In this paper, I discuss the concept of complexity. I show that the principle of natural selection as acting on complexity gives a solution to the problem of reconciling the seemingly contradictory notion of generally increasing complexity and the observation that most species don’t follow such a trend. I suggest the process of evolution to be illustrated by means of a schematic diagram of complexity versus time, interpreted as a form of the Tree of Life. The suggested model implies that complexity is cumulatively increasing, giving evolution a direction, an arrow of time, thus also implying that the latest emerging species will be the one with the highest level of complexity. Since the human species is the last species evolved in the evolutionary process seen at large, this means that we are the species with the highest complexity. The model implies that the human species constitutes an integral part of organic evolution, yet rendering us the exclusive status as the species of the highest complexity.
I have in this thesis suggested a rough and qualitative description of complexity in biology coupled to the level of functional capability of the inner organs, the nervous system and intelligence. I have furthermore suggested that increasing complexity is explained by natural selection and I have shown that these rationales have brought about explications of some contentious problems involved in the basic understanding of the evolutionary process.
It is a common observation that complex systems have a nested or hierarchical structure: they consist of subsystems, which themselves consist of subsystems, and so on, until the simplest components we know, elementary particles. It is also generally accepted that the simpler, smaller components appeared before the more complex, composite systems. Thus, evolution tends to produce more complex systems, gradually adding more levels to the hierarchy. For example, elementary particles evolved subsequently into atoms, molecules, cells, multicellular organisms, and societies of organisms. These discrete steps, characterized by the emergence of a higher level of complexity, may be called “evolutionary transitions”. The logic behind this sequential complexification appears obvious: you can only build a higher order system from simpler systems after these building blocks have evolved themselves. The issue becomes more complicated when you start looking for the precise mechanisms behind these evolutionary transitions, and try to understand which levels have appeared at what moment, and why.
The astonishing new discovery that could change everything . . . Lying inside a high-security vault, deep within the heart of one of the world’s leading natural history museums, is the scientific find of a lifetime – a perfectly fossilized early primate, older than the previously most famous primate fossil, Lucy, by an astonishing forty-four million years. A secret until now, the fossil – ‘Ida’- is the most complete early primate fossil ever found. Forty-seven million years old, Ida rewrites what we’ve assumed about the earliest primate origins. Her completeness is unparalleled. With exclusive access to the first scientists to study her, the award-winning science writer Colin Tudge tells the history of Ida and her place in the world. The Link offers a wide-ranging investigation into Ida and our earliest origins – and the magnificent, cutting-edge scientific detective story that followed her discovery. At the same time it opens a stunningly evocative window into our past and changes what we know about primate evolution and, ultimately, our own.
How did we develop from simple animals inhabiting small pockets of forest in Africa to the dominant species on Earth, capable of sending spaceships to the Moon?
Traveling back almost eight million years to our earliest primate relatives, Evolution: The Human Story charts the development of our species from tree-dwelling primates to modern humans. Evidence for the earliest primates goes back an astonishing 60 million years, but it was around seven million years ago that some apes started walking on two legs. This was the first sign of human-ness, of a lineage that would teeter on the brink of extinction several times, but would then go on to survive and prosper, providing the ancestors of a species that would eventually colonize every continent of the world except Antarctica-Homo sapiens.
Evolution: The Human Story investigates each of our ancestors in detail and in context, from the anatomy of their bones to the environment they lived in. Study of their fossil bones reveals what they ate, how they moved, and even what diseases they had to contend with, while environmental archaeology paints a picture of the world they inhabited. Add to this picture finds such as stone tools, bone and stone carvings, and early art, and Evolution: The Human Story takes on a depth and fascination that is hard to resist.
The ultimate proof of our understanding of natural or technological systems is reflected in our ability to control them. Although control theory offers mathematical tools for steering engineered and natural systems towards a desired state, a framework to control complex self-organized systems is lacking. Here we develop analytical tools to study the controllability of an arbitrary complex directed network, identifying the set of driver nodes with time-dependent control that can guide the system’s entire dynamics. We apply these tools to several real networks, finding that the number of driver nodes is determined mainly by the network’s degree distribution. We show that sparse inhomogeneous networks, which emerge in many real complex systems, are the most difficult to control, but that dense and homogeneous networks can be controlled using a few driver nodes. Counterintuitively, we find that in both model and real systems the driver nodes tend to avoid the high-degree nodes.
