This session talked about sourcing intelligence from communities vs crowds. The crowd/community or audience/community distinction is something I’ve thought and talked about quite a bit. In the world of “social media,” I don’t think we’ve made the distinction or found it important enough. “Social media” is a marketing term, and much of that thinking has come from marketing professionals who are trying to understand how to do post-broadcast marketing, in a world where media and mindshare are decentralized and diverse, fragmented. In marketing, the coherence of media or communication environments is not an issue, so long as messages can be communicated effectively in a context to drive conversions or purchases. Random drive-by messaging in environments like Twitter and Facebook don’t have to have coherence to work as “social media” in this sense, however I’m more interested in building sustained conversations and collaborations, or “community.”
You can “crowdsource” wherever a crowd is gathered. The crowd itself needn’t be “wise” on the whole; but it’s useful to assemble a crowd that has within it sources of relevant intelligence. What do the members of a crowd have in common? A physical crowd can have no more than proximity, but our sense of the virtual crowd is that they share something more. A crowd that shares only membership at Twitter could be random, but when we crowdsource via Twitter, we’re usually addressing our particular slice of the crowd, which has affinity if only through their relationship to us as individuals, as part of our network.
Jeff Howe coined the term “crowdsourcing” in 2006, as a riff on the term “outsourcing.” Crowdsourcing was defined as taking a job traditionally performed by some designated agent, usually an employee or contractor, and assigning it instead to a crowd or collective. Trendwatching defines the term as “customer made.” I found an article at the site that deepens the definition in a business context:
Next year, says Reinier Evers of Amsterdam’s Trendwatching.com, will see the re-emergence of group decision-making power as organisations of all kinds try to harness the wisdom of crowds. But if 2006 was the year in which DIY or home-made internet content triumphed over all its competitors in sites such as YouTube, 2007, says Evers, will see talented amateurs on the net demand payment for the stuff they produce. Expect, he says, more and more user-generated content sites and ventures to move to a paid or revenue-sharing model in the next 12 months. An example of this crowdsourcing is the software company Cambrian House (cambrianhouse.com), which works by inviting huge numbers of people into the production process and then paying them royalties if their contribution makes any money. Even Lego wants its customers to make money. The toy company now lets online visitors (at factory.lego.com) design Lego models and upload them to a gallery to show off their skills. It recently organised a contest in which the winning 10 models were sold as Lego models, with the creators earning 5% of the revenues. The company is keen to expand the initiative.
According to Belsky and Kalmikoff, the crowdsourcing definition needs to evolve, especially beyond the common misconception that crowdsourcing means access only to free labor. They mention three business models:
1) Crowdsource wisdom (or knowledge/expertise/skill), as with Wikipedia.
2) Crowdsource labor, as with Amazon’s Mechanical Turk, or traditional spec contests.
3) Crowdsource both wisdom and labor, as with Digg or Threadless. Keep the community active in the business.
To the question of crowds vs communities… a crowd is definable through a common purpose or set of emotions. Where crowds are concerned, sourcing exists in sprints.
In communities, intent, beliefs, risks, etc. may be present in common, affecting identity and cohesiveness. Sustainability exists inherently in the organic, adaptive nature of communities. They talked about various risks and the need to ensure the means to have a true collaboration with others and produce a result that’s relevant. One risk that particularly resonated with me: careless engagement – apathy, where one or more participants don’t care enough to withhold something that’s crappy.
Another issue: where money is the sole incentive to perform, you’ll work just as hard as required to reach the monetary goal, and no harder. As Daniel Pink has noted, money is a poor motivator for quality work.
Another risk: wasted neurons, where people spend an inordinate amount of time working on stuff the majority of which is never used. In a managed environment, the role of the manager is partly to ensure the efficiency of effort. In self-organized crowdsourced operations, how do you avoid wrong turns?
Does crowdsourcing foster the emergence of community? Yes, where there’s incentive for conversation and learning, and where there’s real engagement. I think this depends on context and coordination.
Does it really tap collective wisdom? Does it nurture participants? It can benefit reputation, result in building new relationships. The best case is where resources are not wasted, and the terms and facts are crystal clear.