Complexity Digest (@cxdig)

Bacterial sensors poised at criticality | Nature Physics Junhua Yuan Nature Physics (2026) Spontaneous switching between active and inactive states in bacterial chemosensory arrays is shown to operate near a critical point. Through biologically controlled disorder, cells balance high signal gain with fast response. Read the full article at: www.nature.com

Bacterial sensors poised at criticality | Nature Physics

01.03.2026 15:42 👍 1 🔁 0 💬 0 📌 0

Optimizing economic complexity Viktor Stojkoski, César A. Hidalgo Research Policy Volume 55, Issue 4, May 2026, 105454 Efforts to apply economic complexity to identify diversification opportunities often rely on diagrams comparing the relatedness and complexity of products, technologies, or industries. Yet, the use of these diagrams, is not based on empirical or theoretical evidence supporting some notion of optimality. Here, we introduce an optimization-based framework that identifies diversification opportunities by minimizing a cost function capturing the constraints imposed by an economy's pattern of specialization. We show that the resulting portfolios often differ from those implied by relatedness–complexity diagrams, providing a target-oriented optimization layer to the economic complexity toolkit. Read the full article at: www.sciencedirect.com

Optimizing economic complexity - ScienceDirect

28.02.2026 16:12 👍 3 🔁 1 💬 0 📌 0

A Disproof of Large Language Model Consciousness: The Necessity of Continual Learning for Consciousness Erik Hoel Scientific theories of consciousness should be falsifiable and non-trivial. Recent research has given us formal tools to analyze these requirements of falsifiability and non-triviality for theories of consciousness. Surprisingly, many contemporary theories of consciousness fail to pass this bar, including theories based on causal structure but also (as I demonstrate) theories based on function. Herein, I show these requirements of falsifiability and non-triviality especially constrain the potential consciousness of contemporary Large Language Models (LLMs) because of their proximity to systems that are equivalent to LLMs in terms of input/output function; yet, for these functionally equivalent systems, there cannot be any falsifiable and non-trivial theory of consciousness that judges them conscious. This forms the basis of a disproof of contemporary LLM consciousness. I then show a positive result, which is that theories of consciousness based on (or requiring) continual learning do satisfy the stringent formal constraints for a theory of consciousness in humans. Intriguingly, this work supports a hypothesis: If continual learning is linked to consciousness in humans, the current limitations of LLMs (which do not continually learn) are intimately tied to their lack of consciousness. Read the full article at: arxiv.org

[2512.12802] A Disproof of Large Language Model Consciousness: The Necessity of Continual Learning for Consciousness

28.02.2026 15:53 👍 0 🔁 0 💬 0 📌 0

Critical phase transition in bee movement dynamics can be modeled using a two-dimensional cellular automaton Ivan Shpurov and Tom Froese Phys. Rev. E 113, 024405 The collective behavior of numerous animal species, including insects, exhibits scale-free behavior indicative of the critical (second-order) phase transition. Previous research uncovered such phenomena in the behavior of honeybees, most notably the long-range correlations in space and time. Furthermore, it was demonstrated that the bee activity in the hive manifests the hallmarks of the jamming process. We follow up by presenting a discrete model of the system that faithfully replicates some of the key features found in the data, such as the divergence of correlation length and scale-free distribution of jammed clusters. The dependence of the correlation length on the control parameter, density, is demonstrated for both the real data and the model. We conclude with a brief discussion on the contribution of the insights provided by the model to our understanding of the insects' collective behavior. Read the full article at: link.aps.org

Critical phase transition in bee movement dynamics can be modeled using a two-dimensional cellular automaton | Phys. Rev. E

24.02.2026 19:21 👍 0 🔁 0 💬 0 📌 0

Calls for the 2026 CSS Emerging Researcher, Junior, and Senior Scientific Awards The Complex Systems Society announces the 2026 edition of the CSS Scientific Awards. The Emerging Researcher Award recognizes promising researchers in Complex Systems within 3 years of their PhD defense. The Junior Scientific Award is aimed at recognizing excellent scientific record of young researchers within 10 years of their PhD defense. The Senior Scientific Award will recognize outstanding contributions of Complex Systems scholars at any stage of their careers. Deadline: April 30th, 2026. See https://cssociety.org/community/awards for the list of previous awardees. More at: cssociety.org

