RLTB

or, Real Life Trumps Blogging.

This week has been a whirlwind between work and family with a death and other things.  Regular book reviews will resume next week!

Scott

Meme Warfare: Part 1

I’ve been introduced to a lot of new concepts through role-playing games. I myself don’t play them but I have always found them to be interesting in that they are often a treasure-trove of ideas. For example, I learned about space elevators from the 2300 AD role-playing game, specifically the module called Beanstalk. Memes I learned about from a game called Transhuman Space, which is set about 90 years from now and incorporates Artificial Intelligence, bioengineering, disembodied human intelligences, and other such weirdness. Much of it I’d seen or heard about before, but memes were a new concept, and an entire book for the game was written by Jamais Cascio, who I’d been following since his Worldchanging days.

Memes are not something I see examined very often in the international security community. Indeed, I don’t see it in business, international development, or anywhere but by futurists and some science fiction fans. Although some might associate them with propaganda or advertising, they are much more advanced and powerful than either. They will surely be a force to contend with in the future, and it would be good for people to be aware of them and know something about them.

So, what IS a meme, anyway?

Let’s start with a quote from Richard Dawkins, who came up with the name in the first place:

“Examples of memes are tunes, ideas, catch-phrases, clothes fashions, ways of making pots or of building arches. Just as genes propagate themselves in the gene pool by leaping from body to body via sperms or eggs, so memes propagate themselves in the meme pool by leaping from brain to brain via a process which, in the broad sense, can be called imitation. If a scientist hears, or reads about, a good idea, he passes it on to his colleagues and students. he mentions it in his articles and his lectures. If the idea catches on, it can be said to propagate itself, spreading from brain to brain.”

In Cascio’s book, he references the sources he used to create the sourcebook for memes. One of these sources was Thought Contagion: How Belief Spreads Through Society – The New Science of Memetics by Aaron Lynch. Lynch has passed on and this is an older book, so sadly, it is hard to tell how his theories may have changed over the intervening fifteen years.

In the first chapter, Lynch notes that memes are “a self-propagating idea” that “proliferate by effectively ‘programming’ for their own retransmission.” He then notes that there are seven ways that memes can be spread:

a) Quantity Parental – The idea causes the host to have more children than normal and so there are more possible hosts in the next generation. Just like compound interest, growth can be exponential. The Amish are an example.
b) Efficiency Parental – The idea has characteristics that make it so the children are more likely to adopt it. A cult is an example as children are indoctrinated from birth.
c) Proselytic: For example, Mormons. This can lead to fast growth but there are diminishing returns as the number of hosts goes down. In turn new memes may arise and old ones may return.
d) Preservational: People retain the beliefs longer.
e) Adversative: As a meme meets resistance, more aggressive variants develop that attack or sabotage competing memes. The Inquisition was an example.
f) Cognitive: These are logical and spread passively, such as scientific ideas.
g) Motivational: This is also passive. People believe in these because they expect the benefits will be higher of they do than if they don’t.

Of course, memes can have more than just one of these characteristics. A “propagative profile” can be done for a meme that shows its advantages in each of these areas.

Note that memes are not always negative – “Love your neighbor” is a positive meme. Memes can also build on other memes. Judaism was a meme, and Christianity was an outgrowth of it. Another way memes can arise is through the recombination of ideas. The Apocalypse + Christianity combination has led to the success of the “Left Behind” series.

Population memetics is, of course, “the study how proliferating memes combine and separate in a population.” Unlike with genetics, hosts can die or drop the belief. The most aggressive memes are most likely to succeed and will often result in new combinations or updated versions. The memes, in other words, evolve and the fittest survive in the realm of ideas, which Lynch refers to as the ideosphere.

Obstacles to the spread of memes include secrecy, competition, information hoarding, resistance to marketing, age and more. Age is a factor because older people tend to proselytize less as opposed to young people who are enthusiastic about spreading new memes.

