My beloved Domino doing a kitty flop.

The following is a video project I helped on for a media class. It’s short and amusing, and it prominently features myspecial(aka mentally challenged) tuxedo cat, Domino. Enjoy!

For the new “version” of this text object AKA blog entry, I wish to spare everyone’s suffering through a rehash the original. Rather, with the passage of time, I think it more appropriate to reflect on the major “historical” (what technically isn’t historical?) upheavals/changes since penning the original entry back in October. Naturally, I will continue to dwell on the theme of contagion with regard to the financial meltdown started circa 2008 that continues to this day. Namely, I extend the discussion that centers on this passage taken from the original blog post:

My point is not to give a blow-by-blow analysis of Part I, but to document my visceral reaction to it, which I have nearly forgotten at this point. In the blog post after this one, I have thrown compiled a list of words and thought associations culled from this section of the book. The emphasis is on those words and phrases most closely associated with the idea of a new paradigm for understanding digital contagions: they constitute internal threats equally if not more so than external (p. 44); the worst, most effective damage comes from targeted attacks (“shocks”) at key, well-connected nodes in the network (p. 45); under the concept of a scale-free topology of networks, the success of a contagion stems from infecting a few select nodes (the elite nodes, I would say) in close proximity to alike “power nodes” or hubs that are incredibly well-connected (better than the average “network assemblage”) to the rest of the network and lie in relatively close “spatial proximity and equilibrium” to each other (p. 55).

While Thomas S. Ray is quoted as saying, “The objective is not to create a digital model of organic life …”, I am in a way breaking this rule by applying a newly refurbished digital model of virality and contagion to the socio-political phenomena (not necessarily organic, I realize) of the latest financial crises. After spending last summer reading Matt Taibbi’s Griftopia: Bubble Machines, Vampire Squids, and the Long Con That Is Breaking America and parts of Naomi Klein’s Shock Doctrine: The Rise of Disaster Capitalism, I cannot help but see the latest round of disastrous events clearer than ever through the lens of this reconfigured model of digital contagion.  The corruption (credit default swaps, toxic loans, bad mortgages, housing market collapse) that infected our financial system stemmed from a small cabal of powerful, well-connected players (e.g., Wall Street Bankers, Goldman Sachs, Lehman Brothers, Bear Stearns and others aided and abetted by politicians, lax government regulation, the Federal Reserve lead by Alan Greenspan) – the nodes or network assemblages of aristocratic connectivity whose activities were kept well hidden from public scrutiny (i.e., they were a nearly invisible internal threat) – many of whom paradoxically ended up rewarded for their misdeeds thanks to a political apparatus (the other internal hubs or nodes of power) more accountable to the anti-democratic influence of corporations than to the democratic influence and outcries of its own people.

Network analysis lends itself easily to the examination of the collapse of markets. It provides an adequate though not comprehensive paradigm for making sense of the mess that is the Great Recession. If I may call upon my faulty memory of Christakis and Fowler, the network paradigm grants us a more nuanced understanding of the phenomenon  of the financial collapse than strictly limiting our view to key individual players (methodological individualism) or its polar opposite, the (economic, political) system as a whole (methodological holism). Rather, a happy medium that strikes a balance between the two methodologies is called for in the adoption of the network paradigm. However, the trap we want to avoid is that of an uncritical exaltation of the network employed by Christakis and Fowler. After all, their infectious, quasi-Pollyannaish attitude toward networks likely contributed to the failure to see and perhaps even prevent (or at least mitigate) the financial disaster of the century sooner.

Rather, the approach of Galloway and Thacker (The Exploit: A Theory of Networks) offers a more critical, albeit more intellectually challenging, method with which to interpret the collapse as a whole. I will grant that contagions on digital networks are not in and of themselves malignant or malevolent. Such blanket judgments are facile and shallow, as we well learned in The Spam Book. If I may hark back to my original musings on contagions through the light of network analysis, I still hold to the assertion that a network model or network theory given the Galloway and Thacker treatment (that is, filtered through the lenses of Deleuze, Guattari, and assorted pomo philosophers) opens up a fuller understanding of the latest exploits enjoyed (and inflicted) by the “winners” of the economic debacle.

