operationalizing complexity
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operationalizing complexity
complexity and the day-to-day operations of firms
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Using Chaos Theory to Predict and Prevent Catastrophic 'Dragon King' Events

Using Chaos Theory to Predict and Prevent Catastrophic 'Dragon King' Events | operationalizing complexity | Scoop.it

Stop a stock trade and avoid a catastrophic global financial crash. Seal a microscopic crack and prevent a rocket explosion. Push a button to avert a citywide blackout.

Though such situations are mostly fantasies, a new analysis suggests that certain types of extreme events occurring in complex systems – known as dragon king events – can be predicted and prevented.


Via Claudia Mihai, Complexity Digest
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Ali Anani's curator insight, November 9, 2013 8:54 AM

Can we control  the uncontrollable? 

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Connection, Connection, Connection…

There are approximately 86 billion neurons in the human brain. Over the past decades, we have made enormous progress in understanding their molecular, genetic, and structural makeup as well as their function. However, the real power of the central nervous system lies in the smooth coordination of large numbers of neurons. Neurons are thus organized on many different scales, from small microcircuits and assemblies all the way to regional brain networks. To interact effectively on all these levels, neurons, nuclei, cortical columns, and larger areas need to be connected. The study of neuronal connectivity has expanded rapidly in past years. Large research groups have recently joined forces and formed consortia to tackle the difficult problems of how to experimentally investigate connections in the brain and how to analyze and make sense of the enormous amount of data that arises in the process.
This year's neuroscience special issue is devoted to general and also several more specific aspects of research on connectivity in the brain. We invited researchers to review the most recent progress in their fields and to provide us with an outlook on what the future may hold in store.

 

Connection, Connection, Connection…
Peter Stern

Science 1 November 2013:
Vol. 342 no. 6158 p. 577
http://dx.doi.org/10.1126/science.342.6158.577


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Risk aversion as an evolutionary adaptation

Risk aversion is a common behavior universal to humans and animals alike. Economists have traditionally defined risk preferences by the curvature of the utility function. Psychologists and behavioral economists also make use of concepts such as loss aversion and probability weighting to model risk aversion. Neurophysiological evidence suggests that loss aversion has its origins in relatively ancient neural circuitries (e.g., ventral striatum). Could there thus be an evolutionary origin to risk avoidance? We study this question by evolving strategies that adapt to play the equivalent mean payoff gamble. We hypothesize that risk aversion in the equivalent mean payoff gamble is beneficial as an adaptation to living in small groups, and find that a preference for risk averse strategies only evolves in small populations of less than 1,000 individuals, while agents exhibit no such strategy preference in larger populations. Further, we discover that risk aversion can also evolve in larger populations, but only when the population is segmented into small groups of around 150 individuals. Finally, we observe that risk aversion only evolves when the gamble is a rare event that has a large impact on the individual's fitness. These findings align with earlier reports that humans lived in small groups for a large portion of their evolutionary history. As such, we suggest that rare, high-risk, high-payoff events such as mating and mate competition could have driven the evolution of risk averse behavior in humans living in small groups.

 

Risk aversion as an evolutionary adaptation
Arend Hintze, Randal S. Olson, Christoph Adami, Ralph Hertwig

http://arxiv.org/abs/1310.6338


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Complexity Digest's curator insight, October 25, 2013 1:14 PM

It is interesting that the same number of 150 individuals was proposed in the context of the evolution of primate brains depending on group size, see http://en.wikipedia.org/wiki/Dunbar's_number

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The Network City

The Network City | operationalizing complexity | Scoop.it

“Only connect,” the writer E. M. Forster said famously — and modern scientists working with network structures are learning how right he was. Forster was talking about how to tell a good story, but it turns out that the same principles for creating richly interconnected structures do apply to making good cities, or other good designs. And what’s all the more interesting (and important) is how bad we’ve gotten at this in recent years — and why that came to pass. Jane Jacobs, the great urbanist and economist, put these ideas to intelligent use in her observation of what made cities such evident crucibles of economic productivity. It was proximities, she said, and networks of proximity, that allowed people to exchange knowledge and creative activities.

 

The Network City
Michael Mehaffy, Nikos Salingaros

http://www.biourbanism.org/network-city/


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SoulFireMage's curator insight, October 28, 2013 9:16 AM

It's spooky how what happens in the brain, in small groups and in other systems appears so self similar. Makes me wonder if, in amongst the deep similarities and simple rules, there isn't some way to predict and even shape more.

