Complexity and Geomagnetic Storms

A Perfect Storm of Planetary Proportions is a fascinating article linking two of my pet fascinations: complexity and catastrophe.The immediate prompt for the article is the expected 2012-13 peaking in solar activity and the potential it has for a geomagnetic superstorm that could disrupt power grids all over the world. The article provides lots of fascinating detail about the storms themselves. Here I focus on the connection to the disruption of power grids

From where we sit, the sun seems quiet enough. And yet it is constantly bombarding Earth with electrons, protons, and radio through X-ray waves. ... Under normal circumstances, this solar wind produces only negligible effects on Earth. Occasionally, though, the sun erupts violently, emitting solar flares or throwing out coronal mass ejections consisting of billions of tons of charged particles. ...

But how does all this space weather cause damage down on the ground? It's a multistep process. First, the intense magnetic field variations in the magnetosphere induce electric fields and currents over large areas of Earth's surface. In turn, this geoelectric field creates what are known as geomagnetically induced currents, or GICs, which flow in any available conductor, including high-voltage transmission lines, oil and gas pipelines, railways, and undersea communications cables. These interconnecting networks essentially act as giant antennas that channel the induced currents from the ground. Hit with a 300-ampere GIC, a high-voltage transformer's paper tape insulation will burn, its copper winding will melt, and the transformer will fail, either right then and there or in the future. High-voltage power grids are designed to withstand the loss of any single important element, such as a substation transformer, and then recover within a half hour or so. For a terrestrial storm like a hurricane or a tornado, this approach works well. But a severe geomagnetic storm covering an entire continent would cause multiple failures all at once.

The video below discusses the most recent major geomagnetic storm from 1989, a storm of roughly 1/10 the magnitude of those known to have occurred in the past. The last time we had a truly powerful storm was in 1921—decades before developed economies became utterly dependent on electrical infrastructure. So here we have a wonderful example of how complexity begets more complexity -- how the development of a complex technological infrastructure has led to the emergence of a new type of problem; a problem that requires yet more complexity (in the software and other aspects that manage the grid) in order to minimize the potential for widespread blackouts.

Network Analysis of A Complex Global System: the 147 Super-Connected Corporations that Run the World

Revealed – the capitalist network that runs the world
By wmw_admin on October 21, 2011

Andy Coghlan and Debbie MacKenzie – New Scientist October 19, 2011


[Caption: The 1318 transnational corporations that form the core of the economy. Superconnected companies are red, very connected companies are yellow. The size of the dot represents revenue.]

AS PROTESTS against financial power sweep the world this week, science may have confirmed the protesters’ worst fears. An analysis of the relationships between 43,000 transnational corporations has identified a relatively small group of companies, mainly banks, with disproportionate power over the global economy.

The study’s assumptions have attracted some criticism, but complex systems analysts contacted by New Scientist say it is a unique effort to untangle control in the global economy. Pushing the analysis further, they say, could help to identify ways of making global capitalism more stable.

The idea that a few bankers control a large chunk of the global economy might not seem like news to New York’s Occupy Wall Street movement and protesters elsewhere (see photo). But the study, by a trio of complex systems theorists at the Swiss Federal Institute of Technology in Zurich, is the first to go beyond ideology to empirically identify such a network of power. It combines the mathematics long used to model natural systems with comprehensive corporate data to map ownership among the world’s transnational corporations (TNCs).

“Reality is so complex, we must move away from dogma, whether it’s conspiracy theories or free-market,” says James Glattfelder. “Our analysis is reality-based.”

Previous studies have found that a few TNCs own large chunks of the world’s economy, but they included only a limited number of companies and omitted indirect ownerships, so could not say how this affected the global economy – whether it made it more or less stable, for instance.

The Zurich team can. From Orbis 2007, a database listing 37 million companies and investors worldwide, they pulled out all 43,060 TNCs and the share ownerships linking them. Then they constructed a model of which companies controlled others through shareholding networks, coupled with each company’s operating revenues, to map the structure of economic power.

The work, to be published in PloS One, revealed a core of 1318 companies with interlocking ownerships (see image). Each of the 1318 had ties to two or more other companies, and on average they were connected to 20. What’s more, although they represented 20 per cent of global operating revenues, the 1318 appeared to collectively own through their shares the majority of the world’s large blue chip and manufacturing firms – the “real” economy – representing a further 60 per cent of global revenues.

When the team further untangled the web of ownership, it found much of it tracked back to a “super-entity” of 147 even more tightly knit companies – all of their ownership was held by other members of the super-entity – that controlled 40 per cent of the total wealth in the network. “In effect, less than 1 per cent of the companies were able to control 40 per cent of the entire network,” says Glattfelder. Most were financial institutions. The top 20 included Barclays Bank, JPMorgan Chase & Co, and The Goldman Sachs Group.