At play in the collapse were multiple networks (or “assemblages” to use Spam Book terminology) operating at different levels. In one corner were the banksters and hedge fund managers, AKA the investment managers AKA the big gamblers. They operated under a dogged delusion of optimism, that is, they were determined to take large, unnecessary risks in the name of big profits. If they lost money, well – so what? - it wasn’t theirs being lost. It was the investors’, the often unwitting pawns in the game (they make up another network), who would under watchful, controlling eye of the investment managers have little to gain and everything to lose. And, so their thinking often went, the next “big win” was just around the corner. There was no way that any underhanded dealings or gigantic losses would catch up to them. If so, they would be long gone, leaving the people to whom they were legally, financially, and ethically beholden (in theory) to foot the bill.

If history, sociology, and human psychology have taught us anything, it’s that this economic optimism is irrational, inflated, and unfounded. In the WS gambling game, there has to be losers; not everyone comes out rosy in the end. Yet the fast and loose players deluded themselves into believing that investments could go nowhere but up, and those that knew better would simply jump ship as soon as the floor fell out beneath them. With so many investors’ pensions and retirements on the line, it is very sad to think that we lowly “ordinary folk” have come to depend on such a system for our fortunes during our twilight years. The folly of irrational faith in The (Great Free) Market demonstrates what a tragedy such thinking leads to in light of recent events.

Even worse is the thought that so much of the finance game is rigged against us, the “lesser” network AKA the network that doesn’t (but should) hold any power all along. The “big players” AKA elite nodes experience the best, strongest connections within their own network, which are then supplemented by equally powerful connections to the network of politicians (another major set of elite nodes) that aided and abetted them (and continue to do so to this day). As the elite nodes, the big players stood in a position of unfathomable privilege and power as they overplayed the wins and downplayed, hid, or outright lied about the risks in the WS game (again, all well documented in the writings of Matt Taibbi, Naomi Klein, and noted economist Paul Krugman). And yet, contagions of at least two types were at play during the collapse that illustrate how utterly undemocratic network structures are (as argued by Galloway and Thacker in The Exploit) as opposed to the “networks are liberating!” viewpoint advocated by Christakis and Fowler. The elite nodes/power players even manipulated the promiscuity factor to their benefit  (Sampson, p. 55). As the losses rolled in and piled up, the elite nodes were more than happy to dump those negatives on the unsuspecting and largely helpless network of joe-blow, you-and-me investors. For this purpose, the network of greaters and the network of lesser were well connected and rampantly promiscuous, in fact, unidirectionally so. When it came to sharing the gains, the level of promiscuity mysteriously and miraculously shrank to apply only to those in the circles or networks of the elite. Suddenly, the network of lesser was not so well connected and continues in this fashion to the present.

It will require an exploit or exploits of monumental proportions (again, as advocated by Galloway and Thacker) for the lesser network to see any justice exacted. Since writing my first entry on this topic back in October, we have witnessed (and many have contributed money and resources to) the coalescence of the Occupy Wall Street movement. An antidote to the insider, poisonous, avaricious behavior of Wall Street and to the overt corruption in Washington that enables such heinous behavior by the WS crowd is badly needed. A contagion of the most virulent, potent, and far-reaching kind is needed, but OWS has a dubious future in light of the extremely uneven ground on which it stands. In the past couple of months, many of the demonstrations have been quelled, pushed out of existence. Clearly, the powers that be, those in the position of the elite nodes, refuse to give up their power easily, going so far as to use the very police forces who are supposed to be dedicated to serving the people to serve their interests instead.

Before I ramble too long, I will close by stating that network analysis no doubt adds a new, highly enlightening dimension to the interpretation (network hermeneutics?) of the current economic crisis. Not to go all Marxist all of a sudden, but I believe that many steeped in the latest network theory (and there are a large number of  Deleuze, Guattari, Galloway, and Thacker fans in The Spam Book, all of whom take/took a critical assessment of capitalism and positions of power) would agree with me that network analysis lodges a strong indictment of capitalism, at least an indictment of a truly unfree, lopsided market under which many of us are buckling. NA is flexible, agile, multidisciplinary, and far-reaching in ways that I could not exhaustively explore in this blog entry to give a critical sizing up of events today and for years to come.