Despite recent advances in uncovering the quantitative features of stationary human activity patterns, many applications, from pandemic prediction to emergency response, require an understanding of how these patterns change when the population encounters unfamiliar conditions. To explore societal response to external perturbations we identified real-time changes in communication and mobility patterns in the vicinity of eight emergencies, such as bomb attacks and earthquakes, comparing these with eight non-emergencies, like concerts and sporting events. We find that communication spikes accompanying emergencies are both spatially and temporally localized, but information about emergencies spreads globally, resulting in communication avalanches that engage in a significant manner the social network of eyewitnesses. These results offer a quantitative view of behavioral changes in human activity under extreme conditions, with potential long-term impact on emergency detection and response.
The growth and evolution of networks has elicited considerable interest from the scientific community and a number of mechanistic models have been proposed to explain their observed degree distributions. Various microscopic processes have been incorporated in these models, among them, node and edge addition, vertex fitness and the deletion of nodes and edges. The existing models, however, focus on specific combinations of these processes and parameterize them in a way that makes it difficult to elucidate the role of the individual elementary mechanisms. We therefore formulated and solved a model that incorporates the minimal processes governing network evolution. Some contribute to growth such as the formation of connections between existing pair of vertices, while others capture deletion; the removal of a node with its corresponding edges, or the removal of an edge between a pair of vertices. We distinguish between these elementary mechanisms, identifying their specific role on network evolution.
Community structure is a salient structural characteristic of many real-world networks. Communities are generally hierarchical, overlapping, multi-scale and coexist with other types of structural regularities of networks. This poses major challenges for conventional methods of community detection. This book will comprehensively introduce the latest advances in community detection, especially the detection of overlapping and hierarchical community structures, the detection of multi-scale communities in heterogeneous networks, and the exploration of multiple types of structural regularities. These advances have been successfully applied to analyze large-scale online social networks, such as Facebook and Twitter. This book provides readers a convenient way to grasp the cutting edge of community detection in complex networks.
The thesis on which this book is based was honored with the “Top 100 Excellent Doctoral Dissertations Award” from the Chinese Academy of Sciences and was nominated as the “Outstanding Doctoral Dissertation” by the Chinese Computer Federation.
Our understanding of how individual mobility patterns shape and impact the social network is limited, but is essential for a deeper understanding of network dynamics and evolution. This question is largely unexplored, partly due to the difficulty in obtaining large-scale society-wide data that simultaneously capture the dynamical information on individual movements and social interactions. Here we address this challenge for the first time by tracking the trajectories and communication records of 6 Million mobile phone users. We find that the similarity between two individuals’ movements strongly correlates with their proximity in the social network. We further investigate how the predictive power hidden in such correlations can be exploited to address a challenging problem: which new links will develop in a social network. We show that mobility measures alone yield surprising predictive power, comparable to traditional network-based measures. Furthermore, the prediction accuracy can be signicantly improved by learning a supervised classifier based on combined mobility and network measures. We believe our findings on the interplay of mobility patterns and social ties offer new perspectives on not only link prediction but also network dynamics.
Social groups are fundamental building blocks of human societies. While our social interactions have always been constrained by geography, it has been impossible, due to practical difficulties, to evaluate the nature of this restriction on social group structure. We construct a social network of individuals whose most frequent geographical locations are also known. We also classify the individuals into groups according to a community detection algorithm. We study the variation of geographical span for social groups of varying sizes, and explore the relationship between topological positions and geographic positions of their members. We find that small social groups are geographically very tight, but become much more clumped when the group size exceeds about 30 members. Also, we find no correlation between the topological positions and geographic positions of individuals within network communities. These results suggest that spreading processes face distinct structural and spatial constraints.
Linked: How Everything is Connected to Everything Else and What it Means for Business, Science, and Everyday Life.
