When Donald Trump stood on the White House lawn in April 2025 with a large laminated sign announcing the first round of trade tariffs that would be imposed on different countries, the Trade Policy Uncertainty Index skyrocketed.
On a monthly basis, this index, overseen by five members of the board of directors of the Federal Reserve (the US central bank), checks the frequency of use of terms related to trade policy and uncertainty in seven major newspapers, including The New York Times and The Guardian.
Trump’s so-called “liberation day” caused volatile fluctuations in the value of financial products and currencies, as governments around the world scrambled to respond. The levels of uncertainty were unprecedented; The outbreak of the Covid pandemic was nothing in comparison, according to the index.
In highly complex systems, conditions of uncertainty and even ignorance are extremely common. These conditions become even more likely when such systems, such as those that control global finance, are opaque and poorly regulated. Add to this a maverick American president and an administration determined to change the status quo, and tidy old assumptions fall away.
Uncertainty occurs when we do not know the probability of different things happening: we cannot predict, manage or control. For many people, uncertain conditions result in precarious employment, insecure housing, and growing inequality. Vulnerabilities, such as mental illness, can be even more exposed when life is so uncertain, which only contributes to accentuating these perceptions of uncertainty.
However, for a lucky few, uncertainty is an opportunity to make a fortune. Financial capitalism thrives on uncertainty and asymmetric information, which can be fostered by those who can pocket the profits by betting on the unknown.
Uncertainty is also being capitalized on in politics. The growing economic precariousness after Covid-19 has been linked to increased support for populist parties in many European countries. And this nationalist policy that extends across much of the world reduces the possibilities for transnational collaboration and multilateral regulation.
There are real and present dangers in this era of uncertainty. But through my research at the Institute for Development Studies, I have witnessed inspiring innovations that I believe could be applied in other areas of work and life. My latest book, “Navigating Uncertainty: Radical Rethinking for a Turbulent World,” explores the strategies used to counter uncertainty.
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Uncertainties of global finance
The financial crisis of 2008 is partly explained by the lack of this type of human involvement and the dependence on a commercial system where taking control turned out to be very misleading.
The international financial system involves a multitude of actors, each with different types of information about the future. In the run-up to the crisis, numerous new financial instruments were devised to make profits. Investment banks—Goldman Sachs, Merrill Lynch, Morgan Stanley—perfected the art of managing the enormous amounts of cash generated in the financial system through various derivative instruments, including the fateful mortgage-backed securities that triggered the collapse. However, the bewildering variety of acronyms and actors involved meant that few truly understood the system and its dynamics.
At the center of this complex web of financial interactions were mathematical models designed to counteract uncertainty and provide control. The famous Black-Scholes-Merton equation helped manage transactions that occurred in ever-increasing volumes and at ultra-fast speeds, with billions of dollars exchanged in nanoseconds over high-speed internet connections.
However, when there is too much reliance on risk-based models within a strictly defined regulatory system, uncertainties have a bad habit of sneaking up and catching us by surprise. As Andy Haldane, then chief economist at the Bank of England, commented after the crisis:
The financial network became dense and opaque. As a result, the precise source and location of the underlying claims became unknown. “Follow the leader” became a crazy strategy. In short, the diversification strategies of individual companies generated greater uncertainty throughout the system.
The crisis originated in what Haldane called “an exaggerated sense of knowledge and control.” Since then, there has been a lot of thinking about what went wrong and what to do about it. One response has been to add new layers of regulation, but many argue that this could simply obscure underlying uncertainties, as has happened before.
The financial system was ill-prepared to respond to the shocks from the subprime mortgage collapse, and very little appears to have changed since then, as was evident after Trump’s tariff announcement.
Today’s financial system increasingly relies on algorithmic models for decision-making, powered by increasingly sophisticated AI applications. Machine learning models, with complex language, use accumulated historical data to predict the future; However, in addition to increasing opacity, accountability is reduced. AI offers an illusion of control, which can be very dangerous.
The reality is that conditions of uncertainty are not unusual or fortuitous phenomena, but rather normal consequences of complex systems. What does it matter if the usual assumptions of modernity (planning, management, regulation, control) must be radically rethought? Is it possible to accept uncertainty for the benefit of all, rather than denying or ignoring it until it is too late?
For financial systems, Haldane and others have argued that this involves rethinking the configurations of financial networks and enabling new practices (requiring new skills) for those involved. There is a need to move from reliance on opaque and highly complex risk-based modeling algorithms to allowing greater human discretion and judgment. Active deliberation about appropriate responses to inevitably incomplete information is necessary in a world where uncertainty, even ignorance, is not only accepted but embraced.
Where can we look for inspiration? I suggest that the pastoral systems of northern Kenya and Amdo Tibet in China are good starting points. In both environments, herders—mobile livestock farmers—must manage highly variable climates and volatile market conditions, along with conflict and political uncertainty, to maintain the health of their animals and support their families. Like the global financial system, pastoralists trade across borders, manage highly variable supply and demand, and interact across networks in real time.
During my research with Kenyan and Chinese colleagues in both places since 2018, we have been surprised by the skill with which pastoralists live with and benefit from uncertainty. I think this offers important lessons for other parts of the world, including its global financial centers.
Continue reading: Humanity at the center of uncertainty
Rethinking an uncertain world
Despite different contexts, they offer important perspectives on how to manage uncertainty in our turbulent times. Could these insights help us avoid the chaos and collapse we witnessed during the financial crisis and after the imposition of Trump’s tariffs? Interestingly, the principles that emerge are similar to those suggested by Haldane and others in the wake of the 2007-2008 financial crisis.
What does this imply? The need to decentralize and rely on social interactions in localized networks. The need to avoid dependence on simple and centralized solutions, whether algorithmic or state dictates. The need to be careful about imposing regulations from above and to seek adaptive and flexible solutions. The need to develop collective options based on relationships of trust, avoiding an atomized and individualized response or one that arises from a centralized and dirigiste imposition.
Above all, it highlights the need for human contact: the networked social relationships that only develop when people interact with each other and build trust.
What does this suggest for the future? A modernist vision of control, whether through markets or states, towards a singular understanding of progress is clearly inappropriate. Instead, a more flexible and adaptive path is required. This involves opening up to alternatives, decentralizing activities, facilitating experimentation and improvisation, and accepting uncertainty.
Accepting uncertainty and encouraging democratic deliberation is also a way to prevent the future from being dominated by those who seek to profit from it or who seek to close down options through populist rhetoric of “taking back control.”
Whether responding to a financial crisis, new technologies, land use change, a pandemic or the climate crisis, this requires, as in citizen assemblies and other forms of deliberative democratic practice, that diverse people interact and build trust for collective responses. AI and predictive mathematical models are no substitute in our current era of uncertainty.
*Ian Scoones He is an associate professor at the Institute of Development Studies.
This text was originally published in The Conversation
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