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How Humans Judge Machines

Sun, 10/25/2020 - 11:01

How Humans Judge Machines is a peer-reviewed book comparing people’s reactions to human and machine actions. Through dozens of experiments, it brings us closer to understanding when people judge humans and machines differently, and why.


Capitalism After the Pandemic

Sat, 10/24/2020 - 12:04

Mariana Mazzucato

Foreign Affairs


After the 2008 financial crisis, governments across the world injected over $3 trillion into the financial system. The goal was to unfreeze credit markets and get the global economy working again. But instead of supporting the real economy—the part that involves the production of actual goods and services—the bulk of the aid ended up in the financial sector. Governments bailed out the big investment banks that had directly contributed to the crisis, and when the economy got going again, it was those companies that reaped the rewards of the recovery. Taxpayers, for their part, were left with a global economy that was just as broken, unequal, and carbon-intensive as before. “Never let a good crisis go to waste,” goes a popular policymaking maxim. But that is exactly what happened.


CCS2018 Book of Abstracts

Fri, 10/23/2020 - 14:05

This is the book of Abstracts from the 2018 Conference on Complex Systems held in Thessaloniki, Greece, 23-28 September, 2018.   With this DOI reference any abstract in the CCS2018 Conference can be referenced in other future publications, and easily located as a citation by any other scientists.    It is planned for CCS2020 to also publish the Book of Abstracts in the same way.   In order for your abstract to be included please note that it must conform exactly with the instructions as given in the CCS2020 Website.  


Visualization of dynamic structure in flocking behavior

Thu, 10/22/2020 - 13:39

Daichi Saito, Norihiro Maruyama, Yasuhiro Hashimoto & Takashi Ikegami
Artificial Life and Robotics (2020)


The flock structures produced by individuals, e.g., animals, self-organize and change their complexity over time. Although flock structures are often characterized by the spatial alignment of each element, this study focuses on their dynamic and hierarchical nature, temporal variations, and meta-structures. In hierarchical systems, sometimes, the upper structure is unchanged, whereas the lower components change constantly over time. Current clustering methods aim to capture the static and mono-layer features of complex patterning. To detect and track dynamic and hierarchical objects, a new clustering technique is required. Hence, in this study, we improve the generative topographic mapping (GTM) method to visualize such dynamic hierarchical structures as they continuously change over time. Using examples from our recent studies on the large-scale Boids model, we confirm that the newly developed method can capture the complex flocking objects as well as track the merging and collapsing events of objects.


An experiment to inform universal basic income

Thu, 10/22/2020 - 12:03

As income inequality and economic upheaval take center stage, is a guaranteed minimum income worth considering? Results from a two-year experiment in Finland offer clues.


Networks 2021

Thu, 10/22/2020 - 10:24

Networks 2021: A Joint Sunbelt and NetSci Conference will take place in Washington D.C. on July 6-11, 2021. We expect this to be the largest networks conference ever held. It will combine the annual meeting of the International Network for Social Network Analysis (Sunbelt XLI), and the annual meeting of the Network Science Society (NetSci 2021).


Rise of the Self-Replicators

Wed, 10/21/2020 - 14:30

In Rise of the Self-Replicators we delve into the deep history of thought about machines, AI and robots that can reproduce and evolve. Although these might seem like very modern concepts, we show that people were thinking about them as far back as the mid-1600s and that the discussion gathered pace in the 1800s following the British Industrial Revolution and the publication of Darwin’s On The Origin of Species.

Behind all of the work we discuss lie two central questions:

  1. Is it possible to design robots and other machines that can reproduce and evolve just like biological organisms do?
  2. And, if so, what are the implications: for the machines, for ourselves, for our environment, and for the future of life on Earth and elsewhere?


Lessons from New Zealand’s COVID-19 outbreak response

Wed, 10/21/2020 - 12:00

Alexis Robert

The Lancet


In the absence of a vaccine for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), or of highly effective pharmaceutical treatments for COVID-19, countries have implemented a large range of non-pharmaceutical interventions to control the spread of the virus.1 These interventions differ in their level of stringency (ie, the severity of the measures) and their ultimate objective (eg, prevent health systems being overwhelmed, suppress incidence to low levels, or reduce incidence to zero and keep it there). With many countries facing epidemic resurgence, evaluating the impact of different strategies implemented in the early phases of the pandemic is crucial for developing an effective long-term response.
New Zealand adopted a set of non-pharmaceutical interventions aiming to bring COVID-19 incidence to zero


Emergence of Organisms

Tue, 10/20/2020 - 09:26

Andrea Roli and Stuart A. Kauffman

Entropy 2020, 22(10), 1163


Since early cybernetics studies by Wiener, Pask, and Ashby, the properties of living systems are subject to deep investigations. The goals of this endeavour are both understanding and building: abstract models and general principles are sought for describing organisms, their dynamics and their ability to produce adaptive behavior. This research has achieved prominent results in fields such as artificial intelligence and artificial life. For example, today we have robots capable of exploring hostile environments with high level of self-sufficiency, planning capabilities and able to learn. Nevertheless, the discrepancy between the emergence and evolution of life and artificial systems is still huge. In this paper, we identify the fundamental elements that characterize the evolution of the biosphere and open-ended evolution, and we illustrate their implications for the evolution of artificial systems. Subsequently, we discuss the most relevant issues and questions that this viewpoint poses both for biological and artificial systems.