Reductionism was the driving force behind much of the twentieth century’s scientific research. To comprehend nature, it tells us, we first must decipher its components. The assumption is that once we understand the parts, it will be easy to grasp the whole. Divide and conquer; the devil is in the details. Therefore, for decades we have been forced to see the world through its constituents. We have been trained to study atoms and superstrings to understand the universe; molecules to comprehend life; individual genes to understand complex human behavior; prophets to see the origins of fads and religions.
Now we are close to knowing just about everything there is to know about the pieces. But we are as far as we have ever been from understanding nature as a whole. Indeed, the reassembly turned out to be much harder than scientists anticipated. The reason is simple: Riding reductionism, we run into the hard wall of complexity. We have learned that nature is not a well-designed puzzle with only one way to put it back together. In complex systems the components can fit in so many different ways that it would take billions of years for us to try them all. Yet nature assembles the pieces with a grace and precision honed over millions of years. It does so by exploiting the allencompassing laws of self-organization, whose roots are still largely a mystery to us.
Professor Barabási’s talk described how the tools of network science can help understand the Web’s structure, development and weaknesses. The Web is an information network, in which the nodes are documents (at the time of writing over one trillion of them), connected by links. Other well-known network structures include the Internet, a physical network where the nodes are routers and the links are physical connections, and organizations, where the nodes are people and the links represent communications.
As a result of studying these networks, Barabási argued that we have seen the emergence of network science, which overlaps with Web science. Network science is an attempt to understand networks emerging in nature, technology and society using a unified set of tools and principles. Despite apparent differences, many networks emerge and evolve, driven by a fundamental set of laws and mechanisms, and these are the province of network science.
From the Internet to networks of friendship, disease transmission, and even terrorism, the concept–and the reality–of networks has come to pervade modern society. But what exactly is a network? What different types of networks are there? Why are they interesting, and what can they tell us? In recent years, scientists from a range of fields–including mathematics, physics, computer science, sociology, and biology–have been pursuing these questions and building a new “science of networks.” This book brings together for the first time a set of seminal articles representing research from across these disciplines. It is an ideal sourcebook for the key research in this fast-growing field.
The book is organized into four sections, each preceded by an editors’ introduction summarizing its contents and general theme. The first section sets the stage by discussing some of the historical antecedents of contemporary research in the area. From there the book moves to the empirical side of the science of networks before turning to the foundational modeling ideas that have been the focus of much subsequent activity. The book closes by taking the reader to the cutting edge of network science–the relationship between network structure and system dynamics. From network robustness to the spread of disease, this section offers a potpourri of topics on this rapidly expanding frontier of the new science.
In his work, Deleuze argued that the sole aim of philosophy was to become “worthy of the event.” This raises the question of whether one could have a philosophy and by extension a politics adequate to the conditions of the event. For Deleuze, the event marks a rupture in the continuity of one’s historical experiences. Events are by definition untimely. An event is time “out of joint.” From this perspective, the event has no evident starting point or terminus. While some may argue that the significance of an event must be measured quantitatively (for example, by how many people are affected by it), one shouldn’t underestimate the importance of the qualitatively singular. What about the event of Deleuze’s work? Many were affected by it. But what is the singularity of his thought? Does it continue to resonate today? How?
Gilles Deleuze left behind a philosophical legacy that went on to influence numerous academic disciplines: continental philosophy, cinema studies, literary theory, cultural criticism, social and political theory, LGBTQ studies, art and architecture theory, as well as the growing field of animal studies and environmental theory. In part this is because Deleuze himself enjoyed such a broad and eclectic range of influences. He innovatively combined the thinking of Bergson, Foucault, Kant, Hume, Lacan, Leibniz, Marx, Nietzsche, and Spinoza with insights on artists such as Bacon and Artaud, novelists like Kafka and Carroll, along with filmmakers such as Herzog, Hitchcock, and Eisenstein. And this is just a brief nod to some of his deepest influences. There are many more. All the intellectual excitement and flurry over Deleuze may confirm the prediction made by his good friend and fellow philosopher, Michel Foucault: “This century [i.e., the 20th century] will be Deleuzian.”