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Constructed Complexities

Complexity theory and social constructionism are two important meta-theories that have evolved from very different worldviews and knowledge bases. Yet, there are some important similarities between the core arguments of the two meta-theories and these similarities are largely neglected in methodological debates. In essence, both meta-theories reject reductionist, time, space and relationship-free analyses of positivist or Newtonian social science.

While social constructionism reveals existence of multiple realities and viewpoints, history and context dependence of reality and the role of social embeddedness; complexity theory studies heterogeneous populations and the role of stochasticity, path-dependence of processes, the role of interactions and interdependencies and properties of social networks.

This project aims to initiate an international network of scholars working together to identify conflicts or differences as well as links and similarities between complexity theory and social constructionism. The network will also aim to develop a lingua franca through which some stability could be imposed on the terms in which social scientists debate these matters, so that scholars from different disciplines, in particular the early career researchers, could find their way around over crowded terminology.


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We make our technologies and then they make us

We develop an idea, apply it, and the idea then changes us. This is generic to the human condition, but we only recognise its significance during periods of very rapid change when we have amassed enough knowledge to appreciate this insight. Of course, over a lifetime, many who reflect on change recognise this as being central to their experience, but it is only in periods of very rapid transition that we appreciate this insight over the short term. This is best encapsulated in Winston Churchill’s (1943) statement about the rebuilding of Parliament when he said: “We shape our buildings, and afterwards our buildings shape us.” This quote is generic to much of what we invent and build, and it is certainly true of the technologies that underpin modern society.

 

We make our technologies and then they make us

Michael Batty

Environment and Planning B 

2013 volume 40(5) pages 761 – 762

http://dx.doi.org/10.1068/b4005ed


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Can science stop government shutdowns?

Government is not traditionally the domain of natural science. But a growing body of researchers think it should be. In their view, rather than being one damned thing after another, human history is just as much in thrall to natural laws as anthills or oceans. If so, the mathematics developed to understand such systems might also help explain how human societies work – and why they sometimes don't.


For example, some complexity theorists say that many civic institutions, built for a minimally networked world, are unfit for purpose. Our more populous and connected societies can't be governed via traditional hierarchies: these need to be displaced by more decentralised networks. In this regard, industry may be faster on the uptake, since many companies are already making that transition.


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Scarcity: Why Having Too Little Means So Much (by Sendhil Mullainathan and Eldar Shafir)

Scarcity: Why Having Too Little Means So Much

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A surprising and intriguing examination of how scarcity—and our flawed responses to it—shapes our lives, our society, and our culture

Why do successful people get things done at the last minute? Why does poverty persist? Why do organizations get stuck firefighting? Why do the lonely find it hard to make friends? These questions seem unconnected, yet Sendhil Mullainathan and Eldar Shafir show that they are all are examples of a mind-set produced by scarcity.

Drawing on cutting-edge research from behavioral science and economics, Mullainathan and Shafir show that scarcity creates a similar psychology for everyone struggling to manage with less than they need. Busy people fail to manage their time efficiently for the same reasons the poor and those maxed out on credit cards fail to manage their money. The dynamics of scarcity reveal why dieters find it hard to resist temptation, why students and busy executives mismanage their time, and why sugarcane farmers are smarter after harvest than before. Once we start thinking in terms of scarcity and the strategies it imposes, the problems of modern life come into sharper focus.

Mullainathan and Shafir discuss how scarcity affects our daily lives, recounting anecdotes of their own foibles and making surprising connections that bring this research alive. Their book provides a new way of understanding why the poor stay poor and the busy stay busy, and it reveals not only how scarcity leads us astray but also how individuals and organizations can better manage scarcity for greater satisfaction and success.

 

 


Via Complexity Digest
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Good example of how reframing can change perpectives

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Dexter Choong's curator insight, January 21, 2014 2:56 PM

This article focuses mainly on the scarcity of resources in the economy.

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War, space, and the evolution of Old World complex societies

How did human societies evolve from small groups, integrated by face-to-face cooperation, to huge anonymous societies of today? Why is there so much variation in the ability of different human populations to construct viable states? We developed a model that uses cultural evolution mechanisms to predict where and when the largest-scale complex societies should have arisen in human history. The model was simulated within a realistic landscape of the Afroeurasian landmass, and its predictions were tested against real data. Overall, the model did an excellent job predicting empirical patterns. Our results suggest a possible explanation as to why a long history of statehood is positively correlated with political stability, institutional quality, and income per capita.