 New modulations of power

Anomalous digital objects

Digital contagions

Intrusive power, bodily invasion, uncontrollable contamination

Universal contagion

“too much connectivity”

Viral ecologies

Being viral versus becoming viral

Ch. 1 Mutant and Viral – Artificial Evolution and Software Ecology

“… the portability, exchangeability, and indeed mutability of this code enabled the system to be generative, and to exfoliate into a dynamically evolving ecology.”

“… a virus is not one particular sequence. Viruses are not pure species. They are, in fact, this cloud, this mutational cloud …”

Cumulative activity diversity diversity

“The objective is not to create a digital model of organic life, but rather to use organic life as a model on which to base our better design of digital evolution.”

Ch. 2 How Networks Become Viral  

Universal contagion

Universal contagion

Epidemic network power

Dynamic of infection

Mechanisms of sovereignty and resistance

Robust yet fragile

Virally vulnerable topology

Stability / instability

“too much connectivity”

“[V]irality is not limited to the criminal, terrorist, or activist enemies of capitalism, but also includes the internal spread of political corruption, economic panic, rumor, gossip, and scandal on technologically enhanced networks”

Inside the borders

Empire Empire Empire

Internet “robust in terms of resistance to random and common contagions, but highly vulnerable to targeted attacks from viruses aimed at clusters or nodes or shocks to the network …”

Hardt and Negri universal contagion and the rhizome

“The Internet is neither hierarchically arborescent nor entirely rhizomatic.”

Increasing centralization

Amplification of a few highly connected clusters

Scale-free topologies

Scale-free model

Emergence of a network

Structures emerge

Code

Emergence of the Internet

Fractal-like

Heterogeneous processes of social interaction

Complex networks

Homogeneously mixed

“… researchers realized that the complexity of the Web exhibited a strange, skewed topological consistency, the patterning of which prompted one author to contrast the democracy of random networks  with the far-from-random aristocratic connectivity of the scale-free model.”

“A few highly connected pages are essentially holding the World Wide Web together …”

Complex, collective behavior of physical matter

Rather than the analogies found in biological and technical codes

“Network politics care therefore be thought through in terms of the power relations established when nodes connected to the network become susceptible to repetitions contagious events.”

Assemblages

Robust yet fragile hypothesis

Epidemic spreading

Promiscuous computer

Swarm to fight a swarm

Spread from node to node

Chain of encounters

Spatial proximity and equilibrium

Opportunities to spread

Hubs intervallic points

Epidemic bridges

Contagious assemblages

Role instability plays in the organization of stable social wholes

“Epidemics ignite public fears with great ease, in part because the ‘enemy’ is often undetected, and therefore potentially everywhere.”

Administrators of fear

Prolong uncertainty

Anomalous and contagious event

Fuzzy techniques

Fuzzy gradations

Heterogeneous compositional force 

Reactions, Thoughts, Musings on Part 1: Contagions

Reading the essays in Part I required extra exercises in anger management to complete. Unless you are completely removed from the U.S. economy – i.e., you live in a hole with no electricity or running water and conduct all material transactions via bartering because you possess no national currency – or you are one of rare few who considers him-/herself part of the richest 1% in the country, I cannot grasp how anyone can get through Contagions without experiencing even the slightest elevation in blood pressure. While this portion of the book ostensibly dealt with re-conceiving the phenomenon of viruses and contagions in the digital context, for better (or perhaps erroneous) understanding, I could not help but incessantly draw parallels to the “contagion” of economic and financial collapse that has befallen this nation and the world, that is, regard this new conception of contagion in the social arena.

“[V]irality is not limited to the criminal, terrorist, or activist enemies of capitalism, but also includes the internal spread of political corruption, economic panic, rumor, gossip, and scandal on technologically enhanced networks.” (Tony D. Sampson, p. 44)

“ … the far-from-random aristocratic connectivity of the scale-free model.” (Tony D. Sampson, p. 52)

“… vulnerable to targeted attacks from viruses aimed at clusters or nodes or shocks to the network …” (Tony D. Sampson, p. 45)

In Part I: Contagion, the authors reinforce the notion that the way to think about digital contagions is not by the old ways of representational analyses (e.g., biological and immunological analogies) that ultimately end up short. Rather, we must shift our viewpoint by casting these old paradigms aside and looking at viruses and digital contagion on their own terms. For instance, the book’s authors invite us to stop looking at viruses and anomalies in a strictly good/bad, good/evil sense, because depending on the situation viruses can act either as parasites or “enablers or other digital life forms” (p. 28). They can’t simply be classified as one or the other, in absolutes. Also, it is short-sided to regard digital contagion strictly in terms of an inside/outside dichotomy, that is, as an external or outside threat to the system only. The first quotation above illustrates that digital threats can just as easily spread from the inside, completely ignoring any keep-out-at-all-costs external-only defense.