John Driffill of the University of London, a macroeconomics expert, says the value of the analysis is not just to see if a small number of people controls the global economy, but rather its insights into economic stability.

Concentration of power is not good or bad in itself, says the Zurich team, but the core’s tight interconnections could be. As the world learned in 2008, such networks are unstable. “If one [company] suffers distress,” says Glattfelder, “this propagates.”

“It’s disconcerting to see how connected things really are,” agrees George Sugihara of the Scripps Institution of Oceanography in La Jolla, California, a complex systems expert who has advised Deutsche Bank.

Yaneer Bar-Yam, head of the New England Complex Systems Institute (NECSI), warns that the analysis assumes ownership equates to control, which is not always true. Most company shares are held by fund managers who may or may not control what the companies they part-own actually do. The impact of this on the system’s behaviour, he says, requires more analysis.

Crucially, by identifying the architecture of global economic power, the analysis could help make it more stable. By finding the vulnerable aspects of the system, economists can suggest measures to prevent future collapses spreading through the entire economy. Glattfelder says we may need global anti-trust rules, which now exist only at national level, to limit over-connection among TNCs. Bar-Yam says the analysis suggests one possible solution: firms should be taxed for excess interconnectivity to discourage this risk.

One thing won’t chime with some of the protesters’ claims: the super-entity is unlikely to be the intentional result of a conspiracy to rule the world. “Such structures are common in nature,” says Sugihara.

Newcomers to any network connect preferentially to highly connected members. TNCs buy shares in each other for business reasons, not for world domination. If connectedness clusters, so does wealth, says Dan Braha of NECSI: in similar models, money flows towards the most highly connected members. The Zurich study, says Sugihara, “is strong evidence that simple rules governing TNCs give rise spontaneously to highly connected groups”. Or as Braha puts it: “The Occupy Wall Street claim that 1 per cent of people have most of the wealth reflects a logical phase of the self-organising economy.”

So, the super-entity may not result from conspiracy. The real question, says the Zurich team, is whether it can exert concerted political power. Driffill feels 147 is too many to sustain collusion. Braha suspects they will compete in the market but act together on common interests. Resisting changes to the network structure may be one such common interest.

The top 50 of the 147 superconnected companies

1. Barclays plc
2. Capital Group Companies Inc
3. FMR Corporation
4. AXA
5. State Street Corporation
6. JP Morgan Chase & Co
7. Legal & General Group plc
8. Vanguard Group Inc
9. UBS AG
10. Merrill Lynch & Co Inc
11. Wellington Management Co LLP
12. Deutsche Bank AG
13. Franklin Resources Inc
14. Credit Suisse Group
15. Walton Enterprises LLC
16. Bank of New York Mellon Corp
17. Natixis
18. Goldman Sachs Group Inc
19. T Rowe Price Group Inc
20. Legg Mason Inc
21. Morgan Stanley
22. Mitsubishi UFJ Financial Group Inc
23. Northern Trust Corporation
24. Société Générale
25. Bank of America Corporation
26. Lloyds TSB Group plc
27. Invesco plc
28. Allianz SE 29. TIAA
30. Old Mutual Public Limited Company
31. Aviva plc
32. Schroders plc
33. Dodge & Cox
34. Lehman Brothers Holdings Inc*
35. Sun Life Financial Inc
36. Standard Life plc
37. CNCE
38. Nomura Holdings Inc
39. The Depository Trust Company
40. Massachusetts Mutual Life Insurance
41. ING Groep NV
42. Brandes Investment Partners LP
43. Unicredito Italiano SPA
44. Deposit Insurance Corporation of Japan
45. Vereniging Aegon
46. BNP Paribas
47. Affiliated Managers Group Inc
48. Resona Holdings Inc
49. Capital Group International Inc
50. China Petrochemical Group Company

* Lehman still existed in the 2007 dataset used

Source

Google+ goes Social: Why Should You Care?

Wired's Steven Levy has a long, but very insightful article, Inside Google+ — How the Search Giant Plans to Go Social, describing the company's recent rollout of Google+ and the company's long term plans to transform itself and its products in light of Facebook's success. This may well be great for Google's bottom line, but bad for humanity. Here's why.

Without going too deeply into the details of the new product vision (you'll have to read the article for that), there are two main components to Google+. The stream looks a lot like a Facebook feed: a stream of social information from friends and others -- but with a significant tweak. Google thinks they have solved the privacy issue by allowing you to easily create different 'Circles' of friends and, hence, share different information with different people. The second element, Sparks, is a stream of information on topics of interest to the user. But, unlike the results of the standard Google search, the Sparks search algorithms have been tweaked to deliver content that is fresh, visual and viral. In other words, there is a designed synergy: the Sparks stream brings things to your attention that you will want to share with one or more of your Circles.

