Christian Schwägerl, science and environment writer, and co-founder of The Anthropocene Project; Tony Juniper, writer, campaigner, environmentalist and sustainability adviser We live at a moment of deep change, between one geological epoch and another, between the Holocene and the present - an era we are beginning to call the Anthropocene. It is only recently that we have come to understand that our actions have already altered the planet, that we now shape nature, and that we have the power to create a positive geological record. Alongside current ecological crises are countless examples of new thinking, such as smart cities, cultivated life forms and landscapes with human-induced biodiversity. Popular movements are fighting for their local ecologies, globally-connected pressure groups are forcing political change, and there is a growing recognition that diverse communities have an equal right to a say in this planet’s future. Award-winning science and environment writer Christian Schwägerl visits the RSA to trace our co-evolution on this planet and the growth of ideas about the Anthropocene concept.
So one way of thinking about complexity is adaptive, many body systems. The sun is not an adaptive system; the sun doesn’t really learn. These do; these are learning systems. And we’ve never really successfully had a theory for many body learning systems. So just to make that a little clearer, the brain would be an example. There are many neurons interacting adaptively to form a representation, for example, of a visual scene; in economy, there are many individual agents deciding on the price of a good, and so forth; a political system voting for the next president. All of these systems have individual entities that are heterogeneous and acquire information according to a unique history about the world in which they live. That is not a world that Newton could deal with. There’s a very famous quote where he says something like, I have been able to understand the motion of the planets, but I will never understand the madness of men. What Newton was saying is, I don’t understand complexity.
Collective compassion has meant an overall decrease in global poverty since the 1980s, says civil rights lawyer Gary Haugen. Yet for all the world's aid money, there's a pervasive hidden problem keeping poverty alive. Haugen reveals the dark underlying cause we must recognize and act on now.
Rob Knight is a pioneer in studying human microbes, the community of tiny single-cell organisms living inside our bodies that have a huge — and largely unexplored — role in our health. “The three pounds of microbes that you carry around with you might be more important than every single gene you carry around in your genome,” he says. Find out why.
Carefully considering all well-known worries about privacy, professor Dirk Helbing raises a great concept: The Planetary Nervous System (PNS). Roughly, this idea involves connecting our smartphones worldwide to build a global measurement network and create a flow of information on all kinds of topics.
You may remember neuroscientist Miguel Nicolelis — he built the brain-controlled exoskeleton that allowed a paralyzed man to kick the first ball of the 2014 World Cup. What’s he working on now? Building ways for two minds (rats and monkeys, for now) to send messages brain to brain. Watch to the end for an experiment that, as he says, will go to "the limit of your imagination."
I discuss "simple" dynamical systems on networks and examine how network structure affects dynamics of processes running on top of networks. I'll give an introduction to the idea of social ("complex") contagions, and I'll present a model for multi-stage complex contagions in which fanatics produce greater influence than mere followers. I'll also briefly discuss the use of ideas from topics like persistent homology to examine wavefront propagation versus the appearance of new contagion clusters, and I'll present a model (without network structure) for the adoption of applications on Facebook. The last family of models illustrates how very different time-dependent dynamics can produce quantitatively similar long-time behavior, which poses both very serious challenges and exciting opportunities for the modeling of complex systems.
Renowned public thinker Cass Sunstein defends his groundbreaking nudge theory. When the state seeks to influence our choices in “our best interests” is this liberty-infringing meddling, or simply good government?
So which explanation captures the dynamics that led to the crash? Could an ordinary order in the futures market or a lone market manipulator really cause the crash? The simple answer is that this is the wrong question to ask. From the perspective of the joint report and the enforcement action, the Flash Crash was a fluke, an idiosyncratic event caused by an unexpected glitch in the markets. But it was far from being a fluke. Instead, the Flash Crash reveals that we need a fundamentally different understanding of how modern financial markets work. We believe that it shows us that markets are governed by the same principle as earthquakes and avalanches: self-organized criticality.
Finding the right mate is no cakewalk -- but is it even mathematically likely? In a charming talk, mathematician Hannah Fry shows patterns in how we look for love, and gives her top three tips (verified by math!) for finding that special someone.
While we like to imagine little green men, it’s far more likely that life on other planets will be microbial. Planetary scientist Nathalie Cabrol takes us inside the search for microbes on Mars, a hunt which counterintuitively leads us to the remote lakes of the Andes mountains. This extreme environment — with its thin atmosphere and scorched land — approximates the surface of Mars about 3.5 billion years ago. How microbes adapt to survive here may just show us where to look on Mars — and could
The news of society's growing inequality makes all of us uneasy. But why? Dan Ariely reveals some new, surprising research on what we think is fair, as far as how wealth is distributed over societies ... then shows how it stacks up to the real stats.
When a very young child looks at a picture, she can identify simple elements: "cat," "book," "chair." Now, computers are getting smart enough to do that too. What's next? In a thrilling talk, computer vision expert Fei-Fei Li describes the state of the art -- including the database of 15 million photos her team built to "teach" a computer to understand pictures -- and the key insights yet to come.
...Today, you can send a design to a fab lab and you need ten different machines to turn the data into something. Twenty years from now, all of that will be in one machine that fits in your pocket. This is the sense in which it doesn't matter. You can do it today. How it works today isn't how it's going to work in the future but you don't need to wait twenty years for it. Anybody can make almost anything almost anywhere.
...Finally, when I could own all these machines I got that the Renaissance was when the liberal arts emerged—liberal for liberation, humanism, the trivium and the quadrivium—and those were a path to liberation, they were the means of expression. That's the moment when art diverged from artisans. And there were the illiberal arts that were for commercial gain. ... We've been living with this notion that making stuff is an illiberal art for commercial gain and it's not part of means of expression. But, in fact, today, 3D printing, micromachining, and microcontroller programming are as expressive as painting paintings or writing sonnets but they're not means of expression from the Renaissance. We can finally fix that boundary between art and artisans.
Making toast doesn’t sound very complicated -- until someone asks you to draw the process, step by step. Tom Wujec loves asking people and teams to draw how they make toast, because the process reveals unexpected truths about how we can solve our biggest, most complicated problems at work. Learn how to run this exercise yourself, and hear Wujec’s surprising insights from watching thousands of people draw toast.
By studying the movement and bodies of insects such as ants, Sarah Bergbreiter and her team build incredibly robust, super teeny, mechanical versions of creepy crawlies … and then they add rockets. See their jaw-dropping developments in micro-robotics, and hear about three ways we might use these little helpers in the future.
What happens when we teach a computer how to learn? Technologist Jeremy Howard shares some surprising new developments in the fast-moving field of deep learning, a technique that can give computers the ability to learn Chinese, or to recognize objects in photos, or to help think through a medical diagnosis. (One deep learning tool, after watching hours of YouTube, taught itself the concept of “cats.”) Get caught up on a field that will change the way the computers around you behave … sooner than you probably think.
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