Calls for the 2026 CSS Emerging Researcher, Junior, and Senior Scientific Awards

23.02.2026 19:20 👍 0 🔁 1 💬 0 📌 0

The cultural evolution of pluralistic ignorance Sergey Gavrilets, Johannes Karl, and Michele J. Gelfand PNAS 123 (7) e2522998123 People often get public opinion wrong, assuming their own views are unpopular when in fact many others share them. This widespread misperception, called pluralistic ignorance, can trap societies in harmful or outdated norms. We build a mathematical model showing how these misperceptions form and change over time, depending on whether cultures are “tight” (with strict norms) or “loose” (with flexible ones). Our results explain why support for issues like climate action or women’s rights is often underestimated, and why change happens faster in some societies than others. The model also points to practical solutions: in loose cultures, sharing accurate information works best, while in tight ones, lowering the costs of speaking up can spark social change. Read the full article at: www.pnas.org

The cultural evolution of pluralistic ignorance

23.02.2026 15:28 👍 0 🔁 0 💬 0 📌 0

Iain Couzin: The Geometry of Decision-Making in Networked Biological Systems https://www.youtube.com/watch?v=e-qtUMRMdUY&t=2sNetwork Science Colloquium Series, 09/24/2025 In 1905 the biologist Edmund Selous wrote of his wonderment when observing a flock of starlings flying overhead “they circle; now dense like a polished roof, now disseminated like the meshes of some vast all-heaven-sweeping net...wheeling, rending, darting...a madness in the sky”. He went on to speculate “They must think collectively, all at the same time, or at least in streaks or patches — a square yard or so of an idea, a flash out of so many brains”. Today, we still know relatively little about how the network of social interactions connect brains—and thus how sensing and information processing arises in such organismal collectives. Employing automated tracking, computational reconstruction of sensory information, and immersive ‘holographic’ virtual reality (VR) experiments, I will discuss newly-discovered geometric principles of collective decision-making that occur across scales of biological organization; from neural networks to the social networks of animal groups. I will also show how this finding can impact humans, including how it can be translated to highly effective control laws for swarming robots, as well as how it has transformed our understanding of locust swarms, one of the most destructive natural phenomena on Earth. Watch at: www.youtube.com

Iain Couzin

23.02.2026 14:57 👍 1 🔁 0 💬 0 📌 0

Self-Organizing Railway Traffic Management Federico Naldini, Fabio Oddi, Leo D'Amato, Grégory Marlière, Vito Trianni, Paola Pellegrini Improving traffic management in case of perturbation is one of the main challenges in today's railway research. The great majority of the existing literature proposes approaches to make centralized decisions to minimize delay propagation. In this paper, we propose a new paradigm to the same aim: we design and implement a modular process to allow trains to self-organize. This process consists in having trains identifying their neighbors, formulating traffic management hypotheses, checking their compatibility and selecting the best ones through a consensus mechanism. Finally, these hypotheses are merged into a directly applicable traffic plan. In a thorough experimental analysis on a portion of the Italian network, we compare the results of self-organization with those of a state-of-the-art centralized approach. In particular, we make this comparison mimicking a realistic deployment thanks to a closed-loop framework including a microscopic railway simulator. The results indicate that self-organization achieves better results than the centralized algorithm, specifically thanks to the definition and exploitation of the instance decomposition allowed by the proposed approach. Read the full article at: arxiv.org