My point is not to give a blow-by-blow analysis of Part I, but to document my visceral reaction to it, which I have nearly forgotten at this point. In the blog post after this one, I have thrown compiled a list of words and thought associations culled from this section of the book. The emphasis is on those words and phrases most closely associated with the idea of a new paradigm for understanding digital contagions: they constitute internal threats equally if not more so than external (p. 44); the worst, most effective damage comes from targeted attacks (“shocks”) at key, well-connected nodes in the network (p. 45); under the concept of a scale-free topology of networks, the success of a contagion stems from infecting a few select nodes (the elite nodes, I would say) in close proximity to alike “power nodes” or hubs that are incredibly well-connected (better than the average “network assemblage”) to the rest of the network and lie in relatively close “spatial proximity and equilibrium” to each other (p. 55).

While Thomas S. Ray is quoted as saying, “The objective is not to create a digital model of organic life …”, I am in a way breaking this rule by applying a newly refurbished digital model of virality and contagion to the socio-political phenomena (not necessarily organic, I realize) of the latest financial crises. After spending last summer reading Matt Taibbi’s Griftopia: Bubble Machines, Vampire Squids, and the Long Con That Is Breaking America and parts of Naomi Klein’s Shock Doctrine: The Rise of Disaster Capitalism, I cannot help but see the latest round of disastrous events clearer than ever through the lens of this reconfigured model of digital contagion.  The corruption (credit default swaps, toxic loans, bad mortgages, housing market collapse) that infected our financial system stemmed from a small cabal of powerful, well-connected players (e.g., Wall Street Bankers, Goldman Sachs, Lehman Brothers, Bear Stearns and others aided and abetted by politicians, lax government regulation, the Federal Reserve lead by Alan Greenspan) – the nodes or network assemblages of aristocratic connectivity whose activities were kept well hidden from public scrutiny (i.e., they were a nearly invisible internal threat) – many of whom paradoxically ended up rewarded for their misdeeds thanks to a political apparatus (the other internal hubs or nodes of power) more accountable to the anti-democratic influence of corporations than to the democratic influence and outcries of its own people.

While I will admit that I had difficulty changing my own mindset so habituated to biological metaphors for my understanding of digital contagion, I have nonetheless adhered to the classic visualization of the virus for this project. To repeat, I have pulled out select quotations, words and phrases from Part I: Contagion that I believe capture the most salient concepts and themes on contagion, compiled them into a document, and fed them into Tagxedo. The resulting tag-image boldly encapsulates in a visual-verbal fashion a new (refined? nuanced?) perspective on digital contagion that, right or wrong, I believe is wholly applicable to socio-political phenomena.

http://www.tagxedo.com/artful/a8f66d3ed9264f8d

Alas, it’s time for the final class-related post on Jonathan Zittrain’s The Future of the Internet: And How to Stop It (Yale, 2008).

Right off the bat, the title on the book’s cover stunned me like a cold, unexpected slap from nowhere. Rather, it was specifically the subtitle that caught my eye: … And How to Stop It. I thought to myself, this guy must be out of his mind. Who on earth would want to get rid of the Internet? You can’t go back. That’s crazy!

Alas, I only needed to peer between the covers to get at Zittrain’s point. The history of the rise of the Internet has taken place through two different modalities of computing machine - the appliance (Hollerith and subsequently IBM’s tabulating and word processing machines) and the PC/personal computer (Jobs’ Apple II and Windows-based machines). Appliances exemplify closed-system computing. They serve preset functions very limited in scope, are safe and secure, and allow little or no flexibility to their users (and manufacturers for that matter) with regard to changing or adding to their functionality. By contrast, the personal computer could be symbolized by an open book whose story waits to be finished or even written by its users. It exemplifies open, generative computing. PCs possess few preset functions by their manufacturers and are open to the addition of new, often yet-to-be discovered functions by their users. This openness to tinkering by its users both blesses and curses the PC, for it endows it with its generative capacity and its large vulnerability (in comparison to appliances) to breeches in security. Without this generative capacity, Zittrain contends, the Internet would not have developed into the wondrous socio-econo-technological phenomenon it is today.

