The field of misinformation studies has experienced a boom of scholarship in recent years. Buoyed by the emergence of information operations surrounding the 2016 election and the rise of so-called “fake news,” researchers hailing from fields ranging from philosophy to computer science have taken up the challenge of detecting, analyzing, and theorizing false and misleading information online. In an attempt to understand the spread of misinformation online, researchers have adapted concepts from different disciplines. Concepts from epidemiology, for example, have opened doors to thinking about spread, contagion, and resistance. The life sciences offer concepts and theories to further extend what we know about how misinformation adapts; by viewing information as an organism within a complex ecosystem, we can better understand why some narratives succeed and others fail. Collaborations between misinformation researchers and life scientists to develop responsible adaptations of fitness models can bolster misinformation research.

This paper investigates the use of Large Language Models (LLMs) in engineering complex systems, demonstrating how they can support designers on detail design phases. Two aerospace cases, a system architecture definition and a CAD model generation activities are studied. The research reveals LLMs' challenges and opportunities to support designers, and future research areas to further improve their application in engineering tasks. It emphasizes the new paradigm of LLMs support compared to traditional Machine Learning techniques, as they can successfully perform tasks with just a few examples.

Designers’ roles are at a turning point of transforming design from an expert-driven design process within an assumed social and economic order to design practices that advocate design-led societal transition toward more sustainable futures. Design education should be adapted accordingly. Introducing the transition design concept into established design education promotes the sustainable society transition by involving more systems thinking from designers in various sectors. This study reports on a pilot practice and reflection on introducing the transition design concept to design students.

This paper explores the interplay of feedback principles in design and systems science. From their roots in engineering, biology, and economics, it investigates intersections between design, cybernetics and servomechanisms. The synthesis emphasizes the need for considering feedback in anticipating unintended consequences and proposes an integrative view reconciling fundamental assumptions from the different fields through simulation. This holistic approach underscores the pivotal role of feedback in understanding and addressing complex phenomena, such as rebound effects, in design science.

This paper outlines the evolution of decision-making spaces through selected instantiations, analyzing the role of design in their utility and identifying preliminary patterns in spatial layout. It builds on the combination of two research fields: A) Decision support systems and B) Creative Spaces. The paper aims to take a first step towards combining these two existing research fields by focusing on the spatial design aspects that foster the convergent aspect of creativity and to provide guidance for further research on the design of decision-making spaces.

The complexity of the products/systems requires an in-depth understanding of variability and its impact on all phases, from design to maintenance. This study explores Variability Management (VM) emphasizing its challenges. Conducting semi-structured interviews with experts at Renault Group, the research examines variability aspects, semantics, methods, challenges, and possible solutions. The findings offer practical insights into industrial-scale variability management, addressing the use case of the automotive industry.

This study proposes a Moon-based factory for space-bound products, aiming to revolutionize space exploration through In-Space Manufacturing (ISM). It defines key elements for lunar manufacturing by adapting Earth-based factory models to lunar conditions.

This contribution builds on the Design Framework for System-of-Systems Resilience to investigate the potential of a new systems resilience measuring approach inspired by the Frailty Index. To explore this research direction, we provide a brief overview of the evolution of the notion of resilience, offer a characterisation of systems resilience as an opposite of systems frailty, and perform a rapid review to identify and inspect existing multi-domain indices of community resilience. Finally, we suggest piloting the proposed system-of-systems resilience index in the Fens in the United Kingdom.

Lab-on-a-Chip (LOC) products for point-of-care diagnostics have gained significant attention. However, there is a lack of systematic approaches for LOC product development. To address this, we introduce an Attribute Dependency Graph exemplary for a magnetophoretic LOC system for pathogen detection. This model organizes dependencies between the design variables and crucial quantities of interest, such as detectability, cost per test, and test duration. The obtained model helps to manage design complexity and can be adapted to other LOC approaches.

This contribution departs from an existing model, the Design Framework for Systems-of-Systems Resilience, to explore systems resilience issues across the health, environmental, and economic domains. The reported research activities include 1) a rapid review to collect a set of systems indicators and 2) a design workshop employing causal loop diagramming to map expected causal influences between indicators. Through this exercise, we examine key themes in this research domain and outline directions for further enquiry, while involving members of the design research community in an open dialogue.

Crises, defined as a period of acute stress on social systems of all kinds, are a recurrent feature of history. As such, they are best approached and understood from a comparative historical perspective. We can distinguish between those caused or precipitated by an exogenous shock and those that derive from an endogenous process that culminates in the crisis. Crises can be of short or long duration and range from local to global. The most severe are ones that lead to a civilizational collapse or radical simplification process. Historically, severe crises have been localized to specific parts of the planet, even when several occur simultaneously because of global natural phenomena, but in the modern world we have truly global crises. Evidence suggests that such a global crisis is imminent or has already commenced. This raises practical and normative pressing issues.

The modern study of resilience in development is conceptually based on a complex adaptive system ontology in which many (intersystem) factors are involved in the emergence of resilient developmental pathways. However, the methods and models developed to study complex dynamical systems have not been widely adopted, and it has recently been noted this may constitute a problem moving the field forward. In the present paper, I argue that an ontological commitment to complex adaptive systems is not only possible, but highly recommended for the study of resilience in development. Such a commitment, however, also comes with a commitment to a different causal ontology and different research methods. In the first part of the paper, I discuss the extent to which current research on resilience in development conceptually adheres to the complex systems perspective. In the second part, I introduce conceptual tools that may help researchers conceptualize causality in complex systems. The third part discusses idiographic methods that could be used in a research program that embraces the interaction dominant causal ontology and idiosyncratic nature of the dynamics of complex systems. The conclusion is that a strong ontological commitment is warranted, but will require a radical departure from nomothetic science.

Plants are complex systems made up of many interacting components, ranging from architectural elements such as branches and roots, to entities comprising cellular processes such as metabolic pathways and gene regulatory networks. The collective behaviour of these components, along with the plant’s response to the environment, give rise to the plant as a whole. Properties that result from these interactions and cannot be attributed to individual parts alone are called emergent properties, occurring at different time and spatial scales. Deepening our understanding of plant growth and development requires computational tools capable of handling a large number of interactions and a multiscale approach connecting properties across scales. There currently exist few methods able to integrate models across scales, or models capable of predicting new emergent plant properties. This perspective explores current approaches to modelling emergent behaviour in plants, with a focus on how current and future tools can handle multiscale plant systems.