NESS is holding a one day policy-oriented conference in London on 28 October, where we will be drawing out practical implications in key areas such as:
Financial marketsCities, transport and infrastructureDecision making
The event is hosting a number of speakers, including:
Sir Charles Bean, Former Deputy Governor, Bank of EnglandDavid Tuckett, Director of the Centre for the Study of Decision-Making Uncertainty Psychoanalysis, University College LondonProfessor Mike Batty, Chairman, Centre for Advanced Spatial Analysis (CASA) at University College LondonPaul Ormerod, Volterra Partners LLP, London
Teotihuacan was the first urban civilization of Mesoamerica and one of the largest of the ancient world. Following a tradition in archaeology to equate social complexity with centralized hierarchy, it is widely believed that the city’s origin and growth was controlled by a lineage of powerful individuals. However, much data is indicative of a government of co-rulers, and artistic traditions expressed an egalitarian ideology. Yet this alternative keeps being marginalized because the problems of collective action make it difficult to conceive how such a coalition could have functioned in principle. We therefore devised a mathematical model of the city’s hypothetical network of representatives as a formal proof of concept that widespread cooperation was realizable in a fully distributed manner. In the model, decisions become self-organized into globally optimal configurations even though local representatives behave and modify their relations in a rational and selfish manner. This self-optimization crucially depends on occasional communal interruptions of normal activity, and it is impeded when sections of the network are too independent. We relate these insights to theories about community-wide rituals at Teotihuacan and the city’s eventual disintegration.
Froese, T., Gershenson, C., and Manzanilla, L. R. (2014). Can government be self-organized? a mathematical model of the collective social organization of ancient teotihuacan, central mexico.PLoS ONE 9 (10) (10): e109966.
It’s been said that we’re living in the golden age of data visualization. And why shouldn’t we be? Every move we make is potential fodder for a bar chart or line graph. Regardless of how you feel about our constant quantification, its been a boon for designers who have made some exceptional infographics—and some not…
“If the facts don’t fit the theory, change the theory,” goes the old adage. But too often it is easier to keep the theory and change the facts – or so German Chancellor Angela Merkel and other pro-austerity European leaders appear to believe. Though facts keep staring them in the face, they continue to deny reality. Austerity has failed. But its defenders are willing to claim victory on the basis of the weakest possible evidence: the economy is no longer collapsing, so austerity must be working! But if that is the benchmark, we could say that jumping off a cliff is the best way to get down from a mountain; after all, the descent has been stopped.
Wendy Aguilar, Guillermo Santamaría Bonfil1, Tom Froese1 and Carlos Gershenson
Universidad Nacional Autonoma de Mexico, Mexico
For millennia people have wondered what makes the living different from the non-living. Beginning in the mid-1980s, artificial life has studied living systems using a synthetic approach: build life in order to understand it better, be it by means of software, hardware, or wetware. This review provides a summary of the advances that led to the development of artificial life, its current research topics, and open problems and opportunities. We classify artificial life research into fourteen themes: origins of life, autonomy, self-organization, adaptation (including evolution, development, and learning), ecology, artificial societies, behavior, computational biology, artificial chemistries, information, living technology, art, and philosophy. Being interdisciplinary, artificial life seems to be losing its boundaries and merging with other fields.
Even the most forward-thinking futurist would find it near-impossible to imagine with any great confidence what the World Wide Web will look like in 2050. Thirty-five years into the future seems like an unfathomably long view when technology is advancing at various exponential rates. Only 25 years ago, the web didn’t exist at all.
That’s the task a group of delegates from various tech companies (plus a token futurist in the form of Book of the Future’s Tom Cheesewright) set themselves to at a roundtable discussion in London this morning. The event was a precursor to the IP Expo Europe next month, at which web creator Sir Tim Berners-Lee will share some of his own thoughts on the matter.
In July, the NESS group met in Rochdale town Hall to discuss the key policy themes arising from the NESS group and its application in the region. A tour of the town was followed with a presentation by Andrzej Nowak on how art has been used to revive a depressed area of Warsaw which is now one of the most desirable districts in the city. A presentation of the NESS report on the findings by Councillor John Blundell, Assistant Portfolio Holder for Regeneration.