This issue of Systemic Practice and Action Research focuses on the practice of co-operative inquiry, and in particular on the choices and actions of those who initiate and facilitate co-operative inquiry groups. I have been struck how much the people who I talk to about co-operative inquiry want to hear stories: not just the theory and methodology, but the human stories about how it all works. They want to know how to initiate an inquiry group, how many people to include, how long the inquiry should go on for, how to locate an inquiry within an organization. In particular, they want to know about the personal qualities this kind of inquiry will demand, the attitudes and skills they will be required to manifest. Maybe the most frequent question people ask is about power and influence: If the inquiry is to be truly co-operative, does this mean that as initiator I cannot be influential? The six papers in this issue address these concerns by providing accounts of how the authors—all of whom recently initiated and participated in co-operative inquiry projects—established and worked with inquiry groups.
Those who fail to study history are doomed to repeat it. We’ve all heard this adage and many among us take to heart the wisdom of looking backward as a vital practice for understanding the future. We must understand how complexity arises from simplicity if we are to build resilience into the fabric of our world. Resilience itself is a form of complexity and cannot emerge through intended design without knowledge of the fundamentals. Similarly, we must be mindful of the systems at play in shaping how human communities arose and which historic problems our biological evolution solved in order to keep us robust as a viable species selected for survival. This is how we will know which physical and cultural environments are best suited to sustaining our existence in this rapidly changing world. Deep History is the study of root causes and primary origins. It is the unravelling of layers throughout time that reveal vital transitions in structure and flow. And it is the perspective of striving for holistic integration of knowledge.
Welcome to the open-access edition of Debates in the Digital Humanities, which brings together leading figures in the field to explore its theories, methods, and practices and to clarify its multiple possibilities and tensions. Encompassing new technologies, research methods, and opportunities for collaborative scholarship and open-source peer review, as well as innovative ways of sharing knowledge and teaching, the digital humanities promises to transform the liberal arts—and perhaps the university itself. Indeed, at a time when many academic institutions are facing austerity budgets, digital humanities programs have been able to hire new faculty, establish new centers and initiatives, and attract multimillion-dollar grants. Clearly the digital humanities has reached a significant moment in its brief history. But what sort of moment is it? Debates in the Digital Humanities brings together leading figures in the field to explore its theories, methods, and practices and to clarify its multiple possibilities and tensions. From defining what a digital humanist is and determining whether the field has (or needs) theoretical grounding, to discussions of coding as scholarship and trends in data-driven research, this cutting-edge volume delineates the current state of the digital humanities and envisions potential futures and challenges. At the same time, several essays aim pointed critiques at the field for its lack of attention to race, gender, class, and sexuality; the inadequate level of diversity among its practitioners; its absence of political commitment; and its preference for research over teaching.
As colleges and universities become more entrepreneurial in a post-industrial economy, they focus on knowledge less as a public good than as a commodity to be capitalized on in profit-oriented activities. In Academic Capitalism and the New Economy, higher education scholars Sheila Slaughter and Gary Rhoades detail the aggressive engagement of higher education institutions in the knowledge-based economy and analyze the efforts of colleges and universities to develop, market, and sell research products, educational services, and consumer goods in the private marketplace. Slaughter and Rhoades track changes in policy and practice, revealing new social networks and circuits of knowledge creation and dissemination, as well as new organizational structures and expanded managerial capacity to link higher education institutions and markets. They depict an ascendant academic capitalist knowledge/learning regime expressed in faculty work, departmental activity, and administrative behavior. Clarifying the regime’s internal contradictions, they note the public subsidies embedded in new revenue streams and the shift in emphasis from serving student customers to leveraging resources from them. Defining the terms of academic capitalism in the new economy, this groundbreaking study offers essential insights into the trajectory of higher education.
What is most fascinating about Bourdieu’s analysis is that it reveals that the higher one’s position in the field of academic power, the greater the conformity required. The type of training required of doctors and jurists appears to be a type of brainwashing, where the “best practices”, as taught, are to be accepted without question. This calls into question the notion of academic freedom and integrity, and causes one to wonder whether authoritative figures can really be trusted, given that they are embroiled in the game of politics. The fact that the function of the training of the “right wing of the parliament of knowledge” (Kant, quoted in Bourdieu) is to produce “agents able to put into practice without questioning or doubting” is also telling of the arrogance often encountered by patients in the offices of clinicians, who dispense medical and non-medical advice as if it were indisputable law.