Societal Verification in the Connected Age

In Six Degrees: The Science of a Connected Age, Duncan Watts discusses the capabilities and limits of predicting and utilizing both individual and group behavior trends. Unraveling the conceptual bases of some commonly-known studies (such as the small-world method and the strength of weak ties/balance theory), Watts explores the introductory premises of aggregations and networks. In analyzing the domino effect of the Keller-Allston line failure on August 10, 1996, he opens the conversation over how individual behavior can be aggregated to collective behavior. He claims that although individual behavior is often well interpreted, collective behavior can sometimes be undeterminable through aggregation: “although genes, like people, exist as identifiably individual units, they function by interacting, and the corresponding patterns of interactions can display almost unlimited complexity” (26). Do these claims challenge or extend your perspective on previous topics of this semester such as nuclear deterrence or the prisoner’s dilemma exercise? Contextualizing these ideas into the readings from this week, how do these ideas of networks and group dynamics play into the U.S.’s application of new media and crowdsourcing into its nonproliferation strategy?

Extending Watts’ ideas into the discussion of societal verification, which application examples seem most appropriate for implementation (considering the potential benefits, effectiveness, possible consequences, and vulnerability pitfalls)? In “Societal Verification: Leveraging the Information Revolution for Arms Control Verification,” Hinderstein and Hartigan state that “‘societal verification’ refers to the concept of incorporating non-traditional stakeholders into verification and transparency regimes to increase the likelihood that violations of international commitments are detected” (1). They note several State Department recommendations such as giving citizens the ability to detect radiation spikes with the use of sensors, employing the use of quick response codes, etc (5). How would you compare these examples of societal verification to the China/North Korea example in the Lee/Lewis/Hanham piece? Are there certain uses of data analytics that are prone to be more valuable or more misleading? Do some examples jeopardize the vulnerability of citizen privacy and anonymity more than others? — Zoë