is a defining feature. You cannot describe a complex system without acknowledging its capacity to evolve, respond, reorganise, and surprise. To separate adaptivity out as if it were some optional feature suggests a lack of grasp of what complexity actually entails.
The deeper issue, however, is not merely a matter of terminology. It is about the way we habitually think. Our default mode of understanding is analytical—we carve out the world into pieces, categorise them, attempt to grasp the relationship between those pieces, and assume that by assembling this knowledge, the whole will reveal itself. We approach systems, phenomena, even people, as puzzles to be solved by way of dissection. It’s the same whether we are analysing an organisation, an ecosystem, or an individual human being. We disassemble and then hope to reconstruct.
But what if that very instinct is the obstacle? Complexity thinking, as I see it, demands something far more radical. It requires that we resist, consciously and continually, this urge to break things down into discrete, manageable parts. Because in complex systems, the “parts” are not truly parts. They are not independent units with fixed boundaries. Instead, they are better understood as dimensions, as particular lenses or prisms through which the whole system can be glimpsed.
Take, for example, the usual list of attributes associated with complex systems—emergence, resilience, self-organisation, order, chaos, equilibrium, entropy. The common mistake is to treat these as parts that can be isolated, measured, optimised, or corrected. But they are not parts in any meaningful sense. They are dimensions—ways in which the whole system manifests itself when viewed from a particular angle. They are not separable components that can be removed, studied, and then reinserted. Rather, the whole system is always present, visible differently depending on the dimension through which we choose to observe it.
It’s like looking at a human being and thinking you can understand them by cutting off their hand or isolating their ear. Of course, you can describe the anatomy of a hand or an ear. But what you lose in the process is the recognition that the hand only makes sense as part of a living, breathing, whole person. The hand contains a trace of the whole person; it is not merely an object attached to a body. To truly understand a person through their hand, you must see the entire person in the hand—not as a separate part, but as a dimension through which the person reveals themselves.
This is why I find the popular label “complex adaptive systems” both redundant and misleading. A system that is complex must be adaptive. Adaptivity is not an add-on; it is a defining feature. You cannot describe a complex system without acknowledging its capacity to evolve, respond, reorganise, and surprise. To separate adaptivity out as if it were some optional feature suggests a lack of grasp of what complexity actually entails.
The deeper issue, however, is not merely a matter of terminology. It is about the way we habitually think. Our default mode of understanding is analytical—we carve out the world into pieces, categorise them, attempt to grasp the relationship between those pieces, and assume that by assembling this knowledge, the whole will reveal itself. We approach systems, phenomena, even people, as puzzles to be solved by way of dissection. It’s the same whether we are analysing an organisation, an ecosystem, or an individual human being. We disassemble and then hope to reconstruct.
But what if that very instinct is the obstacle? Complexity thinking, as I see it, demands something far more radical. It requires that we resist, consciously and continually, this urge to break things down into discrete, manageable parts. Because in complex systems, the “parts” are not truly parts. They are not independent units with fixed boundaries. Instead, they are better understood as dimensions, as particular lenses or prisms through which the whole system can be glimpsed.
Take, for example, the usual list of attributes associated with complex systems—emergence, resilience, self-organisation, order, chaos, equilibrium, entropy. The common mistake is to treat these as parts that can be isolated, measured, optimised, or corrected. But they are not parts in any meaningful sense. They are dimensions—ways in which the whole system manifests itself when viewed from a particular angle. They are not separable components that can be removed, studied, and then reinserted. Rather, the whole system is always present, visible differently depending on the dimension through which we choose to observe it.
It’s like looking at a human being and thinking you can understand them by cutting off their hand or isolating their ear. Of course, you can describe the anatomy of a hand or an ear. But what you lose in the process is the recognition that the hand only makes sense as part of a living, breathing, whole person. The hand contains a trace of the whole person; it is not merely an object attached to a body. To truly understand a person through their hand, you must see the entire person in the hand—not as a separate part, but as a dimension through which the person reveals themselves.
Similarly, when we look at resilience or emergence in a
complex system, we are not identifying a detachable component. We are seeing
the whole system as it expresses itself through resilience or emergence. Each
dimension reveals a different face of the system, but always the system in its
entirety. It’s a shift from part-thinking to dimensional-thinking.
This is where I believe most systems thinking falls short. Despite all its language about interconnection and feedback loops, it still operates on the premise that if you understand the parts well enough, the system will surrender its secrets. It assumes that by mapping, analysing, and optimising individual elements, the whole can be controlled or predicted. But complexity is not controllable. It is not something that can be reverse-engineered like a machine.
What is needed instead is a way of thinking—and a way of diagnosing—that honours the irreducibility of complex systems. A diagnostic tool that resists the temptation to dissect and instead invites us to observe how the whole system shifts when viewed through different dimensions. Such a tool would not promise easy solutions or control; rather, it would offer patterns, insights, and relational understanding. It would teach us to look, not to fragment.
In a time when every field seems eager to slap the word “systems” onto their strategies, the real challenge is to avoid falling back into the same reductionist traps under a new banner. Complexity thinking is not a brand of systems thinking. It is something else entirely—a discipline of resisting the fragmentation instinct, and learning instead to engage with wholes as wholes, in all their unpredictability and aliveness.
This is where I believe most systems thinking falls short. Despite all its language about interconnection and feedback loops, it still operates on the premise that if you understand the parts well enough, the system will surrender its secrets. It assumes that by mapping, analysing, and optimising individual elements, the whole can be controlled or predicted. But complexity is not controllable. It is not something that can be reverse-engineered like a machine.
What is needed instead is a way of thinking—and a way of diagnosing—that honours the irreducibility of complex systems. A diagnostic tool that resists the temptation to dissect and instead invites us to observe how the whole system shifts when viewed through different dimensions. Such a tool would not promise easy solutions or control; rather, it would offer patterns, insights, and relational understanding. It would teach us to look, not to fragment.
In a time when every field seems eager to slap the word “systems” onto their strategies, the real challenge is to avoid falling back into the same reductionist traps under a new banner. Complexity thinking is not a brand of systems thinking. It is something else entirely—a discipline of resisting the fragmentation instinct, and learning instead to engage with wholes as wholes, in all their unpredictability and aliveness.