Mass protests erupted, and the president fled the country. This rapid default set off a new wave of political turmoil — a vicious cycle that would trap the nation for years.

We tend to call such situations “unstable,” but the word does little to capture the complexity of what is happening in the modern world — or how it affects us. What happened in Sri Lanka in 2022, and more broadly what is unfolding globally, is increasingly described through the concept of the “polycrisis.”

A global polycrisis is the causal entanglement of crises across multiple global systems, leading to a significant deterioration in humanity’s prospects (Cascade Institute). The term was first introduced by French philosopher and sociologist Edgar Morin.

A polycrisis is not simply the sum of its parts. It is a condition in which each crisis becomes a catalyst for the others, where the consequences of one feed into and amplify all the rest. It spans eight key global systems: ecological, energy, economic, informational, transportation, healthcare, social governance, and international security.

A polycrisis doesn’t announce itself outright. But we feel it. In the growing sense of instability, and in the increasingly fragmented way we access information about the world.

Research from the Pew Research Center shows that most people don’t encounter the news itself, but rather reactions to it and secondary content about it: memes, tweets, TikToks. Algorithms designed for engagement — not understanding — strip away crucial context and flatten complex realities into single, isolated pieces of content, visually indistinguishable from AI-generated slop.

As the result, we know that something is wrong everywhere, but we don’t understand how it all connects. The relentless pace of publication, combined with the difficulty of verifying sources, erodes the stability of our mental map of the world.

At its core, the polycrisis is a crisis of knowledge: we are losing stable ways of understanding how knowledge about the world is produced, verified, and transmitted. And it is impossible to fight what we do not understand. Education is the infrastructure through which we gather and validate understanding. And it is now changing faster than any other system.

For many educators, the central challenge today is to design learning formats that align with how their students are already accustomed to receiving information through technology. Traditional educational models no longer work for this, as they were built for a different informational reality.

But the real question goes far deeper than “Can students use ChatGPT to write essays?” or “Will AI replace teachers?” Artificial intelligence is beginning to play a central role in learning, becoming the mediator between us and what we consider knowledge: filtering, summarizing, generating, suggesting. Gradually, AI systems are colonizing the very spaces through which we access structured knowledge about the world.

Research in complexity theory shows that knowledge production functions as a Complex Adaptive System — one defined by nonlinearity, self-organization, and emergence, where the behavior of the whole cannot be predicted from the behavior of its individual parts.

This logic is well illustrated by Michael Gibbons and Helga Nowotny in The New Production of Knowledge (1994), where they describe two modes of knowledge production:

• Mode 1 is the classic model: knowledge is created within established disciplines, under stable academic hierarchies, and follows a linear progression.
• Mode 2 operates differently: knowledge emerges non-linearly, in the context of application, and across disciplines. The process loops back on itself — problems and solutions refine one another through constant dialogue and feedback.

So far, artificial intelligence has proven most effective in Mode 1. But it is Mode 2 that is critical for understanding the polycrisis and finding solutions. As the production of knowledge accelerates and becomes automated, there is a growing risk of replacing understanding with optimization — shifting from “figuring out what’s going on” to “doing it faster and cheaper.”

Mode 2 is not only about process — it’s also about the resources required to sustain it. The mass adoption of AI tools promised to free us from routine work, leaving more room for creativity. In reality, the opposite happened: to remain competitive in a world of ever-expanding skill stacks, we now work more. According to PwC’s Global Workforce Hopes and Fears Survey 2024, 45% of employees report working significantly more hours in the past 12 months despite technological optimizations.

The boom in solopreneurship, the blurring of boundaries between work and life (work-life blend, zig-zag working), the rise of labor-intensive formats such as “996,” and polyworking are making personal productivity strategies increasingly extreme.
And gradually, they are moving beyond the realm of individual choice.

The logic of endless self-optimization erodes our sense of belonging to meaningful communities — a key factor in human happiness. Collectivity loses its value when everyone becomes a project of one’s own. According to Gallup research, nearly half of respondents report feeling lonely.

The mass migration online after 2020 accelerated this shift — not only because we began leaving our homes less often. Modern social platforms depersonalize us, reducing individuals to sets of personal data primarily used to extract behavioral patterns that can be monetized.

This undermines our online safety and creates an internet where public spaces for collective interaction are disappearing. Inevitably, this leads to the erosion of the social fabric.
And when the mechanisms of global togetherness collapse, so does our capacity to mount meaningful collective responses to large-scale exploitation of data and resources.

The most insidious feature of the polycrisis is its entanglement. A telling example is green energy: moving away from fossil fuels doesn’t just mean switching to new energy sources with their associated investments — it requires completely rewriting the energy models that underpin demand and supply planning. In practice, this is far more complicated than building wind turbines or solar farms.

The polycrisis forces us to recognize and account for complexity — in every sphere of life, in every decision. This means not relying on a single future scenario to adapt to once and for all, and not explaining the world through one cultural trend, one technological breakthrough, or one shift in consumption.

Polycrisis researchers recommend focusing on understanding systemic mechanisms, highlighting three in particular:

• Common Stresses — The same slow-moving stressors can simultaneously erode the resilience of multiple global systems. For example, an aging population can strain both healthcare systems and economies as the workforce shrinks and healthcare costs rise.
• Domino Effects — A crisis in one system can causally intensify stress in another or trigger an event that pushes the second system into crisis. For example, the COVID-19 pandemic exacerbated socio-economic inequality while driving up prices for goods and services.
• Inter-systemic Feedbacks — Stresses in one system can causally interact with stresses in another, which in turn feeds back into the first. A classic case: Economic shocks ↔ Authoritarianism ↔ Nationalism. Economic turmoil sparks mass discontent, populist leaders rise to power and establish authoritarian regimes, nationalist ideologies strengthen, and the cycle worsens economic instability.

The complexity of the polycrisis demands radically new forms of attention — to the world and to ourselves — if we want to remain in contact with what is happening both to it and to us.

Which is why the most damaging thing we can do for our understanding of the modern world is to draw final conclusions about it.