 

War, space, and the evolution of Old World complex societies
Peter Turchin, Thomas E. Currie, Edward A. L. Turner, and Sergey Gavrilets

http://dx.doi.org/10.1073/pnas.1308825110
PNAS September 23, 2013


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Yannis Corovesis's curator insight, October 4, 2013 3:01 PM

Peter Turchin is the son of Valentin Fiodorovitch

Thomas Owens's curator insight, January 25, 2014 5:47 AM

I wish I had more time to study this so I'm going to mark it.

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Management Is (Still) Not Leadership - John Kotter - Harvard ...

Management Is (Still) Not Leadership - John Kotter - Harvard ... | operationalizing complexity | Scoop.it
Business bloggers at Harvard Business Review discuss a variety of business topics including managing people, innovation, leadership, and more.
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Recording and replaying human touch: The next user-interface revolution?

Recording and replaying human touch: The next user-interface revolution? | operationalizing complexity | Scoop.it
Researchers at the University of California, San Diego report a breakthrough in technology that could pave the way for digital systems to record, store, edit and replay information in a dimension that goes beyond what we can see or hear: touch.

 

“Touch was largely bypassed by the digital revolution, except for touch-screen displays, because it seemed too difficult to replicate what analog haptic devices – or human touch – can produce,” said Deli Wang, a professor of Electrical and Computer Engineering (ECE) in UC San Diego’s Jacobs School of Engineering. “But think about it: being able to reproduce the sense of touch in connection with audio and visual information could create a new communications revolution.”

 

In addition to uses in health and medicine, the communication of touch signals could have far-reaching implications for education, social networking, e-commerce, robotics, gaming, and military applications, among others. The sensors and sensor arrays reported in the paper are also fully transparent (see optical image of transparent ZnO TFT sensor array at right), which makes it particularly interesting for touch-screen applications in mobile devices.

 

Digital replay, editing and manipulation of recorded touch events were demonstrated at various spatial and temporal resolutions. The researchers used an 8 × 8 active-matrix ZnO pressure sensor array, a data acquisition and processing system (sensor array reader circuit, computer, and actuator array driver circuit), and a semi-rigid 8 × 8 polymer diaphragm actuator array.

 

The ability to digitize the touch contact enables direct remote transfer of touch information, long-term memory storage, and replay at a later time. “In addition, with the ability to reproduce and change the feeling of touch with both temporal and spatial resolutions make it possible to produce synthesized touch,” said UC San Diego’s Wang. “It could create experiences that do not exist in nature, as we have done with computer-generated imagery and synthesized music.”

 

While Wang and his colleagues recognize that the touch revolution is still in its infancy, and human trials will probably be needed to calibrate the optimal actuator response needed to conform to the human perception of pressure strength, which depends on actuator displacement (amplitude), frequency, and how much time the actuator spends in its on- or off-state (duty cycle). Yet, say the researchers, there is every reason to believe that their experimental system, by adding an extra dimension to existing digital technologies, could extend the capabilities of modern information exchange.


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The Surprising Origins of Life’s Complexity

The Surprising Origins of Life’s Complexity | operationalizing complexity | Scoop.it

Conventional wisdom holds that complex structures evolve from simpler ones, step-by-step, through a gradual evolutionary process, with Darwinian selection favoring intermediate forms along the way.
But recently some scholars have proposed that complexity can arise by other means—as a side effect, for instance—even without natural selection to promote it.
Studies suggest that random mutations that individually have no effect on an organism can fuel the emergence of complexity in a process known as constructive neutral evolution.

 

https://www.simonsfoundation.org/quanta/20130716-the-surprising-origins-of-lifes-complexity/


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How Poverty Taxes the Brain

How Poverty Taxes the Brain | operationalizing complexity | Scoop.it

Human mental bandwidth is finite. You’ve probably experienced this before (though maybe not in those terms): When you’re lost in concentration trying to solve a problem like a broken computer, you’re more likely to neglect other tasks, things like remembering to take the dog for a walk, or picking your kid up from school. This is why people who use cell phones behind the wheel actually perform worse as drivers. It’s why air traffic controllers focused on averting a mid-air collision are less likely to pay attention to other planes in the sky.


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Neuroelectronics: Smart connections - Computer chips inspired by human neurons can do more with less power.

