Many thinkers have argued that studying philosophy is learning how to die. If that’s true, then we have entered humanity’s most philosophical age.
"...The biggest problems the Anthropocene poses are precisely those that have always been at the root of humanistic and philosophical questioning: “What does it mean to be human?” and “What does it mean to live?” In the epoch of the Anthropocene, the question of individual mortality — “What does my life mean in the face of death?” — is universalized and framed in scales that boggle the imagination. What does human existence mean against 100,000 years of climate change? What does one life mean in the face of species death or the collapse of global civilization? How do we make meaningful choices in the shadow of our inevitable end? These questions have no logical or empirical answers. They are philosophical problems par excellence. Many thinkers, including Cicero, Montaigne, Karl Jaspers, and The Stone’s own Simon Critchley, have argued that studying philosophy is learning how to die. If that’s true, then we have entered humanity’s most philosophical age — for this is precisely the problem of the Anthropocene. The rub is that now we have to learn how to die not as individuals, but as a civilization..."
Scientists have derived a series of mathematical formulas that describe how cities' properties vary in relation to their population size, and then posits a novel unified, quantitative framework for understanding how cities function and grow.
"It's an entirely new kind of complex system that we humans have created," he says. "We have intuitively invented the best way to create vast social networks embedded in space and time, and keep them growing and evolving without having to stop. When that is possible, a social species can sustain ways of being incredibly inventive and productive."
A model describing the brain as a system close to a phase transition can capture the global dynamics of brain activity observed in fMRI experiments.
Critical systems can be defined as systems that are close to a critical point, generally identified as the boundary of an order-disorder phase transition. Many complex systems far from equilibrium and composed of a large number of interacting elements have been successfully modeled as critical: notable examples range from gene-interaction networks to financial markets. At criticality, these systems can avoid being trapped in one of two extreme cases: a disordered state (when interactions are too weak and the system is dominated by noise) or a globally ordered state in which all elements are locked (when interactions are too strong and the system is completely static). Neither state supports the dualism essential for a complex system like the brain to function: it must maintain some order to ensure coherent functioning (i.e., generate a reproducible behavior in response to a certain stimulus) while allowing for a certain degree of disorder to enable flexibility (i.e., adapt to varying external conditions). Such dualism is instead possible at criticality.
Dynamical systems that maximize their future possibilities behave in surprisingly “intelligent” ways.
The second law of thermodynamics—the one that says entropy can only increase—dictates that a complex system always evolves toward greater disorderliness in the way internal components arrange themselves. In Physical Review Letters, two researchers explore a mathematical extension of this principle that focuses not on the arrangements that the system can reach now, but on those that will become accessible in the future. They argue that simple mechanical systems that are postulated to follow this rule show features of “intelligence,” hinting at a connection between this most-human attribute and fundamental physical laws.
Bottom-up processes in areas such as transportation can create cities that actually work for residents.
The autocatalytic city contains an intelligence, a kind of ingenuity that can never be captured by a top-down system of control. So it is almost poetic that the complexity of the city finds an analogue and an ally in the nonhierarchical complexity of the Internet. In much the same way that the autocatalytic city makes maximum use of physical materials and space, it is also co-opting technology into its fabric.
If you've ever wondered whether mammalian evolution has a speed limit, here's a number for you: 24 million generations.
That’s how many generations a new study estimates it would take to go from mouse- to elephant-sized while operating on land at the maximum velocity of change. The figure underscores just how special a trait sheer bigness can be.
“Big animals represent the accumulation of evolutionary change, and change takes time,”
Science 1 February 2013: Vol. 339 no. 6119 pp. 574-576 DOI: 10.1126/science.1225883
The capacity for groups to exhibit collective intelligence is an often-cited advantage of group living. Previous studies have shown that social organisms frequently benefit from pooling imperfect individual estimates. However, in principle, collective intelligence may also emerge from interactions between individuals, rather than from the enhancement of personal estimates. Here, we reveal that this emergent problem solving is the predominant mechanism by which a mobile animal group responds to complex environmental gradients. Robust collective sensing arises at the group level from individuals modulating their speed in response to local, scalar, measurements of light and through social interaction with others. This distributed sensing requires only rudimentary cognition and thus could be widespread across biological taxa, in addition to being appropriate and cost-effective for robotic agents.
We used to know how to know. Get some experts, maybe a methodology, add some criteria and credentials, publish the results, and you get knowledge we can all ...
An interesting talk on how the architecture of knowledge was influenced along 2500 years by the media of paper, more than we could dear to imagine, and how the hyper linked structure of internet has transformed all that. Skulls don't scale, networks do, knowledge does.