At its height, in the 18th century and the boom of the industrial revolution Rochdale was amongst some of the richest places in the world. Now with a population of 200,000 it is now relatively poor in UK terms. The workshop was to understand the policy theme arising from the NESS work and therefore, how NESS could benefit.
Some themes arising from the research include:
Agglomeration: The benefits of denser employment have demonstrated higher productivity in an area, meaning that higher density produces greater wealth.
Employment density and economic resilience: The research has found that in addition to higher density generating greater wealth, it also impacts positively the ability of a local area recover more quickly from economic shocks
Currently Rochdale is performing poorly in both areas and therefore, the workshop raised specific policy questions:
* Should policy be aimed at increasing employment in central Manchester in order to benefit further from the agglomeration effect, bearing in mind the need for improved transport links to enable this?
* Should policy within a borough such as Rochdale be aimed at increasing the employment density of its existing densest area?
If local circumstances can generate local social trends, it follows that global circumstances can generate global trends. Furthermore, modern global circumstances match the conditions used to create artificial evolutionary systems. If it is possible for evolutionary forces to arise in global society, then it is possible that key forces shaping global society are evolutionary in nature. We can experimentally test for the possibility of evolutionary forces in global society by using a multi-agent simulation. This paper presents a simulation programmed to capture the evolutionary prerequisites observed in global society. Trends arising from this simulation are tested against three known trends and three assumed trends arising from global society. The results from this experiment support the hypothesis that a wealth aggregation evolutionary imperative is shaping key trends in global society.
Can the choice of words and tone used by the authors of financial news articles correlate to measurable stock price movements? If so, can the magnitude of price movement be predicted using these same variables? We investigate these questions using the Arizona Financial Text (AZFinText) system, a financial news article prediction system, and pair it with a sentiment analysis tool. Through our analysis, we found that subjective news articles were easier to predict in price direction (59.0% versus 50.0% of chance alone) and using a simple trading engine, subjective articles garnered a 3.30% return. Looking further into the role of author tone in financial news articles, we found that articles with a negative sentiment were easiest to predict in price direction (50.9% versus 50.0% of chance alone) and a 3.04% trading return. Investigating negative sentiment further, we found that our system was able to predict price decreases in articles of a positive sentiment 53.5% of the time, and price increases in articles of a negative sentiment 52.4% of the time. We believe that perhaps this result can be attributable to market traders behaving in a contrarian manner, e.g., see good news, sell; see bad news, buy.
While many countries succeeded in moving people out of poverty, the welfare of a growing number is precarious. An economic system that fails to deliver gains for most of its citizens, and in which a rising share of the population faces increasing insecurity, is, in a fundamental sense, a failed economic system.
Self-organisation occurs in natural phenomena when a spontaneous increase inorder is produced by the interactions of elements of a complex system. Thermodynamically,this increase must be offset by production of entropy which, broadly speaking, can beunderstood as a decrease in order. Ideally, self-organisation can be used to guide the systemtowards a desired regime or state, while “exporting” the entropy to the system’s exterior. Thus, Guided Self-Organisation (GSO) attempts to harness the order-inducing potentialof self-organisation for specific purposes. Not surprisingly, general methods developed tostudy entropy can also be applied to guided self-organisation. This special issue covers a broad diversity of GSO approaches which can be classified in three categories: informationtheory, intelligent agents, and collective behavior. The proposals make another step towardsa unifying theory of GSO which promises to impact numerous research fields.
Entropy Methods in Guided Self-Organisation Mikhail Prokopenko and Carlos Gershenson
The emerging field of computational social science (CSS) is devoted to the pursuit of interdisciplinary social science research from an information processing perspective, through the medium of advanced computing and information technologies.