Self-Organizing Railway Traffic Management

21.02.2026 21:29 👍 0 🔁 0 💬 0 📌 0

The meaning of life in a universe whose ultimate origins are unknown John E. Stewart BioSystems Volume 262, April 2026, 105733 Our universe appears to be fine-tuned for life. But once life emerges, it does not evolve randomly. Evolution has a trajectory. Both evolvability and cooperative integration increase as evolution proceeds. Until now, this trajectory has largely been driven blindly by gene-based natural selection. But humans are developing cognitive capacities that are far superior than natural selection at adapting and evolving humanity. These capacities will enable humanity to use an understanding of evolution's future trajectory to guide its own evolution, avoiding the destructive selection that will otherwise reinforce the trajectory. Humans who help realize this potential will be fulfilling vital evolutionary roles that are meaningful and purposeful in a much larger scheme of things. The paper considers whether these roles remain meaningful when considered in the wider context of possible origins of the universe. But this analysis is faced with a potentially infinite number of origin hypotheses (including innumerable ‘God hypotheses’), which are not falsified by current knowledge. The paper addresses this challenge using methods that enable rational decision-making despite radical uncertainty. Broadly, this approach reinforces the conclusions reached by consideration of the evolutionary trajectory within the universe, and opens some new possibilities. Finally, the paper demonstrates that extending this analysis also largely overcomes Hume's critique of induction, placing scientific methodologies on a firmer footing. It achieves this by recognising that a universe which exhibits a trajectory towards increasing evolvability must contain discoverable regularities that provide adaptive advantages for evolvability. Read the full article at: www.sciencedirect.com

The meaning of life in a universe whose ultimate origins are unknown

21.02.2026 03:11 👍 1 🔁 1 💬 0 📌 0

Elections – yrCSS The yrCSS Advisory Board is composed of six members and is partially renewed every year. This year, there are three vacant places with a mandate of two years. We are therefore looking for motivated early-career researchers who wish to be a part of the Advisory Board. Please, consider applying and/or spreading this call. Application deadline: February 28th Voting: March 1-15th More at: yrcss.cssociety.org

Elections – yrCSS

21.02.2026 01:10 👍 4 🔁 1 💬 0 📌 0

Mechanistic interplay between information spreading and opinion polarization Kleber Andrade Oliveira , Henrique Ferraz de Arruda , Yamir Moreno PNAS Nexus, Volume 5, Issue 1, January 2026, pgaf402 We investigate how information-spreading mechanisms affect opinion dynamics and vice versa via an agent-based simulation on adaptive social networks. First, we characterize the impact of reposting on user behavior with limited memory, a feature that introduces novel system states. Then, we build an experiment mimicking information-limiting environments seen on social media platforms and study how the model parameters can determine the configuration of opinions. In this scenario, different posting behaviors may sustain polarization or reverse it. We further show the adaptability of the model by calibrating it to reproduce the statistical organization of information cascades as seen empirically in a microblogging social media platform. Our model combines mechanisms for platform content recommendation, connection rewiring, and limited-attention user behavior, paving the way for a robust understanding of echo chambers as a specialized phenomenon of opinion polarization. Read the full article at: academic.oup.com

Mechanistic interplay between information spreading and opinion polarization | PNAS Nexus | Oxford Academic

21.02.2026 00:30 👍 1 🔁 0 💬 0 📌 0

Bootstrapping Life-Inspired Machine Intelligence: The Biological Route from Chemistry to Cognition and Creativity Giovanni Pezzulo, Michael Levin Achieving advanced machine intelligence remains a central challenge in AI research, often approached through scaling neural architectures and generative models. However, biological systems offer a broader repertoire of strategies for adaptive, goal-directed behavior - strategies that emerged long before nervous systems evolved. This paper advocates a genuinely life-inspired approach to machine intelligence, drawing on principles from biology that enable robustness, autonomy, and open-ended problem-solving across scales. We frame intelligence as flexible problem-solving, following William James, and develop the concept of "cognitive light cones" to characterize the continuum of intelligence in living systems and machines. We argue that biological evolution has discovered a scalable recipe for intelligence - and the progressive expansion of organisms' "cognitive light cone", predictive and control capacities. To explain how this is possible, we distill five design principles - multiscale autonomy, growth through self-assemblage of active components, continuous reconstruction of capabilities, exploitation of physical and embodied constraints, and pervasive signaling enabling self-organization and top-down control from goals - that underpin life's ability to navigate creatively diverse problem spaces. We discuss how these principles contrast with current AI paradigms and outline pathways for integrating them into future autonomous, embodied, and resilient artificial systems. Read the full article at: arxiv.org

[2602.08079] Bootstrapping Life-Inspired Machine Intelligence: The Biological Route from Chemistry to Cognition and Creativity