"We used to know how to know. Get some experts, maybe a methodology, add some criteria and credentials, publish the results, and you get knowledge we can all rely on. But as knowledge is absorbed by our new digital medium, it's becoming clear that the fundamentals of knowledge are not properties of knowledge but of its old paper medium. Skulls don't scale. But the Net does. Now networked knowledge is taking on the properties of its new medium: never being settled, including disagreement within itself, and becoming not a set of stopping points but a web of temptations. Networked knowledge, for all its strengths, has its own set of problems. But, in knowledge's new nature there is perhaps a hint about why the Net has such surprising transformative power.
Darkly Digital Over the past few years as we’ve watched the digital revolution help bring about political and social revolutions around the world, it has seemed inevitable that the Internet would set people free...
Lecture about the rise of digital fabrication and parametric design, looking at their implications for creative practices. Specifically, Open Source design (Makerbot and Thingiverse), generative systems and data sculpture.
I have a brain cancer. I converted my digital medical records into open, accessible formats, turning them into a very personal form of Open Data. Artists, scientists, doctors, designers, hackers are all invited to send me their cure.
the rise of human technology, watch the TEDxtalk on the site
It is futile to ask whether people are naturally cooperative or selfish. They can be either, depending on the circumstances. Dr. Helbing cites "tragedies of the commons" where open access to a common-pool resource such as a fishery tends to result in overfishing that harms everybody—a sort of extended real-world version of the prisoner's dilemma.
In an increasingly interconnected world, scientists are seeking safeguards against catastrophic cascades of failure like stock market crashes and widespread blackouts.
Three years ago, Stanley and his colleagues discovered the mathematics behind what he calls “the extreme fragility of interdependency.” In a system of interconnected networks like the economy, city infrastructure or the human body, their model indicates that a small outage in one network can cascade through the entire system, touching off a sudden, catastrophic failure.
Onstage at TED2013, Sugata Mitra makes his bold TED Prize wish: Help me design the School in the Cloud, a learning lab in India, where children can explore and learn from each other -- using resources and mentoring from the cloud.
a brilliant thought in the future of education, Sugata Mitra won TED prize this month
As systems grow increasingly complex, it becomes impossible to identify or test for every possible cause of failure, writes Guest Columnist Irving Wladawsky-Berger.
There is a continuing struggle between complexity and robustness in both evolution and human design. A kind of survival imperative, whether in biology or engineering, requires that simple, fragile systems become more robust. But the mechanisms to increase robustness will in turn make the system considerably more complex. Furthermore, that additional complexity brings its own unanticipated failure modes, which are corrected over time with additional robust mechanisms, which then further add to the complexity of the system, and so on. This balancing act between complexity and robustness is never done.
The classic approaches to safety assumed that accidents are caused by component failures or by human error. Introducing fault tolerance techniques and planning for their failure will help prevent accidents, thus making components very reliable. Similarly rewarding safe human behavior and punishing unsafe behavior will eliminate or significantly reduce accidents.
These assumptions no longer apply, especially for complex, sociotechnical systems–that is, systems that combine powerful digital technologies with the people and organizations that use and support them.
Partisan lines that once fell along regional borders can increasingly be found at the county level. What does that mean for the future of the United States?
The voting data suggest that people don't make cities liberal -- cities make people liberal.
The gap is so stark that some of America's bluest cities are located in its reddest states.
Electoral cartograms by University of Michigan physics professor Mark Newman show the power of Democratic counties based on population density. Spreading each vote out, his illustrations portray the hidden truth of the conventional electoral map, and why the much smaller number of dedicated blue counties is outmatching the more geographically numerous red counties.
After this year's election, roughly half of the 50 states allow the practice of one, more, or all of the following: same-sex marriage, marijuana use or assisted suicide.
Meanwhile, all of the states that voted against Obamacare also ban both same-sex marriage and marijuana use.
http://www.ted.com Christien Meindertsma, author of "Pig 05049" looks at the astonishing afterlife of the ordinary pig, parts of which make their way into at least 187 non-pork products, from bullets to artificial hearts....
TED Talks Why do transnational extremist organizations succeed where democratic movements have a harder time taking hold?
Maajid Nawaz, a former Islamist extremist, and today a promoter of decomacracy in Pakistan, asks important, critical questions on global political processes and brings an insider view into the fight among extremism of all types and democratic activism and culture. Important.
a brilliant glimpse into the growing non-linearity of cause-effect in complex and overly connected systems.
a module from Boston University, School of Public Health, on causal inference and webs of causation; Prof WW LaMorte.
"Since a determination that a relationship is causal is a judgment, there is often disagreement, particularly since causality often implies some degree of responsibility for the outcome, and this often has legal and financial consequences. Many would agree that incomplete evidence or a lack of agreement about causality, should not always prevent appropriate actions to protect the public's health. Nevertheless, the question of whether a relationship is causal sometimes has important consequences for a vast number of people, as we will see in this module..
Distinguish between association and a causal relationship.Describe and apply Hill's criteria and for a judgment of causality.Describe the sufficient-component cause model.Discuss in general the differences in the weight of evidence needed for determining causality versus taking public health action."