Cultural complexity and complexity evolution

Sun, 10/11/2020 - 07:44

Dwight Read, Claes Andersson


We review issues stemming from current models regarding the drivers of cultural complexity and cultural evolution. We disagree with the implication of the treadmill model, based on dual-inheritance theory, that population size is the driver of cultural complexity. The treadmill model reduces the evolution of artifact complexity, measured by the number of parts, to the statistical fact that individuals with high skills are more likely to be found in a larger population than in a smaller population. However, for the treadmill model to operate as claimed, implausibly high skill levels must be assumed. Contrary to the treadmill model, the risk hypothesis for the complexity of artifacts relates the number of parts to increased functional efficiency of implements. Empirically, all data on hunter-gatherer artifact complexity support the risk hypothesis and reject the treadmill model. Still, there are conditions under which increased technological complexity relates to increased population size, but the dependency does not occur in the manner expressed in the treadmill model. Instead, it relates to population size when the support system for the technology requires a large population size. If anything, anthropology and ecology suggest that cultural complexity generates high population density rather than the other way around.


Beyond COVID-19: Network science and sustainable exit strategies

Sat, 10/10/2020 - 19:27

James Bell, Ginestra Bianconi, David Butler, Jon Crowcroft, Paul C.W Davies, Chris Hicks, Hyunju Kim, Istvan Z. Kiss, Francesco Di Lauro, Carsten Maple, Ayan Paul, Mikhail Prokopenko, Philip Tee, Sara I. Walker


On May 28th and 29th, a two day workshop was held virtually, facilitated by the Beyond Center at ASU and Moogsoft Inc. The aim was to bring together leading scientists with an interest in Network Science and Epidemiology to attempt to inform public policy in response to the COVID-19 pandemic. Epidemics are at their core a process that progresses dynamically upon a network, and are a key area of study in Network Science. In the course of the workshop a wide survey of the state of the subject was conducted. We summarize in this paper a series of perspectives of the subject, and where the authors believe fruitful areas for future research are to be found.


How Social Media Has Changed Society – Interview with Sinan Aral

Fri, 10/09/2020 - 11:31

Last April, states began to sporadically reopen after weeks of being shut down. Georgia was among the first to begin the process, while some states didn’t start lifting restrictions until June. 

The uncoordinated reopening caused chaos, according to Sinan Aral, director of MIT’s Initiative on the Digital Economy. Why? Because Georgia pulled in hundreds of thousands of visitors from neighboring states – folks hoping to get a haircut or go bowling.

Aral was tracking Americans on social media, and it became clear to him that having uncoordinated coronavirus policies doesn’t make sense. As people watched their social feeds fill with images of people heading back outside, they stepped out too — even if their state wasn’t at the same phase.


Planning for sustainable Open Streets in pandemic cities

Wed, 10/07/2020 - 19:24

Daniel Rhoads, Albert Solé-Ribalta, Marta C. González, Javier Borge-Holthoefer


In the wake of the pandemic, the inadequacy of urban sidewalks to comply with social distancing remains untackled in academy. Beyond isolated efforts (from sidewalk widenings to car-free Open Streets), there is a need for a large-scale and quantitative strategy for cities to handle the challenges that COVID-19 poses in the use of public space. The main obstacle is a generalized lack of publicly available data on sidewalk infrastructure worldwide, and thus city governments have not yet benefited from a complex systems approach of treating urban sidewalks as networks. Here, we leverage sidewalk geometries from ten cities in three continents, to first analyze sidewalk and roadbed geometries, and find that cities most often present an arrogant distribution of public space: imbalanced and unfair with respect to pedestrians. Then, we connect these geometries to build a sidewalk network –adjacent, but not assimilable to road networks, so fertile in urban science. In a no-intervention scenario, we apply percolation theory to examine whether the sidewalk infrastructure in cities can withstand the tight pandemic social distancing imposed on our streets. The resulting collapse of sidewalk networks, often at widths below three meters, calls for a cautious strategy, taking into account the interdependencies between a city’s sidewalk and road networks, as any improvement for pedestrians comes at a cost for motor transport. With notable success, we propose a shared-effort heuristic that delays the sidewalk connectivity breakdown, while preserving the road network’s functionality.