20.02.2026 21:26 👍 1 🔁 0 💬 0 📌 0

Graphs are maximally expressive for higher-order interactions Tiago P. Peixoto, Leto Peel, Thilo Gross, Manlio De Domenico We demonstrate that graph-based models are fully capable of representing higher-order interactions, and have a long history of being used for precisely this purpose. This stands in contrast to a common claim in the recent literature on "higher-order networks" that graph-based representations are fundamentally limited to "pairwise" interactions, requiring hypergraph formulations to capture richer dependencies. We clarify this issue by emphasizing two frequently overlooked facts. First, graph-based models are not restricted to pairwise interactions, as they naturally accommodate interactions that depend simultaneously on multiple adjacent nodes. Second, hypergraph formulations are strict special cases of more general graph-based representations, as they impose additional constraints on the allowable interactions between adjacent elements rather than expanding the space of possibilities. We show that key phenomenology commonly attributed to hypergraphs -- such as abrupt transitions -- can, in general, be recovered exactly using graph models, even locally tree-like ones, and thus do not constitute a class of phenomena that is inherently contingent on hypergraphs models. Finally, we argue that the broad relevance of hypergraphs for applications that is sometimes claimed in the literature is not supported by evidence. Instead it is likely grounded in misconceptions that network models cannot accommodate multibody interactions or that certain phenomena can only be captured with hypergraphs. We argue that clearly distinguishing between multivariate interactions, parametrized by graphs, and the functions that define them enables a more unified and flexible foundation for modeling interacting systems. Read the full article at: arxiv.org

Graphs are maximally expressive for higher-order interactions

20.02.2026 18:31 👍 1 🔁 0 💬 0 📌 0

Is Every Cognitive Phenomenon Computable? Fernando Rodriguez-Vergara and Phil Husbands Mathematics 2026, 14(3), 535 According to the Church–Turing thesis, the limit of what is computable is bounded by Turing machines. Following from this, given that general computable functions formally describe the notion of recursive mechanisms, it is sometimes argued that every organismic process that specifies consistent cognitive responses should be both limited to Turing machine capabilities and amenable to formalization. There is, however, a deep intuitive conviction permeating contemporary cognitive science, according to which mental phenomena, such as consciousness and agency, cannot be explained by resorting to this kind of framework. In spite of some exceptions, the overall tacit assumption is that whatever the mind is, it exceeds the reach of what is described by notions of computability. This issue, namely the nature of the relation between cognition and computation, becomes particularly pertinent and increasingly more relevant as a possible source of better understanding the inner workings of the mind, as well as the limits of artificial implementations thereof. Moreover, although it is often overlooked or omitted so as to simplify our models, it will probably define, or so we argue, the direction of future research on artificial life, cognitive science, artificial intelligence, and related fields. Read the full article at: www.mdpi.com

Is Every Cognitive Phenomenon Computable?

20.02.2026 01:23 👍 2 🔁 1 💬 0 📌 0

Call for Abstracts: The International Conference on Computational Social Science (IC2S2) Burlington, Vermont, USA | July 28-31, 2026 Call for Abstracts The International Conference on Computational Social Science (IC2S2) is the premier conference bringing together researchers from different disciplines interested in using computational and data-intensive methods to address relevant societal problems. IC2S2 hosts academics and practitioners in computational science, social science, complexity, and network science, and provides a platform for new research in the field of computational social science. More at: ic2s2-2026.org

Call for Abstracts: The International Conference on Computational Social Science (IC2S2)

19.02.2026 23:31 👍 0 🔁 0 💬 0 📌 0

ESSA Summer School 2026: Introduction to Agent-Based Modelling | Integrated socio-environmental modelling of policy scenarios for Scotland As part of the European Social Simulation Association's life-long learning strategy, the ESSA Summer School 2026 will take place from Monday 17 to Friday 21 August 2026 at the James Hutton Institute, Aberdeen. Led by Gary Polhill, this one-week intensive course offers an introduction to agent-based modelling (ABM), connecting theories of complex systems with practical model design, programming, and experimentation in NetLogo. Participants will learn how agent-based models can represent heterogeneous actors, dynamic environments, and emergent socio-ecological patterns. The course combines conceptual theory, coding exercises, and group projects to help participants understand the purpose, design, and implementation of ABMs for socio-environmental systems. Key themes include:Complex systems thinking and agent-based theoryTranslating conceptual systems into computational modelsProgramming ABMs in NetLogo and developing clear model structuresSetting up experiments, analysing results, and communicating model findingsThe summer school is designed for PhD students, researchers, and practitioners interested in modelling socio-ecological systems, environmental policy, behavioural dynamics, and other complex adaptive systems. More at: large-scale-modelling.hutton.ac.uk