Neuroelectronics: Smart connections - Computer chips inspired by human neurons can do more with less power. | operationalizing complexity | Scoop.it

Kwabena Boahen got his first computer in 1982, when he was a teenager living in Accra. “It was a really cool device,” he recalls. He just had to connect up a cassette player for storage and a television set for a monitor, and he could start writing programs.

 

But Boahen wasn't so impressed when he found out how the guts of his computer worked. “I learned how the central processing unit is constantly shuffling data back and forth. And I thought to myself, 'Man! It really has to work like crazy!'” He instinctively felt that computers needed a little more 'Africa' in their design, “something more distributed, more fluid and less rigid”.


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The Man Who Would Teach Machines to Think

The Man Who Would Teach Machines to Think | operationalizing complexity | Scoop.it
Douglas Hofstadter, the Pulitzer Prize–winning author of Gödel, Escher, Bach, thinks we've lost sight of what artificial intelligence really means. His stubborn quest to replicate the human mind.

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Things

Assuming one could momentarily step aside from the current pandemonium generated by big data, social networks, and smart phones; there is an obvious question that comes to one's mind: what will be the next wave of innovations? Of course, the only safe prediction, about forecasting the future, is that it is very easy to get it wrong. Who would have thought that, 20 years after the flop of the Newton (http://www.youtube.com/watch?v=MiNKMmyRiw4), we would have been queuing to buy an iPad? Sometimes, you just have to wait for the right Apple to fall on your head. Still, there are a couple of low-hanging fruits that seem to be sufficiently ripe to be worth monitoring.

Some pundits have been talking about “the internet of things” for some years now (...)

 

Things
Luciano Floridi

Philosophy & Technology
http://dx.doi.org/10.1007/s13347-013-0139-2


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“Wrong, but Useful”: Negotiating Uncertainty in Infectious Disease Modelling

“Wrong, but Useful”: Negotiating Uncertainty in Infectious Disease Modelling | operationalizing complexity | Scoop.it

For infectious disease dynamical models to inform policy for containment of infectious diseases the models must be able to predict; however, it is well recognised that such prediction will never be perfect. Nevertheless, the consensus is that although models are uncertain, some may yet inform effective action. This assumes that the quality of a model can be ascertained in order to evaluate sufficiently model uncertainties, and to decide whether or not, or in what ways or under what conditions, the model should be ‘used’. We examined uncertainty in modelling, utilising a range of data: interviews with scientists, policy-makers and advisors, and analysis of policy documents, scientific publications and reports of major inquiries into key livestock epidemics. We show that the discourse of uncertainty in infectious disease models is multi-layered, flexible, contingent, embedded in context and plays a critical role in negotiating model credibility. We argue that usability and stability of a model is an outcome of the negotiation that occurs within the networks and discourses surrounding it. This negotiation employs a range of discursive devices that renders uncertainty in infectious disease modelling a plastic quality that is amenable to ‘interpretive flexibility’. The utility of models in the face of uncertainty is a function of this flexibility, the negotiation this allows, and the contexts in which model outputs are framed and interpreted in the decision making process. We contend that rather than being based predominantly on beliefs about quality, the usefulness and authority of a model may at times be primarily based on its functional status within the broad social and political environment in which it acts.

 

Paper: http://www.plosone.org/article/info:doi/10.1371/journal.pone.0076277

 


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The Nobel Prize in Economic Sciences 2013

There is no way to predict the price of stocks and bonds over the next few days or weeks. But it is quite possible to foresee the broad course of these prices over longer periods, such as the next three to five years. These findings, which might seem both surprising and contradictory, were made and analyzed by this year’s Laureates, Eugene Fama, Lars Peter Hansen and Robert Shiller.


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What Are the New Implications of Chaos for Unpredictability?

From the beginning of chaos research until today, the unpredictability of chaos has been a central theme. It is widely believed and claimed by philosophers, mathematicians and physicists alike that chaos has a new implication for unpredictability, meaning that chaotic systems are unpredictable in a way that other deterministic systems are not. Hence one might expect that the question 'What are the new implications of chaos for unpredictability?' has already been answered in a satisfactory way. However, this is not the case. I will critically evaluate the existing answers and argue that they do not fit the bill. Then I will approach this question by showing that chaos can be defined via mixing, which has not been explicitly argued for. Based on this insight, I will propose that the sought-after new implication of chaos for unpredictability is the following: for predicting any event all sufficiently past events are approximately probabilistically irrelevant.