Moving in Sync Creates Surprising Social Bonds among People

Wed, 10/07/2020 - 16:14

Dancing, rowing and even finger tapping in unison unleash powerful forces in the brain that drive good feelings


The Nobel Prize in Chemistry 2020

Wed, 10/07/2020 - 09:15

Emmanuelle Charpentier and Jennifer A. Doudna have discovered one of gene technology’s sharpest tools: the CRISPR/Cas9 genetic scissors. Using these, researchers can change the DNA of animals, plants and microorganisms with extremely high precision. This technology has had a revolutionary impact on the life sciences, is contributing to new cancer therapies and may make the dream of curing inherited diseases come true.


An Overview on Optimal Flocking

Tue, 10/06/2020 - 14:22

Logan E. Beaver, Andreas A. Malikopoulos


The study of robotic flocking has received considerable attention in the past twenty years. As we begin to deploy flocking control algorithms on physical multi-agent and swarm systems, there is an increasing necessity for rigorous promises on safety and performance. In this paper, we present an overview the literature focusing on optimization approaches to achieve flocking behavior that provide strong safety guarantees. We separate the literature into cluster and line flocking, and categorize cluster flocking with respect to the system objective, which may be realized by a reactive, or planning, control algorithm. We also present several approaches aimed at minimizing flocking communication and computational requirements in real systems via neighbor filtering and event-driven planning. We conclude the overview with our perspective on the outlook and future research direction of optimal flocking algorithms.


The Nobel Prize in Physics 2020

Tue, 10/06/2020 - 09:59

Three Laureates share this year’s Nobel Prize in Physics for their discoveries about one of the most exotic phenomena in the universe, the black hole. Roger Penrose showed that the general theory of relativity leads to the formation of black holes. Reinhard Genzel and Andrea Ghez discovered that an invisible and extremely heavy object governs the orbits of stars at the centre of our galaxy. A supermassive black hole is the only currently known explanation.


The Nobel Prize in Physiology or Medicine 2020

Mon, 10/05/2020 - 09:57

This year’s Nobel Prize is awarded to three scientists who have made a decisive contribution to the fight against blood-borne hepatitis, a major global health problem that causes cirrhosis and liver cancer in people around the world.

Harvey J. Alter, Michael Houghton and Charles M. Rice made seminal discoveries that led to the identification of a novel virus, Hepatitis C virus. Prior to their work, the discovery of the Hepatitis A and B viruses had been critical steps forward, but the majority of blood-borne hepatitis cases remained unexplained. The discovery of Hepatitis C virus revealed the cause of the remaining cases of chronic hepatitis and made possible blood tests and new medicines that have saved millions of lives.


The cost of coordination can exceed the benefit of collaboration in performing complex tasks

Sun, 10/04/2020 - 13:27

Vince J. Straub, Milena Tsvetkova, Taha Yasseri


Collective decision-making is ubiquitous when observing the behavior of intelligent agents, including humans. However, there are inconsistencies in our theoretical understanding of whether there is a collective advantage from interacting with group members of varying levels of competence in solving problems of varying complexity. Moreover, most existing experiments have relied on highly stylized tasks, reducing the generality of their results. The present study narrows the gap between experimental control and realistic settings, reporting the results from an analysis of collective problem-solving in the context of a real-world citizen science task environment in which individuals with manipulated differences in task-relevant training collaborated on the Wildcam Gorongosa task, hosted by The Zooniverse. We find that dyads gradually improve in performance but do not experience a collective benefit compared to individuals in most situations; rather, the cost of team coordination to efficiency and speed is consistently larger than the leverage of having a partner, even if they are expertly trained. It is only in terms of accuracy in the most complex tasks that having an additional expert significantly improves performance upon that of non-experts. Our findings have important theoretical and applied implications for collective problem-solving: to improve efficiency, one could prioritize providing task-relevant training and relying on trained experts working alone over interaction and to improve accuracy, one could target the expertise of selectively trained individuals.


K: The Overlooked Variable That’s Driving the Pandemic

Sat, 10/03/2020 - 14:48



There’s something strange about this coronavirus pandemic. Even after months of extensive research by the global scientific community, many questions remain open.

Why, for instance, was there such an enormous death toll in northern Italy, but not the rest of the country? Just three contiguous regions in northern Italy have 25,000 of the country’s nearly 36,000 total deaths; just one region, Lombardy, has about 17,000 deaths. Almost all of these were concentrated in the first few months of the outbreak. What happened in Quito, Ecuador, in April, when so many thousands died so quickly that bodies were abandoned in the sidewalks and streets? Why, in the spring of 2020, did so few cities account for a substantial portion of global deaths, while many others with similar density, weather, age distribution, and travel patterns were spared? What can we really learn from Sweden, hailed as a great success by some because of its low case counts and deaths as the rest of Europe experiences a second wave, and as a big failure by others because it did not lock down and suffered excessive death rates earlier in the pandemic? Why did widespread predictions of catastrophe in Japan not bear out? The baffling examples go on.