ESSA Summer School 2026: Introduction to Agent-Based Modelling | Integrated socio-environmental modelling of policy scenarios for Scotland

19.02.2026 22:28 👍 1 🔁 0 💬 0 📌 0

Complex Networks Theory, Methods, and Applications 10th edition May 18-22, 2026 Villa del Grumello, Como, Italy Many real systems can be modeled as networks, where the elements of the system are nodes and interactions between elements are edges. An even larger set of systems can be modeled using dynamical processes on networks, which are in turn affected by the dynamics. Networks thus represent the backbone of many complex systems, and their theoretical and computational analysis makes it possible to gain insights into numerous applications. Networks permeate almost every conceivable discipline – including sociology, transportation, economics and finance, biology, and myriad others – and the study of “network science” has thus become a crucial component of modern scientific education. The school “Complex Networks: Theory, Methods, and Applications” offers a succinct education in network science. It is open to all aspiring scholars in any area of science or engineering who wish to study networks of any kind (whether theoretical or applied), and it is especially addressed to doctoral students and young postdoctoral scholars. The aim of the school is to deepen into both theoretical developments and applications in targeted fields. Read the full article at: ntml.lakecomoschool.org

Complex Networks Theory, Methods, and Applications

19.02.2026 21:27 👍 1 🔁 0 💬 0 📌 0

MPIDR - Doctoral Student Position The Max Planck Institute for Demographic Research (MPIDR) in Rostock is one of the leading demographic research centers in the world. It's part of the Max Planck Society, the internationally renowned German research society.More at: www.demogr.mpg.de

MPIDR - Doctoral Student Position

18.02.2026 22:23 👍 1 🔁 0 💬 0 📌 0

Complexity72h 2026 – Call for Participants Complexity72h is a cross-disciplinary workshop where young researchers work in small interdisciplinary teams on a real research project in complex systems over 72 intense hours. 📍 June 21–26, 2026 | Northeastern University London 👩‍🔬 Open to Master’s students, PhD students, and postdocs 📌 Application deadline: February 28th, 2026 Registration fee: €710 (includes 5 nights accommodation, workshop facilities, coffee breaks, lunches, invited lectures, and social events). More information and applications: https://complexity72h.com

Complexity72h 2026 – Call for Participants

17.02.2026 19:10 👍 0 🔁 0 💬 0 📌 0

The Mythology Of Conscious AI Anil Seth Why consciousness is more likely a property of life than of computation and why creating conscious, or even conscious-seeming AI, is a bad idea. Read the full article at: www.noemamag.com

The Mythology Of Conscious AI

15.02.2026 21:01 👍 0 🔁 0 💬 0 📌 0

Discovering network dynamics with neural symbolic regression Zihan Yu, Jingtao Ding & Yong Li Nature Computational Science (2025) Network dynamics are fundamental to analyzing the properties of high-dimensional complex systems and understanding their behavior. Despite the accumulation of observational data across many domains, mathematical models exist in only a few areas with clear underlying principles. Here we show that a neural symbolic regression approach can bridge this gap by automatically deriving formulas from data. Our method reduces searches on high-dimensional networks to equivalent one-dimensional systems and uses pretrained neural networks to guide accurate formula discovery. Applied to ten benchmark systems, it recovers the correct forms and parameters of underlying dynamics. In two empirical natural systems, it corrects existing models of gene regulation and microbial communities, reducing prediction error by 59.98% and 55.94%, respectively. In epidemic transmission across human mobility networks of various scales, it discovers dynamics that exhibit the same power-law distribution of node correlations across scales and reveal country-level differences in intervention effects. These results demonstrate that machine-driven discovery of network dynamics can enhance understandings of complex systems and advance the development of complexity science. Read the full article at: www.nature.com

Discovering network dynamics with neural symbolic regression | Nature Computational Science

