Tuesday, April 28, 2009

DJs and Monkeys and Swishers, Oh My!

The DJ as rhetorician is becoming an important figure in academia. NYU's Aram Sinnreich has done an entire book-length study of DJ practices, and Spencer Schaffner has given academic talks in DJ form. Graduate students like Michael Bullock and Kevin Driscoll are also identifying themselves with the DJ m métie.

The DJ was also an important figure at today's session of Persuasive 2009, BJ Fogg, the father of captology as an academic discipline made the argument that the group's work aimed to "make the world a better place" through "mass interventions" that were altruistic rather than intended to "make a ton of money."

Fogg was suggesting a different matrix for thinking about persuasion that was fundamentally different from more conventional models for persuasive technologies, which he characterized in the bulleted list below:
  • Change attitude – behavior
  • Deep thinking
  • Theory guides steps
  • Control intervention
  • Measure result
  • Share with experts
Now he argued that "tradition" could be at odds with "impact," so he outlined three possible approaches that might be more successful in the age of the Internet.

1) "Million Monkeys" used automated or random mechanics to generate results. Like the "infinite monkey theory," it relied on creating many trials, on the assumption that traditional focus groups often couldn't create true viral sensations such as YouTube's Fred because they weren't considering enough possible results. As an example, Fogg showed Hunch, which "helps you make decisions and gets smarter the more you use it." Fogg argued that this approach fostered "branching knowledge" as content-creators kept busy "rolling out interventions."

2) "Savvy DJs" also uses creating many trials, but Fogg argued that for this group "metrics drive iteration." Just as a DJ has an audience and finds grooves people respond to, persuasive technologies could thing about "moving crowd and changing it up" by taking advantage of "feedback loops" and rapid analysis of "matching patterns." Fogg takes lessons from RockYou!, zynga, and slide as top application creators. He interviews Jia Shen and Johnnie Manzari to learn about how they "iterate multiple times a day" by being in constant contact via cell phone, since they need to watch metrics constantly and are "obsessing about the numbers all day and all night." Fogg argued that a program like Texting for Health fits this model, particularly since "what happens" can be tracked with a "built-in user base."

3) "Swishers" represents a more refined and analytic approach based on the sensibility of a critical individual. Fogg takes as his model Kara Swisher of the Boom Town all things digital blog for the Wall Street Journal, who "already analyzes what already exists." Like the DJ, this activity involves "pattern matching intelligence," where it "could be person or could be code," she resists the "schedule drives output" mode with her appealing video format that may well change "how we do journalism." In his talk, Fogg showed her working method in which viewers never ever see her face but understand her critical commentary through the eye of her flip camera. As Fogg notes, "people love point of view," although "as scientists, we are resistant to point of view."

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