In chapter 2, Lynch notes that the success of a meme is based on how much of the population believes it, and that if it doesn’t deliver on its promises (the world will end in 2000 AD!) it loses credibility and appeal and will be dropped. This also means that it doesn’t matter if the meme benefits the population or not, only that a majority believes it. Our modern world has also made it easier for this to happen due to the increases population (hosts), urbanization and communication. More people are living in proximity and are in touch with people from around the globe, not just their small village. He suggests that “Memetic self-awareness” can help prevent the spread of negative memes.

Lynch also compares memetics to other social sciences such as sociobiology, which is critical of memetics; evolutionary psychology, which overlaps with memetics in the areas of family life and reproduction; Politics, where memes are key. He notes, furthermore, that fashion depends on the fact that memes are diluted as they spread and die out and so new ones (new fashions) can take their place. Urban legends are also memes, and the most successful ones are the ones that mutate into a more interesting story.

He also examines how innovations can be propagated. Complexity will slow the spread of a new innovation but it helps if they are compatible with existing values, simple, and have increased benefits over the old ways of doing things. It’s also very useful if they can be tried out before adoption. Finally, Lynch notes that memetics and Asimov’s Psychohistory from the Foundation series are similar in the short term but that memes aren’t necessarily useful for long term forecasting.

In the rest of the book, Lynch applies his theory to various areas such as family structure, sex preference, evangelism, firearm ownership, and drug abuse. He develops hypotheses of how those memes are formed, spread, and die. I should note that I disagree with many of his explanations and in many cases I got the impression that he didn’t know the belief system well. Interestingly, modern Evolutionary Psychology theories differ from his explanations as well. In conclusion, the first two chapters do an excellent job of explaining the theory of memes and are well worth reading. The rest of the book is mere speculation and opinion on Lynch’s part.

What are some memes that you have encountered?

Review of Linked: The New Science of Networks

As I’ve noted previously, I’ve been exploring the science of complexity these last few months, trying to get a feel for the different subfields and how it can be applied to various real world issues. One of the areas in the field of Complexity is that of Network Science.

Linked:  The New Science of Networks by Albert-Laszlo Barabasi is a useful overview of the field.  It’s an easy read that covers a broad amount of the field and is a good layman’s introduction to network theory.  He shows that the world around us can be described in terms of Networks, and comments on how they are formed, what forms they take, and how they grow.  Note:  This is one of my longer reviews, and I left a lot out!

Barabasi starts off with one of the most famous network problems of history: the bridges of Konigsberg.  He shows how the problem can be solved using nodes and links, which was discovered by Leonhard Euler.  This segues into a discussion of graph theory and its history. Graph theory describes a network as a collection of links and nodes.  How to connect these nodes and the relations between them, as well as how the network grows in the first place, is the focus of the book.  Hr runs through a history, starting with random networks which although helpful in formulating basic laws, do not really describe real world networks.  He describes Stanley Milgram’s famous six degrees experiment and how Barabasi and his team researched it and found similarities in other networks of small worlds, where any node can reach any other node in a small number of jumps no matter how large the network.  He also talks about the strength of weak ties.

Clustering – each of us has a small number of close friends – is a key structure in networks and Barabasi talks about these and how a few links between them reduces the length between distant nodes.  Still, the nodes are all egalitarian and this is not how it works in real life.  Barabasi refers back to Malcolm Gladwell’s book The Tipping Point, talking about connectors and hubs – which means they have more than the average number of links which the egalitarian model doesn’t allow.  Hubs are apparent in the Kevin Bacon Game and in airline networks, among others.  The distribution follows a Power Law rather than a bell curve.  These networks are “scale-free” since there is no average node.

A discussion Of Pareto’s 80 / 20 law and a discussion of “phase transitions” follows, and how understanding them helps us to see how hubs appear in networks.  He notes that networks grow and are not static, and that counterintuitively just because a hub is old doesn’t mean it will get the most links – although that does play a role.  There is “preferential attachment” – nodes prefer to link to nodes that already have a lot of links.  Google today is a perfect example.  In other words, the rich get richer…

A basic prediction of scale-free networks is that the first mover will have an advantage in forming the most links.  In real life networks, however, this isn’t the case.  This is because contrary to the assumption that all links are the same, they instead are all different with different intrinsic properties.  This is defined as fitness.  More fit nodes will end up with more links.  This is complementary to preferential attachment which only examines the number of links.  It also shows that the number of links is therefore independent of when the node joins the network.