14.02.2026 21:00 👍 1 🔁 0 💬 0 📌 0

Interplay of sync and swarm: Theory and application of swarmalators Gourab Kumar Sar, Kevin O’Keeffe, Joao U.F. Lizárraga, Marcus A.M. de Aguiar, Christian Bettstetter, Dibakar Ghosh Physics Reports Volume 1167, 14 April 2026, Pages 1-52 Swarmalators, entities that combine the properties of swarming particles with synchronized oscillations, represent a novel and growing area of research in the study of collective behavior. This review provides a comprehensive overview of the current state of swarmalator research, focusing on the interplay between spatial organization and temporal synchronization. After a brief introduction to synchronization and swarming as separate phenomena, we discuss the various mathematical models that have been developed to describe swarmalator systems, highlighting the key parameters that govern their dynamics. The review also discusses the emergence of complex patterns, such as clustering, phase waves, and synchronized states, and how these patterns are influenced by factors such as interaction range, coupling strength, and frequency distribution. Recently, some minimal models were proposed that are solvable and mimic real-world phenomena. The effect of predators in the swarmalator dynamics is also discussed. Finally, we explore potential applications in fields ranging from robotics to biological systems, where understanding the dual nature of swarming and synchronization could lead to innovative solutions. By synthesizing recent advances and identifying open challenges, this review aims to provide a foundation for future research in this interdisciplinary field. Read the full article at: www.sciencedirect.com

Interplay of sync and swarm: Theory and application of swarmalators - ScienceDirect

13.02.2026 20:57 👍 0 🔁 0 💬 0 📌 0

From Statistical Mechanics to Nonlinear Dynamics and into Complex Systems Alberto Robledo Complexities 2026, 2(1), 3 We detail a procedure to transform the current empirical stage in the study of complex systems into a predictive phenomenological one. Our approach starts with the statistical-mechanical Landau-Ginzburg equation for dissipative processes, such as kinetics of phase change. Then, it imposes discrete time evolution to explicit back feeding, and adopts a power-law driving force to incorporate the onset of chaos, or, alternatively, criticality, the guiding principles of complexity. One obtains, in closed analytical form, a nonlinear renormalization-group (RG) fixed-point map descriptive of any of the three known (one-dimensional) transitions to or out of chaos. Furthermore, its Lyapunov function is shown to be the thermodynamic potential in q-statistics, because the regular or multifractal attractors at the transitions to chaos impose a severe impediment to access the system’s built-in configurations, leaving only a subset of vanishing measure available. To test the pertinence of our approach, we refer to the following complex systems issues: (i) Basic questions, such as demonstration of paradigms equivalence, illustration of self-organization, thermodynamic viewpoint of diversity, biological or other. (ii) Derivation of empirical laws, e.g., ranked data distributions (Zipf law), biological regularities (Kleiber law), river and cosmological structures (Hack law). (iii) Complex systems methods, for example, evolutionary game theory, self-similar networks, central-limit theorem questions. (iv) Condensed-matter physics complex problems (and their analogs in other disciplines), like, critical fluctuations (catastrophes), glass formation (traffic jams), localization transition (foraging, collective motion). Read the full article at: www.mdpi.com

From Statistical Mechanics to Nonlinear Dynamics and into Complex Systems

13.02.2026 18:08 👍 2 🔁 0 💬 0 📌 0

The Effects of Remote Working on Scientific Collaboration and Impact The Effects of Remote Working on Scientific Collaboration and Impact Sara Venturini, Satyaki Sikdar, Martina Mazzarello, Francesco Rinaldi, Francesco Tudisco, Paolo Santi, Santo Fortunato, Carlo Ratti The COVID-19 pandemic shifted academic collaboration from in-person to remote interactions. This study explores, for the first time, the effects on scientific collaborations and impact of such a shift, comparing research output before, during, and after the pandemic. Using large-scale bibliometric data, we track the evolution of collaboration networks and the resulting impact of research over time. Our findings are twofold: first, the geographic distribution of collaborations significantly shifted, with a notable increase in cross-border partnerships after 2020, indicating a reduction in the constraints of geographic proximity. Second, despite the expansion of collaboration networks, there was a concerning decline in citation impact, suggesting that the absence of spontaneous in-person interactions-which traditionally foster deep discussions and idea exchange-negatively affected research quality. As hybrid work models in academia gain traction, this study highlights the need for universities and research organizations to carefully consider the balance between remote and in-person engagement. Read the full article at: arxiv.org

