Complexity Science Could Transform 21st-Century Research — Here’s How
Why Read This
What Makes This Article Worth Your Time
Summary
What This Article Is About
Astrophysicist Adam Frank introduces complexity science as an emerging paradigm that promises to redefine scientific inquiry in the 21st century. Drawing on David Krakauer’s framework from the Santa Fe Institute, Frank contrasts traditional “A systems”—predictable, law-governed phenomena like planetary motion—with “B systems,” which are complex, adaptive, and characterized by emergence, where the whole exhibits properties that cannot be reduced to its parts.
B systems encompass phenomena from hurricanes to societies, unified by four key domains: evolution (selection-driven change), entropy (energy transformation in thermodynamically open systems), dynamics (non-linear, often chaotic behaviors), and computation (information processing). This transdisciplinary approach transcends traditional disciplinary boundaries, positioning complexity science to address urgent questions about life, consciousness, social organization, and planetary co-evolution that define humanity’s future.
Key Points
Main Takeaways
A New Scientific Paradigm
Complexity science represents not merely a specialized field but a fundamentally new approach to organizing intellectual inquiry across domains.
A vs B Systems
A systems follow predictable laws with minimal assumptions; B systems exhibit emergence from nested hierarchies, operating far from equilibrium.
Reductionism’s Inadequacy
Even perfect microscopes resolving subatomic scales prove useless for B systems, where organization patterns matter more than component details.
Four Foundational Domains
Complexity unifies evolution (selection), entropy (energy transformation), dynamics (non-linear behaviors), and computation (information processing).
Transdisciplinary Integration
Complexity transcends physics, biology, computer science, and mathematics—not multidisciplinary but transdisciplinary, creating something entirely new.
Century-Defining Questions
Complexity science addresses humanity’s most pressing puzzles: the nature of life, consciousness, social organization, planetary co-evolution, and AI.
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Article Analysis
Breaking Down the Elements
Main Idea
Paradigmatic Shift Beyond Reductionism
The article argues complexity science represents a fundamental reorganization of scientific inquiry away from reductionist approaches toward studying emergent, self-organizing systems. By distinguishing A systems (governed by simple laws) from B systems (characterized by organization and emergence), Frank positions complexity as the defining framework for 21st-century science because the most consequential questions—from consciousness to climate—involve B systems that reductionism cannot adequately address.
Purpose
Introducing Transformative Framework
Frank aims to introduce general readers to complexity science’s core concepts and significance, translating David Krakauer’s scholarly framework into accessible terms. The piece functions as intellectual recruitment, making the case that complexity represents both the most fertile ground for scientific discovery and the necessary approach for addressing humanity’s urgent challenges, from artificial intelligence to democratic stability.
Structure
Credentialing to Contrast to Domains
Personal Hook (reading experience) → Authority Establishment (Santa Fe Institute, Krakauer) → Conceptual Framework (A vs B systems distinction) → Detailed Elaboration (four domains: evolution, entropy, dynamics, computation) → Transdisciplinary Claims → Future-Oriented Conclusion. This architecture moves from concrete grounding through abstract theory to expansive vision, establishing credibility before making ambitious claims about scientific transformation.
Tone
Enthusiastic, Accessible & Visionary
The tone combines intellectual excitement with clarity, avoiding both condescension and impenetrable jargon. Phrases like “door-jam of a book” and “incomparable Santa Fe Institute” convey genuine enthusiasm while concrete examples (rainforests, hurricanes) ground abstract concepts. The conclusion’s declarative confidence—”the future belongs to complexity”—reflects advocacy for paradigm adoption without defensiveness about challenging established frameworks.
Key Terms
Vocabulary from the Article
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Tough Words
Challenging Vocabulary
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A typical example or pattern; a framework of theories, methods, and standards that shapes how a field understands problems.
“A new science is emerging that promises to become the defining field of the 21st century.”
Organizational structures where systems contain subsystems at multiple levels, each level exhibiting distinct properties.
“Novel structures and behavior that emerge from nested hierarchies of sub-components.”
Forming or belonging to the base or foundation; fundamental or elementary level components.
“Organization patterns that cannot be fully understood by reducing them to their fundamental (or ‘basal’) components.”
The complete range or scope of something; the entire extent from one extreme to another.
“Its purview runs the gamut from hurricanes to viruses to cells to nervous systems to societies.”
Not proceeding in a straight line; exhibiting disproportionate responses where small changes can produce large effects.
“Rich, non-linear, and often chaotic behaviors allow for rich behaviors to emerge.”
Having openings that permit passage; permeable with spaces allowing movement through boundaries.
“The old silos that gave us separate disciplines will still exist but the walls separating them will need to become porous.”
Reading Comprehension
Test Your Understanding
5 questions covering different RC question types
1According to the article, A systems and B systems both require similar methodological approaches, with the primary difference being the scale of phenomena studied.
2What distinguishes B systems from A systems according to David Krakauer’s framework?
3Which sentence best explains why complexity science qualifies as transdisciplinary rather than merely multidisciplinary?
4Evaluate these statements about the four foundational domains of complexity science:
Evolution allows entirely new orders of behavior to emerge through selection processes.
Complex systems are thermodynamically open, pulling energy from surroundings to maintain themselves.
Information use distinguishes living from non-living systems because rocks can store but not process information.
Select True or False for all three statements, then click “Check Answers”
5Based on the article, what can be inferred about the author’s view on the future relationship between traditional disciplines and complexity science?
FAQ
Frequently Asked Questions
Complexity science shifts focus from predictable, law-governed systems (A systems) to emergent, self-organizing systems (B systems) that operate far from equilibrium. Unlike reductionist approaches that break phenomena into components, complexity science studies how organization and interactions at multiple nested levels produce properties that cannot be predicted from studying parts in isolation. It integrates evolution, thermodynamics, dynamics, and information processing in a transdisciplinary framework that transcends traditional disciplinary boundaries.
The four domains are: (1) Evolution—selection processes that allow new orders of behavior to emerge; (2) Entropy—recognition that complex systems are thermodynamically open engines transforming energy; (3) Dynamics—non-linear, often chaotic behaviors described by dynamical system theory; and (4) Computation—systems’ use of information through storage, copying, transmission, and processing. These domains overlap and integrate, distinguishing complexity science from single-discipline approaches that focus on only one or two of these dimensions.
A rainforest ecosystem exemplifies B systems because ‘the interactions between plants, animals, microorganisms, and the environment create a complex web of relationships that cannot be understood by studying individual components in isolation.’ The ecosystem exhibits emergence—properties arising from relationships rather than from any single species or element. Studying individual organisms in isolation misses the dynamic patterns of information, energy flows, and co-evolutionary relationships that define the ecosystem’s organization and behavior, making reductionist approaches inadequate.
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This article is classified as Advanced level, requiring readers to grasp abstract theoretical frameworks, understand meta-level distinctions between scientific paradigms, and appreciate how methodological approaches relate to ontological claims about system types. It assumes familiarity with concepts like reductionism, emergence, and thermodynamics while demanding integration of ideas across physics, biology, mathematics, and information theory. The text’s argumentation about paradigm transformation requires sophisticated conceptual navigation beyond simple factual comprehension.
The Santa Fe Institute (SFI) is a premier research institution dedicated to complexity science, which Frank calls ‘incomparable.’ SFI is publishing a four-volume set of foundational papers in complexity science with annotations by current researchers, demonstrating its role as both historical curator and contemporary leader in the field. David Krakauer, SFI’s head, provides the theoretical framework Frank uses throughout the article, establishing SFI as the institutional center for developing and disseminating complexity science as a coherent paradigm.
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