In an intriguing chapter,  Barabasi then turns to the weaknesses of a highly-interconnected network.  Most networks in nature are highly interconnected and are also highly robust in that the failure of one component won’t take down the whole network.  Barabasi and his team investigated this phenomenon.  They found that for these networks, removing a large number of nodes typically had little or no effect on the functioning of the network.  This is due to the hubs model – removing nodes randomly eliminates a large number of tiny nodes and not very many hubs, which preserves the integrity of the network since the tiny nodes aren’t very interconnected.  However, if the Hubs are specifically AND simultaneously targeted, the network will quickly break apart.  This, then is the primary weakness of these networks.  they are not vulnerable to accident, but are highly vulnerable to attack.  This applies to both man-made and natural networks from the internet to food webs.  Cascading failures can happen when the load from a failed node is shifted to other nodes that are unable to handle the load, whereupon they fail and pass it on to yet more nodes that cannot handle the load, and so on.  This is what happens during blackouts and rolling power failures and in denial of service attacks on routers.  These happen in dynamic networks and still need researched.

Using these findings of network theory, Barabasi discusses the spread of ideas, fads, and viruses, using as examples AIDS, computer viruses, jokes, and hybrid corn.   Malcolm Gladwell covers some of this in The Tipping Point.  One of the more surprising findings was that the rate of spread does not depend on virulence.  The solution is to target the cures to the hubs.  In AIDS, this would involve targeting the people who are most likely spreading the virus (those with many partners) as opposed to those who don’t (people with only one or two partners).  There are, obviously, ethical questions associated with this course of action.  Barabasi also examines the resilience of today’s internet (the physical infrastructure as opposed to the World Wide Web).  Instead of being a mesh as it was originally designed inj the 1950s, the Internet is more of a hub and spoke model that has grown organically.   This is why the Internet, too, is vulnerable to an attack on Hubs, rather than being perfectly resilient.  It also enables “parasitic computing,” where your computer can be “hijacked” and used to perform functions for a computer thousands of miles away – this is done with spam, for example.  It can also be used voluntarily, as in SET@Home or research into protein-folding.  Another question asked is that as the Internet continues to grow across the planet as it is connected to computers and sensors and cell-phones, will it eventually become self-aware?

One surprising thing about the World Wide Web is how difficult it can be to find information, even though theoretically the amount of information is limitless.  Google, surprisingly, indexes less than 25% of all the pages out there!  Worse yet, despite the fact that most webpages are separated by an average of nineteen links, due to the architecture of the Web, only 24% of pages can be reached by surfing from one to the other.  This is due to the structure of the Web: it is a Directed Network.  Barabasi describes this in detail.  Also, due to these properties, sections of the web can be partitioned off – providing a tool for control of access.  However, the topology of the Web as described here is much more effective than a government at keeping a website hidden!  Barabasi notes that the Web is little understood and a great deal more time and attention should be paid to understanding it.

Networks are common, and especially so in biology.  Barabasi also discusses how network theory can be applied to business and the economy.  He posits that to compete organizations need to go from a tree hierarchy to a web or network instead.  They will also participate in ever interconnected webs with suppliers and customers.  He shows how members of boards of corporations are ever more interconnected with hubs – 20% of them serve on more than one board.  The degree of separation of boards of directors is only three!

In conclusion, Barabasi summarizes:  “…though real networks are not as random…as envisioned, chance and randomness do play an important role in their construction.  Real networks are not static, as all graph theoretical models were until recently.  Instead, growth plays a role in shaping their topology.  They are not as centralized as a star network is.  Rather, there is a hierarchy of hubs that keep these networks together, a heavily connected node followed by several less connected ones, trailed by dozens of even smaller nodes. ”  There is no center, or controller, in the middle of the network that could be removed to destroy the web.  They are instead self-organized with emergent behavior.  Al-Qaeda is an example of a web organization, which is why the United States military – a hierarchical tree organization – has had trouble battling it.  Barabasi suggests that “We must eliminate the need and desire of the nodes to form links to terrorist organizations by offering them a chance to belong to more constructive and meaningful webs.”  We can do this by attacking “…the underlying social, economic, and political roots that fuel the network’s growth.”  Barabasi sees the future of network theory as understanding complexity and “move beyond structure and topology and start focusing on the dynamics that take place along the links.”