[2511.18481] The Effects of Remote Working on Scientific Collaboration and Impact

13.02.2026 00:56 👍 0 🔁 0 💬 0 📌 0

How malicious AI swarms can threaten democracy Advances in artificial intelligence (AI) offer the prospect of manipulating beliefs and behaviors on a population-wide level (1). Large language models (LLMs) and autonomous agents (2) let influence campaigns reach unprecedented scale and precision. Generative tools can expand propaganda output without sacrificing credibility (3) and inexpensively create falsehoods that are rated as more human-like than those written by humans (3, 4). Techniques meant to refine AI reasoning, such as chain-of-thought prompting, can be used to generate more convincing falsehoods. Enabled by these capabilities, a disruptive threat is emerging: swarms of collaborative, malicious AI agents. Fusing LLM reasoning with multiagent architectures (2), these systems are capable of coordinating autonomously, infiltrating communities, and fabricating consensus efficiently. By adaptively mimicking human social dynamics, they threaten democracy. Because the resulting harms stem from design, commercial incentives, and governance, we prioritize interventions at multiple leverage points, focusing on pragmatic mechanisms over voluntary compliance. DANIEL THILO SCHROEDER, MEEYOUNG CHA, ANDREA BARONCHELLI, NICK BOSTROM, NICHOLAS A. CHRISTAKIS, DAVID GARCIA, AMIT GOLDENBERG, YARA KYRYCHENKO, KEVIN LEYTON-BROWN, NINA LUTZ, GARY MARCUS, FILIPPO MENCZER, GORDON PENNYCOOK, DAVID G. RAND, MARIA RESSA, FRANK SCHWEITZER, DAWN SONG, CHRISTOPHER SUMMERFIELD, AUDREY TANG, JAY J. VAN BAVEL, SANDER VAN DER LINDEN, AND JONAS R. KUNST SCIENCE 22 Jan 2026 Vol 391, Issue 6783 pp. 354-357 Read the full article at: www.science.org

How malicious AI swarms can threaten democracy

12.02.2026 20:54 👍 0 🔁 0 💬 0 📌 0

Call for bids: Conference on Complex Systems (CCS 2028) The Complex Systems Society (CSS) organizes every year the Conference on Complex Systems (CCS), the flagship annual meeting of the international complexity science community. The CSS hereby invites bids to host the 2028 edition of CCS. The conference is typically held in September–October and is intended to be primarily an in-person event, in order to preserve the value of direct interaction and collective discussion that characterize CCS. Hybrid formats may nevertheless be considered in a limited form, in particular to ensure inclusivity for participants who are unable to travel. Interested organizing teams are invited to submit a proposal document outlining their bid. More at: cssociety.org

Call for bids: Conference on Complex Systems (CCS 2028)

12.02.2026 20:11 👍 0 🔁 1 💬 0 📌 0

The case against efficiency: friction in social media Joshua Garland, Joe Bak-Coleman, Susan Benesch, Simon DeDeo, Renee DiResta, Jan Eissfeldt, Seungwoong Ha, John Irons, Chris Kempes, Juniper Lovato, Kristy Roschke, Paul E. Smaldino, Anna B. Stephenson, Thalia Wheatley & Valentina Semenova npj Complexity volume 3, Article number: 5 (2026) Social media platforms frequently prioritize efficiency to maximize ad revenue and user engagement, often sacrificing deliberation, trust, and reflective, purposeful cognitive engagement in the process. This manuscript examines the potential of friction—design choices that intentionally slow user interactions—as an alternate approach. We present a case against efficiency as the dominant paradigm on social media and advocate for a complex systems approach to understanding and analyzing friction. Drawing from interdisciplinary literature, real-world examples, and industry experiments, we highlight the potential for friction to mitigate issues like polarization, disinformation, and toxic content without resorting to censorship. We propose a state space representation of friction to establish a multidimensional framework and language for analyzing the diverse forms and functions through which friction can be implemented. Additionally, we propose several experimental designs to examine the impact of friction on system dynamics, user behavior, and information ecosystems, each designed with complex systems solutions and perspectives in mind. Our case against efficiency underscores the critical role of friction in shaping digital spaces, challenging the relentless pursuit of efficiency and exploring the potential of thoughtful slowing. Read the full article at: www.nature.com

