What are the underpinning necessities or conditions—the essential ingredients—that lead to and engender the qualities or characteristics of the complex world, especially its processual and emergent nature?
Three conditions for complexity: the essential ingredients
A watch or intricate machine is not complex. Nor is a saucer of water. So, when do we regard something as complex? What are the necessary conditions for complexity fully to be realised?
How can a modern university train highly qualified specialists who are able to rethink and unambiguously solve wicked problems?
Here I build on my previous i2Insights contribution Systems transdisciplinarity as a metadiscipline, the methodology of which aims to unify and generalize complementary and non-complementary disciplinary knowledge and methodologies. This metadiscipline provides the basis of a proposed curriculum for a two-year training program at the masters level. The intention is that specialists would be trained in systems transdisciplinarity using a single curriculum to ensure a uniform level of professional capabilities and competencies.
The curriculum
The curriculum involves the organization of training in four sections.
How can i2Insights best capitalise on its first ten years and the wealth of resources contributed from around the world? How can you contribute to strengthening the i2Insights toolkit?
On 25 November 2025, i2Insights celebrates its 10th birthday as a toolkit to support researchers and educators tackling complex societal and environmental problems, specifically providing tools to understand and address complexity. It sets out to be:
global, with contributions from around the world
comprehensive, tackling all aspects of addressing complex problems
living, continuing to grow and stay up-to-date.
It’s a good time to reinvigorate the aims, strengthen the toolkit and celebrate achievements.
How can transdisciplinarity in Africa help achieve higher education’s third mission, namely making a contribution to society? What are the best pathways for achieving this? What are the key obstructions and potential ways around them?
Higher education’s third mission involves adding to the first two missions of teaching and research towards providing service to society. However, general pathways to achieving this are still unclear. A few studies have explored how and why the local impacts of universities need to be measured, but these are generally from outside Africa and concentrate more on quantitative methods to measure specific impact, such as economic impact.
Transdisciplinarity provides opportunities to consider the diversity of societal needs and values, to benefit from local knowledge, to involve scientific disciplines, stakeholders and target groups.
As the importance of interdisciplinary and transdisciplinary research approaches becomes more widely recognised, how can we overcome the danger that they are seen to be all that is needed for tackling complex problems? What are the limitations of these approaches? What else might be required?
My starting point is that improved understanding of, and action on, a complex societal or environmental problem usually requires a number of research questions to be addressed. Different questions require different kinds of research approaches. Let’s illustrate this by considering the following complex problem:
As effort goes into making cities more sustainable, how can we incorporate illicit drug users into a more sustainable city X?
Why is an appreciation of imperfection and its inevitability important for those seeking to understand and act on complex societal and environmental problems? Which traps can imperfection lead to and what are the most effective ways of dealing with it?
The inevitability of imperfection
Imperfection is inevitable both in attempting to develop a comprehensive understanding of complex societal and environmental problems and in acting on them. The multiple underpinning reasons include:
● Complex problems are systems problems, and all systems views are partial, so that the whole system cannot be taken into account. Even then, boundaries need to be set to effectively deploy available resources and these artificial boundaries further constrain understanding of the whole system.
How can researchers interested in tackling complex societal and environmental problems easily find and draw on what they need from inter- and transdisciplinary approaches, systems thinking, action research, post-normal science and a range of other ways of combining disciplinary and stakeholder perspectives in order to bring about improvements? How can the necessary expertise be fostered and supported in a systematic way?
These are the questions that I have been addressing for more than 20 years in considering whether a new discipline – Integration and Implementation Sciences or i2S – could provide a way forward. i2S 3.0 is the third conceptualization of this discipline and the current version is summarised in the figure below.
At this stage in its development, i2S is focused on providing a framework and conduit for sharing concepts, methods, processes and other tools that are currently fragmented across inter- and transdisciplinarity, systems thinking, action research, post-normal science and other approaches.
What is a useful systemic process for tackling complex societal and environmental problems?
The Intervention Design Process (IDP) is a non-linear approach that integrates different models, methods, techniques, and tools in a set of four iterative stages that are both systematic and systemic (Marín-Vanegas, 2023). The four phases – captured in the acronym IDP-3DC – are:
Would systems thinking realize its potential as a force for good in the world if it rediscovered and developed its pragmatist roots? Does the link between the past and future of systems thinking lie through critical systems thinking and practice?
In brief, I suggest that:
Pragmatism provides an appropriate philosophy for systems thinking.
Systems thinking has pragmatist roots.
Critical systems thinking and practice shows how to develop those roots.
Pragmatism can help systems thinking realize its potential and systems thinking can help pragmatism achieve what it set out to do.
What is pragmatism?
Kant was in awe of Newton’s science but believed it could supply certainty only about the physical world. In most areas of human endeavor, he argued, we have to use ‘pragmatic belief’ to guide our actions.
How does the way we approach complex problems differ from how we approach problems that are familiar or obvious?
In this i2Insights contribution, I explore four kinds of reasoning:
Deduction
Induction
Abduction
Design abduction.
Design abduction is the brain-child of Professor Kees Dorst (2015). In simplified terms, these different kinds of reasoning can be compared as follows (Watson and Dorst, 2022, p. 3; taken from Dorst, 2015, pp. 46-49):
Post-normal science comes into play for decision-making on policy issues where facts are uncertain, values in dispute, stakes high and decisions urgent.
A good example of a problem requiring post-normal science is the actions that need to be taken to mitigate the effects of sea level rise consequent on global climate change. All the causal elements are uncertain in the extreme, at stake is much of the built environment and the settlement patterns of people, what to save and what to sacrifice is in dispute, and the window for decision-making is shrinking. The COVID-19 pandemic is another instance of a post-normal science problem. The behaviour of the current and emerging variants of the virus is uncertain, the values of socially intrusive remedies are in dispute, and obviously stakes are high and decisions urgent.
In such contexts of policy making, normal science (in the Kuhnian sense, see Kuhn 1962) is still necessary, but no longer sufficient.
How can we forge a new alliance between the natural and human sciences in order to deal with complex problems? Can economics and engineering show the way? Where does transdisciplinarity fit?
Ilya Prigogine based his 1990s theory of complexity on the need for a “new alliance” between the natural and human sciences in order to restore a unified knowledge based on plurality, diversity and multiple perspectives.
I explore what this would mean if we focus on two disciplines – economics and engineering – in the context of one complex problem: a future society increasingly influenced by the cluster of organizational and market innovations induced by Artificial Intelligence technologies.
Economists and engineers have played a vital role in the evolution of our modern society. The related disciplines have intertwined with each other, leading to mutual cross-fertilization. Nevertheless, Artificial Intelligence sheds light on the inadequacy of both the economics and engineering mainstreams and their relevant paradigms in dealing with, and responding to, the profound economic, ethical and social transformations that have brought humanity into a new “complexity era.”