Yet, at the same time, it is this crucial feature of generative capacity that lies under an enormous threat. The flexibility and freedom to create enabled by the generative capacity of a technology also leaves it wide open to corruption and abuse. According to Zittrain, it will take only a 9/11-like watershed security breech (unlikely but possible) or a “death of a thousand cuts” (the “creeper scenario,” much more likely) to lock down our PCs (and the Internet) and turn them into sterile, unimaginative, highly restricted appliances and humanity will effectively enter the next socio-technological Dark Age (p. 51). Hence, there we find the reason for the book’s alarmist subtitle. It is this wholly plausible fate - the lockdown of the Internet - against which Zittrain inveighs.

Speaking of inveighing against things (enter my not-so-subtle segue into an entirely new point that doesn’t bore you with summarizing any more of the book), I have a confession to make about one of the model technologies Zittrain highlights as an example of successful generative technology: yes, that’s right, Wikipedia. Librarians and info professionals, as the story normally goes, have historically been quick to inveigh against Wikipedia, because it represents a shortcut in good research and critical thinking, or so they/we would say. After reading chapter 6, “The Lessons of Wikipedia,” I have to say that I have been convinced that this opinion no longer holds an “absolute truth,” much less is it entirely correct. Sure, I agree that Wikipedia should not be one’s sole source of information, especially with regard to projects that require serious, thorough research (e.g., academic papers). I would say the same for the use of any encyclopedia, for that matter. It can serve as an excellent starting point, a place to help brainstorm ideas on a topic (i.e., discovery tool), a source for background information on nearly any topic. However, as I always strive to impress upon all the student researchers I encounter, it should not turn into one’s one-stop, all-in-one destination for research. You have to expand your horizons beyond what is found there. That’s what the references are for!

That being said, Zittrain has opened my eyes to the reason Wikipedia encompasses more than just an online encyclopedia. Despite its many ups and downs (but mainly, they have been ups), Wikipedia stands head and shoulders above the competition, because it embodies the essence of generative technology:

Wikipedia’s success … is attributable to a messy combination of constantly updated technical tools and social conventions that elicit and reflect personal commitments from a critical mass of editors to engage in argument and debate about topics they care about. Together these tools and conventions facilitate a notion of “netizenship”: belonging to an Internet project that includes other people, rather than relating to the Internet as a deterministic information location and transmission tool or as a cash-and-carry service offered by a separate vendor responsible for its content. (Zittrain, p. 142)

In this passage, Zittrain conceptualizes Wikipedia using the language of Lawrence Lessig, namely the “four constraints” of regulation in Ch. 7, “What Things Regulate,” of Code v. 2.0. They are:

These four constraints are better understood in tandem, interdependent parts of a dynamic system of regulation imposed on the “dot” (in this case, generative technology or Wikipedia). Changes in one often affect changes in one or more other constraints. Therefore, as Lessig argues in Code 2.0, a complete view takes into account all four modalities together (p. 123). Regarding each constraint in isolation generates an incomplete and potentially misleading picture. Thus, for example, architecture applies to hardware of the Internet and servers that are used to host Wikipedia as well as the software that allows its contributors to generate entries. This architecture is in turn shaped by Wikipedian’s norms or set of community-generated rules - which among other things require that anyone with access to the Web can become a Wikipedia contributor, an enormous openness to public involvement (FotI, p. 146) - and laws - which Wikipedia honors and upholds, such as laws on copyright and defamation.

Given Lessig’s 4-sided paradigm, we can appreciate the power and complexity of Wikipedia as a generative technology, an almost organic, living entity, an ever-dynamic “work in progress” (FotI, p. 142), a representation of “semiotic democracy” (FotI, p. 147) that owes its very existence to its community of dedicated creator-participants, the netizens. On this last part, I will close by saying that, explicitly and implicitly, I believe that Zittrain regards netizens and their actions (or lack thereof) as a major key in preserving the Internet as a generative technology and prevent it from suffering a sad fate of being reduced to mere appliance. If you and I value generativity and believe its benefits are worth the very real and significant risks that it entails, as responsible netizens, we must be proactive and vocal in our support and protection of it. Now is not the time for slacktivism!