The Great Depression and today

In his book Lords of Finance: The Bankers Who Broke The World, Liquat Ahamed writes the story of the Great Depression of 1929 by following the lives of the Central Bankers of four of the leading countries of the time – France, Germany, England, and the United States. It is a new perspective to me, and while I don’t pretend to know all the differences between the Austrian School and the Keynesians, I thought it was very interesting. Reviews of the book are generally positive although there are followers of Austrian theory that state that Ahamed, who worked in the past for the World Bank, is too accepting of Keynes.

Again, I’m not well read enough in economic theory to say. Ahamed does make a case that the slavish adherence to the gold standard by these men was a prime cause of the Great Depression and that the ultimate cause was a “…series of misjudgments by economic policy makers” both in the decade before and during the Great Depression. By economic policy makers he refers to the politicians and the central bankers of the era. An item that caught my eye was the fact that the Great Depression was the confluence of a number of cascading failures:

* “The contraction in the German economy that began in 1928

* The Great Crash on Wall Street in 1929

* The serial bank panics that affected the United States from the end of 1930

* The unraveling of European finances in the summer of 1931″

Ahamed compares these to (respectively):

* The Mexican Peso crisis in 1994

* The bursting of the Dot-Com bubble in 2000

* The financial crisis of 2007-8

* The Asian Flu of 1997-8

He states that had these events occurred together, we may have seen a financial disaster of the scale of the Great Depression. There are, however, a number of financial bloggers that believe that we are indeed headed for one anyway, and that the crisis of 2007-8 isn’t really over…

Some other items from the book I thought were interesting:

* Before World War I, Norman Angell, a British journalist, wrote a book called Europe’s Optical Illusion. In it, he stated that “…the economic benefits of war were so illusory…and the commercial and financial linkages between countries now so extensive that no rational country should contemplate starting a war. The economic chaos, especially the disruptions to international credit, that would ensue from a war among the Great Powers would harm all sides and the victor would lose as much as the vanquished. Even if war were to break out in Europe by accident, it would speedily be brought to an end.” Both Tom Friedman and Tom Barnett (especially with respect to China) make similar arguments today – let’s hope they’re not as wrong as Angell was when he was “…trusting too much in the rationality of nations and seduced by the extraordinary economic achievements of the era.”

* Related to the above: “The argument that it was was not so much the cruelty of war as its economic futility that made it unacceptable as an instrument of state power struck a cord in that materialistic era.”

* An English newspaper article after the 1884 panic on the New York Stock Exchange: “The English, however speculative, fear poverty. The Frenchman shoots himself to avoid it. The American with a million speculates to win ten, and if he takes losses takes a clerkship with equanimity. This freedom from sordidness is commendable, but it makes a nation of the most degenerate gamesters in the world.”

* The signs of a mania: “…the progressive narrowing in the number of stocks going up, the nationwide fascination with the activities of Wall Street, the faddish invocations of a new era, the suspension of every conventional standard of financial rationality, and the rabble enlistment of an army of amateur and ill-informed speculators betting on the basis of rumors and tip sheets.” Indeed, ten percent of households were in the market in 1929.

* Almost a third of the speculators were female. There were even special brokerage houses set up to cater to only women.

* “One is led to the inescapable but unsatisfying conclusion that the bull market of 1929 was so violent and intense and driven by passions so strong that the Fed could do nothing about it. Every official had tried to talk it down. The president was against it; Congress too; even the normally reticent secretary of the treasury had spoken out. But it was remarkable how difficult it was to kill it. All that the Fed could do, it seemed, was to step aside and let the frenzy burn itself out. By trying to stand up to the market and then failing, it simply made itself look as impotent as everybody else.”

All in all, I thought it was a well-written summary of the actions and lives of the Central Bankers of the era, and it was an easy read. Whether or not you agree with the Keynesians or the Austrians, you should definitely read this book as a way of beginning to understand the events of the last few years…and where we could be headed in the future.