 

What Are the New Implications of Chaos for Unpredictability?
Charlotte Werndl

http://arxiv.org/abs/1310.1576


Via Complexity Digest
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to quote the author, "

a new implication of
chaos for unpredictability is that for predicting any event at any level of precision, all
suciently past events are approximately probabilistically irrelevant"

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Modelling Complexity for Policy: Opportunities and Challenges

This chapter reviews the purpose and use of models from the field of complex systems and, in particular, the implications of trying to use models to understand or make decisions within complex situations, such as policy makers usually face. A discussion of the different dimensions one can formalise situations, the different purposes for models and the different kinds of relationship they can have with the policy making process, is followed by an examination of the compromises forced by the complexity of the target issues. Several modelling approaches from complexity science are briefly described, with notes as to their abilities and limitations. These approaches include system dynamics, network theory, information theory, cellular automata, and agent-based modelling. Some examples of policy models are presented and discussed in the context of the previous analysis. Finally we conclude by outlining some of the major pitfalls facing those wishing to use such models for policy evaluation.

 

Modelling Complexity for Policy: Opportunities and Challenges
Bruce Edmonds, Carlos Gershenson

http://arxiv.org/abs/1310.2290


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Social: Why Our Brains Are Wired to Connect (by Matthew D. Lieberman)

Social: Why Our Brains Are Wired to Connect

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In Social, renowned psychologist Matthew Lieberman explores groundbreaking research in social neuroscience revealing that our need to connect with other people is even more fundamental, more basic, than our need for food or shelter.  Because of this, our brain uses its spare time to learn about the social world – other people and our relation to them. It is believed that we must commit 10,000 hours to master a skill.  According to Lieberman, each of us has spent 10,000 hours learning to make sense of people and groups by the time we are ten.
 
Social argues that our need to reach out to and connect with others is a primary driver behind our behavior.  We believe that pain and pleasure alone guide our actions.  Yet, new research using fMRI – including a great deal of original research conducted by Lieberman and his UCLA lab -- shows that our brains react to social pain and pleasure in much the same way as they do to physical pain and pleasure.  Fortunately, the brain has evolved sophisticated mechanisms for securing our place in the social world.  We have a unique ability to read other people’s minds, to figure out their hopes, fears, and motivations, allowing us to effectively coordinate our lives with one another.  And our most private sense of who we are is intimately linked to the important people and groups in our lives.  This wiring often leads us to restrain our selfish impulses for the greater good.  These mechanisms lead to behavior that might seem irrational, but is really just the result of our deep social wiring and necessary for our success as a species.
 
Based on the latest cutting edge research, the findings in Social have important real-world implications.  Our schools and businesses, for example, attempt to minimalize social distractions.  But this is exactly the wrong thing to do to encourage engagement and learning, and literally shuts down the social brain, leaving powerful neuro-cognitive resources untapped.  The insights revealed in this pioneering book suggest ways to improve learning in schools, make the workplace more productive, and improve our overall well-being.

 

 


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I'm reluctant to advertise but this has some interesting ideas.

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june holley's curator insight, October 7, 2013 1:09 PM

I'll add more comments after I read it. 

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Towers Watson: complexity coming straight at you

Towers Watson: complexity coming straight at you | operationalizing complexity | Scoop.it

To be a long-term investor requires thematic investing because markets and economies are complex adaptive systems, according to Tim Hodgson, global head of the thinking-ahead group at Towers Watson.

 

Hodgson told delegates at the Towers Watson Ideas Exchange in Sydney that economies and markets are complex and adaptive, their path is not random and the future is not predictive.

 

“We don’t live in a linear world. We must hold truths in our head while we navigate the future. A single market price cannot reflect this,” he says.

 

Towers Watson believes that there are a number of interconnected issues that will converge in the next decades, and which it outlines in its 2013 secular outlook on thematic investing, which will require transformational change.

 

“It is coming straight at you: the asset owner and you have to deal with it whether you like it or not,” he says.

 

Recognition of the interconnectedness of these issues is essential.

Hodgson says traditional investment thinking is drawn heavily from economics, which has separate disciplines. The micro side of economics is well developed and the industry is disciplined in how to optimise a portfolio, value a company or price a derivative, all in isolation. But the macro side, including the emergence of bubbles, is almost completely unknown.


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This Mind-Reading Headset Gives Users The Power of Mind Control

This Mind-Reading Headset Gives Users The Power of Mind Control | operationalizing complexity | Scoop.it

Five years ago, Vietnamese-Australian inventor and Emotiv CEO Tan Le released the Emotiv EPOC neuroheadset, what was billed as the world’s first commercial brain-computer interface. The product, which still sells for $300, proved to be a hit, making it clear that the public craved this new kind of wearable technology.