This reader-friendly textbook/reference is the first work of its kind to provide a comprehensive and unified Introduction to Computational Social Science. Four distinct methodological approaches are examined in particular detail, namely automated social information extraction, social network analysis, social complexity theory, and social simulation modeling. The coverage of each of these approaches is supported by a discussion of the historical context and motivations, as well as by a list of recommended texts for further reading.
Imagine that someone told you that three of the biggest stories of the past few years — the financial crisis, exploding economic inequality, and the National Security Agency spy scandal — weren’t actually different stories at all. Different in detail, yes, but essentially identical in their deeper cause. The cause, they go on to say, wasn’t greed or fear or the age of terrorism or anything else linked to human fallibility, but technology — specifically, computation and its networked manifestation, the Internet. Sound crazy?
The International System is a self-organized system and shows emergent behavior. During the timeframe (1495 - 1945), a finite-time singularity and four accompanying accelerating log-periodic cycles shaped the dynamics of the International System. The accelerated growth of the connectivity of the regulatory network of the International System, in combination with its anarchistic structure, produce and shape the war dynamics of the system. Accelerated growth of the connectivity of the International system is fed by population growth and the need for social systems to fulfill basic requirements. The finite-time singularity and accompanying log-periodic oscillations were instrumental in the periodic reorganization of the regulatory network of the International System, and contributed to a long-term process of social expansion and integration in Europa. The singularity dynamic produced a series of organizational innovations. At the critical time of the singularity (1939) the connectivity of the system reached a critical threshold, resulting in a critical transition. This critical transition caused a fundamental reorganization of the International System: Europe transformed from an anarchistic system to cooperative security community. This critical transition also marks the actual globalization of the International System. During the life span of cycles, the war dynamics show chaotic characteristics. Various early-warning signals can be identified, and can probably be used in the current International System. These findings have implications for the social sciences and historical research.
Topological properties of networks are widely applied to study the link-prediction problem recently. Common Neighbors, for example, is a natural yet efficient framework. Many variants of Common Neighbors have been thus proposed to further boost the discriminative resolution of candidate links. In this paper, we reexamine the role of network topology in predicting missing links from the perspective of information theory, and present a practical approach based on the mutual information of network structures. It not only can improve the prediction accuracy substantially, but also experiences reasonable computing complexity.
Evolutionary adaptation can be described as a biased, stochastic walk of a population of sequences in a high dimensional sequence space. The population explores a fitness landscape. The mutation-selection process biases the population towards regions of higher fitness. In this paper we estimate the time scale that is needed for evolutionary innovation. Our key parameter is the length of the genetic sequence that needs to be adapted. We show that a variety of evolutionary processes take exponential time in sequence length. We propose a specific process, which we call ‘regeneration processes’, and show that it allows evolution to work on polynomial time scales. In this view, evolution can solve a problem efficiently if it has solved a similar problem already.
The stability analysis of socioeconomic systems has been centred on answering whether small perturbations when a system is in a given quantitative state will push the system permanently to a different quantitative state. However, typically the quantitative state of socioeconomic systems is subject to constant change. Therefore, a key stability question that has been under-investigated is how strongly the conditions of a system itself can change before the system moves to a qualitatively different behaviour, i.e. how structurally stable the systems is. Here, we introduce a framework to investigate the structural stability of socioeconomic systems formed by a network of interactions among agents competing for resources. We measure the structural stability of the system as the range of conditions in the distribution and availability of resources compatible with the qualitative behaviour in which all the constituent agents can be self-sustained across time. To illustrate our framework, we study an empirical representation of the global socioeconomic system formed by countries sharing and competing for multinational companies used as proxy for resources. We demonstrate that the structural stability of the system is inversely associated with the level of competition and the level of heterogeneity in the distribution of resources. Importantly, we show that the qualitative behaviour of the observed global socioeconomic system is highly sensitive to changes in the distribution of resources. We believe that this work provides a methodological basis to develop sustainable strategies for socioeconomic systems subject to constantly changing conditions.
How structurally stable are global socioeconomic systems? Serguei Saavedra, Rudolf P. Rohr, Luis J. Gilarranz, Jordi Bascompte