Navigating Consequential World Problems: Toward a Better Understanding of Complexity in Political Decision-Making

The study of complexity in political decision-making addresses crucial questions at the intersection of cognitive science, political science, and public policy. In the modern era, complexity underpins the most pressing worldwide challenges—from climate change and economic crises to global health emergencies. These problems are characterized by evolving, interconnected parameters, nonlinear dynamics, and deep uncertainty, making them inherently difficult to analyze, predict, and resolve. Politicians are tasked with making decisions amidst conflicting objectives and ambiguous, changing realities. Information may be out of reach, and data that seem relevant may not be, while seemingly irrelevant cues can matter. There is no single best or optimal solution to consequential world problems because they lack clear answers and can be understood in multiple ways. While such decisions shape economic, social, and governance outcomes, the existing research highlights the ongoing struggle politicians face when navigating complex issues, thus revealing persistent gaps in our understanding of how best to support effective political decision-making.

Recent investigations have demonstrated that even seasoned politicians are not immune to cognitive biases, detrimental reductionistic approaches to information processing, and systematic errors when confronting complex issues. The advent of new digital technologies—ranging from artificial intelligence and simulation tools to immersive environments—has enabled novel approaches to understanding and supporting decision-making processes. Despite the potential of these innovations, a comprehensive framework for understanding how political leaders conceptualize, frame, and address complexity remains underdeveloped. Furthermore, the heterogeneity of interventions designed to support cognition in processing complex information makes it difficult to assess the potential of these innovations to assist political decision-making.

This Research Topic aims to advance our understanding of the cognitive, behavioral, and technological factors shaping political decision-making under complexity. It seeks to promote interdisciplinary contributions that explore how politicians process information, learn, adapt, and attempt to manage consequential world problems—sometimes in an appropriate manner, other times resulting in serious judgment errors—as well as to identify actionable strategies, tools, and protocols to enhance these capabilities. By fostering dialogue across cognitive science, political science, and applied policymaking, this work aspires to lay the groundwork for more robust theories and empirically grounded solutions that prepare decision-makers to manage complexity in an increasingly interconnected world.

To gather further insights in the relationship between human cognition and political complexity, we welcome submissions that focus on, but are not limited to, the following areas:
• Heuristics, cognitive strategies, biases, and errors in complex political decision-making
• Microworld-based studies of complex problem-solving and dynamic political decision-making
• Innovative methods, protocols, decision-support tools, and training programs to enhance political decision-making under complexity
• The role of uncertainty, incomplete information, dynamism, and conflicting objectives in political decision-making
• Case studies on policymaking and governance in the face of high complexity
• Literature reviews that summarize evidence on complexity applied to political decision-making
We invite a variety of article types, including original research, methodological innovations, conceptual analyses, reviews, and case studies.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Conceptual Analysis
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Conceptual Analysis
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Policy and Practice Reviews
• Policy Brief
• Registered Report
• Review
• Study Protocol
• Systematic Review
• Technology and Code

Keywords: political decision-making, complexity, cognition, heuristics, policymaking, decision-support systems

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.