Overall, the stream and Sparks are indications of how the need to respond to the social challenge has already changed Google’s philosophy. It’s almost as if the Emerald Sea team is creating an anti-Google. Before starting the company in 1998, Page and Brin had tried to sell their technology to portals like Excite and Yahoo, whose execs refused because the Google search engine was deemed too effective: It would fulfill a users’ requests and then briskly send them on their way, taking their lucrative eyeballs with them. Google insisted that search quality trumped stickiness, and built a business on the premise that users were best served by getting results that sent them off to preferred destinations.

But with these streams, Google is changing direction. Right now, the content from Sparks and the social stream is not intermingled, but it’s reasonable to assume that before long, the company will use its algorithmic powers to produce a single flow that skillfully mixes those apples and oranges. Google has already pulled off a much more complicated version of that trick with Universal Search, which includes web pages, images, videos, books, Tweets, news items and other formats among its results. And that’s only the beginning. With its deep resources of information about its users, Google is capable of delivering a comprehensive collection of information, tailored exactly to one’s needs and interests. “It’s the long-term vision that we have for that newsfeed, that stream,” Gundotra says. “We think long-term, four to five years from now, the system should be putting items in there not just from your friends, but things that Google knows you should be seeing.”
...
This mother of all streams would be the equivalent of an intravenous feed of information, with inclusion of all the vital content from our social graph and the world at large (Google calls this the “interest graph”). It would scroll forever, and everything would be relevant. If Google’s original goal was to expeditiously dispatch us elsewhere, with this near-clairvoyant stream, Google could turn us into search potatoes who never leave.

So, Google is changing its business model. Why should we care? To appreciate the significance of this, we need to take a short trip into the world of evolutionary anthropology. Conventional wisdom over the past 160 years in the cognitive and neurosciences has assumed that brains evolved to process factual information about the world. Over the past decade, that view has largely been displaced by the social brain hypothesis. Crudely put, the traditional view held that human information processing capabilities (our brain and related language skills) evolved in relation to adaptive pressures that favored the sharing of technical information and the ability to socialize came as an added benefit. The social brain hypothesis turns this explanation on its head: the selective adaptation was sociability -- specifically the ability to use language in order to bond in groups larger than than those of other primates which bond by touch through sequential grooming. According to the social brain hypothesis, the ability to share technical information is an extra bonus, not the primary purpose of language. This model corresponds much better with how people actually act: we spend 3-4 times as much of our day using language to socialize (How are you?) as we do using it to exchange technical information (That will be $29.95, please.)

In short, Google is recognizing that the primary focus of human communication is social rather than technical and adapting their product to take that into account. This could well be a good move for Google's bottom line, but it is a potentially bad development for humanity. We are facing a set of complex and interconnected challenges -- climate change, population growth, biodiversity loss, improperly regulated economies, new diseases, increasing inequalities in the distribution of income, the end of cheap energy supplies, the list goes on and on -- that require innovative thought and action to successfully address. And pretty much everyone who studies the process of innovation (see, for example, the clip below), argue that innovations come from places that allow ideas to have sex -- that is to interact with one another in ways that will generate something new.



In sum, innovation typically depends on connecting ideas that weren't previously seen as related to each other. The new Google framework, however, is designed to do the exact opposite -- to take all the information and knowledge that they have about you as an individual and deliver to you only those things they think will be of interest. I don't want to be a Luddite here. People are creative and will find new and interesting ways to use Google's social turn to their advantage.

But, everything considered, this development seems to negatively impact the likelihood that ideas will have sex in any individuals head in several ways. First, it turns an efficient search engine into another time suck. Second, while nominally facilitating connectivity (a good thing) it will actually tend to limit the breadth of information that the person receives and the types of connections their mind makes. Think, for example, of the difference between a) receiving a newspaper, scanning all the headlines and deciding to read something totally unexpected and b) receiving a feed limited to specific topics that, as a result, doesn't bring you the article in an area outside your interest. Third, it will take development dollars away from Google's previous focus -- technical search algorithms -- and, potentially, limit future developments in that area.

In a McLuhanesque sense, a new technology creates a new environment. My fear is that, everything considered, the environment created by Google+ encourages protected sex over unprotected sex and, as a result, is less likely to produce new offspring. In a world that desperately needs innovation, this is not a positive development

Finding Simplicity in Complex Ecosystems

A talk by ecologist Eric Berlow shows how network models and their nodes can help us find simplicity in complex systems, biological or social. The talk and demonstration of the model takes less than three minutes. The presentation is, unfortunately, so brief that he fails to describe the method by which nodes are selected and significant relationships are identified.

What I find most compelling about this concept is the possibility of using network/nodes analysis as a research method. I see that it has the potential to rival or exceed the capacity of statistical analysis to yield useful information for sociologists. The network/node analysis would reveal the significant relationships in a system; statistics would then be used as a refinement to quantify how strong the relationship is.