The case against efficiency: friction in social media

01.02.2026 22:52 👍 1 🔁 0 💬 0 📌 0

Cognition spaces: natural, artificial, and hybrid Ricard Solé, Luis F Seoane, Jordi Pla-Mauri, Michael Timothy Bennett, Michael E. Hochberg, Michael Levin Cognitive processes are realized across an extraordinary range of natural, artificial, and hybrid systems, yet there is no unified framework for comparing their forms, limits, and unrealized possibilities. Here, we propose a cognition space approach that replaces narrow, substrate-dependent definitions with a comparative representation based on organizational and informational dimensions. Within this framework, cognition is treated as a graded capacity to sense, process, and act upon information, allowing systems as diverse as cells, brains, artificial agents, and human-AI collectives to be analyzed within a common conceptual landscape. We introduce and examine three cognition spaces -- basal aneural, neural, and human-AI hybrid -- and show that their occupation is highly uneven, with clusters of realized systems separated by large unoccupied regions. We argue that these voids are not accidental but reflect evolutionary contingencies, physical constraints, and design limitations. By focusing on the structure of cognition spaces rather than on categorical definitions, this approach clarifies the diversity of existing cognitive systems and highlights hybrid cognition as a promising frontier for exploring novel forms of complexity beyond those produced by biological evolution. Read the full article at: arxiv.org

Cognition spaces: natural, artificial, and hybrid

01.02.2026 18:53 👍 0 🔁 0 💬 0 📌 0

The software complexity of nations Sándor Juhász, Johannes Wachs, Jermain Kaminski, César A. Hidalgo Research Policy Volume 55, Issue 3, April 2026, 105422 Despite the growing importance of the digital sector, research on economic complexity and its implications continues to rely mostly on administrative records—e.g. data on exports, patents, and employment—that have blind spots when it comes to the digital economy. In this paper we use data on the geography of programming languages used in open-source software to extend economic complexity ideas to the digital economy. We estimate a country's software economic complexity index (ECIsoftware) and show that it complements the ability of measures of complexity based on trade, patents, and research to account for international differences in GDP per capita, income inequality, and emissions. We also show that open-source software follows the principle of relatedness, meaning that a country's entries and exits in programming languages are partly explained by its current pattern of specialization. Together, these findings help extend economic complexity ideas and their policy implications to the digital economy. Read the full article at: www.sciencedirect.com

The software complexity of nations - ScienceDirect

01.02.2026 03:54 👍 2 🔁 0 💬 0 📌 0

Crossing the Functional Desert: Cascade-Driven Assembly and Feasibility Transitions in Early Life Galen J. Wilkerson The origin of life poses a problem of combinatorial feasibility: How can temporally supported functional organization arise in exponentially branching assembly spaces when unguided exploration behaves as a memoryless random walk? We show that nonlinear threshold-cascade dynamics in connected interaction networks provide a minimal, substrate-agnostic mechanism that can soften this obstruction. Below a critical connectivity threshold, cascades die out locally and structured input-output response mappings remain sparse and transient-a "functional desert" in which accumulation is dynamically unsupported. Near the critical percolation threshold, system-spanning cascades emerge, enabling discriminative functional responses. We illustrate this transition using a minimal toy model and generalize the argument to arbitrary networked systems. Also near criticality, cascades introduce finite-timescale structural and functional coherence, directional bias, and weak dynamical path-dependence into otherwise memoryless exploration, allowing biased accumulation. This connectivity-driven transition-functional percolation-requires only generic ingredients: interacting units, nonlinear thresholds, influence transmission, and non-zero coherence times. The mechanism does not explain specific biochemical pathways, but it identifies a necessary dynamical regime in which structured functional organization can emerge and be temporarily supported, providing a physical foundation for how combinatorial feasibility barriers can be crossed through network dynamics alone. Read the full article at: arxiv.org

[2601.06272] Crossing the Functional Desert: Cascade-Driven Assembly and Feasibility Transitions in Early Life

31.01.2026 22:52 👍 0 🔁 1 💬 0 📌 0

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