 

Now, Le and Emotiv are back with an entirely revamped headset that features a full redesign and update of the original EPOC. The Emotiv Insight, they promise, not only bridges the electro-communicational gap between one’s brain and computer, but also allows users to track their brain activity in real-time and even monitor their mental health. The team has set up a Kickstarter campaign ahead of the project’s 2014 release, and the response couldn’t have been more viral. With two weeks left in its Kickstarter run, nearly 3,300 backers have pledged over $1 million in support.

 

The enthusiastic reaction is only surprising if you don’t already know what the Emotiv headsets can do. The new model is a multi-channel device that gives the wearer Jedi-like mind powers, and who doesn’t want to be a Jedi? As Le points out in the Kickstarter video, users can wield the Emotive Insight for very creative ends that to the outside observer might seem like magic.

 

But how does it work? The Insight sports a new five-channel sensor setup--a significant improvement over the EPOC--that picks up electroencephalography (EEG) data. The headset’s individual sensors target key junctions of the cerebral cortex and translates the EEG they detect into meaningful ways, which the project text explains can be used to “optimize” a user’s cognitive performance. By understanding and breaking down brain activity in this manner, the Insight can also generate brainwaves that power the product's multiple applications.

 

Just a handful of these are illustrated in the Kickstarter video: A child outfitted with the new headset is seen conjuring up a three-dimensional design for a toy on the computer screen before him, hands free. Another volunteer holds a modified electric helicopter--synced to the headset--in the palm in his hand and watches with amazement as it rises into the air, spurred only by his mental command. In yet another test case, a handicapped man creates the soundtrack that scores the video just using the power of his thought.

 

Still, these choice examples aside, the exact applications of the system are vague. That’s intentional because, as Le explains, the Insight is a platform that allows you, the user, to develop newer and unexpected uses for the technology. The Emotiv team plans to offer up API and SDK for developers wanting to play around with the technology; doing so, Le says, will “make it possible for anyone to take this innovation and create new applications with the technology.”


Via Dr. Stefan Gruenwald
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randy yerrick's curator insight, September 26, 2013 3:31 PM

Another advancement in connecting the Brain directly. - MJP

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Economics 2.0: The Natural Step towards a Self-Regulating, Participatory Market Society

Despite all our great advances in science, technology and financial innovations, many societies today are struggling with a financial, economic and public spending crisis, over-regulation, and mass unemployment, as well as lack of sustainability and innovation. Can we still rely on conventional economic thinking or do we need a new approach? Is our economic system undergoing a fundamental transformation? Are our theories still doing a good job with just a few exceptions, or do they work only for “good weather” but not for “market storms”? Can we fix existing theories by adapting them a bit, or do we need a fundamentally different approach? These are the kind of questions that will be addressed in this paper. I argue that, as the complexity of socio-economic systems increases, networked decision-making and bottom-up self-regulation will be more and more important features. It will be explained why, besides the “homo economicus” with strictly self-regarding preferences, natural selection has also created a “homo socialis” with other-regarding preferences.(...)

 

Economics 2.0: The Natural Step towards a Self-Regulating, Participatory Market Society
Dirk Helbing

Evolutionary and Institutional Economics Review Vol. 10 (2013) No. 1 p. 3-41

https://www.jstage.jst.go.jp/article/eier/10/1/10_3/_article


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june holley's curator insight, September 18, 2013 6:17 PM

This understanding is key for those of us committed to a more just and inclusive economy.

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Think uncertainty is a bad thing? It’s actually a mark of sound science

Think uncertainty is a bad thing? It’s actually a mark of sound science | operationalizing complexity | Scoop.it

Scientists are challenging the idea that uncertainty in research is a reason for people to worry about the reliability of findings.

 

Researchers use uncertainty to express how confident they are in results, or to describe the boundaries of what is known and unknown, but in everyday language uncertainty is heard as ‘unreliable’.

 

In a new guide, Making Sense of Uncertainty, Sense About Science worked with researchers in climate science, disease modelling, epidemiology, weather forecasting, and natural hazard prediction to explain why we should be relieved when scientists describe the uncertainties in their work. We asked them to tell us why it is that the uncertainty in these areas doesn’t worry them, and to share these insights to help people engage more constructively with debates about uncertainty.


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