Dan Woods had an intersting column on the “Myth of Crowdsourcing” on Forbes online the other day. Best quotes:

“There is no crowd in crowdsourcing. There are only virtuosos, usually uniquely talented, highly trained people who have worked for decades in a field. … The crowd solves nothing, creates nothing.”

“There is no crowd of open-source developers ready to attack every problem. ”

“without the virtuoso contribution at the outset, they would achieve nothing.”

“Does crowdsourcing exist as it is popularly conceived? Yes, it does, but it doesn’t have anything to do with innovation. …The other businesses mentioned in the crowdsourcing category… are really versions of Wikipedia, that is, aggregations of the inventions of individual virtuosos”

“[crowdsourcing should be conceptualized as] broadcast search.”

In short: Only virtuosos innovate, not crowds; crowds can’t solve anything; virtuosos steer the crowd. Dan Woods concludes that crowdsourcing is not about creating collective intelligence and labour force that would unite in creating new things. Crowdsourcing would not create collective intelligence and not result in mass co-creation. Following Wood’s ideas, crowdsourcing is a mode of production, and as such it combines elements of Taylorism (splitting up working packages into small chunks like in Mechanical Turk) with a tender technique often used by creative buyers: let the service provider first show what their solution would look like and then decide whether it’s fine for you and worth some of your money. Jeff Howe uses the name ‘open call’ for this. It’s open neither the caller, nor the called are obligated to anything. The called is free to answer, the caller is free to accept the answer. Reading Jeff Howe’s crowdsourcing blog, you can easily get the impression that he touts crowdsourcing as a way to get out of the recession. But at what price? Brabham has the answer: ”Proportionately, the amount of money paid to the crowd for high quality labor relative to the amount that labor is worth in the market resembles a slave economy.” {Brabham 2008@83}

Surprisingly, Brabham is very optimistic about the civilizing potentials of crowdsourcing. “I am eager to see us learn from the successes and mistakes of crowdsourcing so that we can apply the best principles to the non-profit world and in the fight for social and environmental justice. ” {Brabham 2008@87} Never underestimate scientists’ ingenuity. They can turn nuclear energy into an ecological blessing, advanced interrogation techniques into a humanitarian act and and war into a means for creating peace. But, please, using a “slave economy” technique as an instrument to “fight for social…justice”? Well, Brabham defines crowdsourcing as a two-pronged concept: “Crowdsourcing is an online, distributed problem solving and production model already in use by for–profit organizations such as Threadless, iStockphoto, and InnoCentive.” {Brabham 2008a} The key word here is: “problem solving”.

Brabham draws on theory (idea? modes?) of the “Wisdom of Crowds”, which basically states that ‘under the right circumstances, groups are remarkably intelligent, and are often smarter than the smartest people in them’ (Surowiecki, quoted by Brabham 2008). The new web-based knowledge communities and their knowledge culture would alter the operational modes of commodity culture. “Thus, there may be an immense amount of good that can come from the existing for-profit crowdsourcing applications in that we may be able to harness the intelligence-aggregating engine of the crowdsourcing model to blend commodity culture with social justice goals.” {Brabham 2008@80} There is a point.

But anyway. It’s not so much the social aspects that raised my interest in Brabham’s article and crowdsourcing. It’s rather the mix of centrality and decentrality, voluntary engagement and exploitation, individuals and masses, openness and propertization.

Brabham considers the crowdsourcing model as way to overcome limits and restrictions of the open source production model, for better or worse. The latter is characterized by “transparency and access in the design stage”, freedom from intellectual property law constraints, openness brings in new creative ideas, contributors donate labour for self-interested motivations (feel-good rewards, increasing social-capital, fun in problem-solving), ownership of production factors by contributors, non-proprietability of production results. {Brabham 2008@82} The hacker ethic, or better: hacker’s hypothesis is that the output in such collaborative open environments is superior to others and socially favourable.

The applicability of the open source model is however limited when it comes to the production of goods other than software, goods which require material pre-products with a price and physical production facilities. In the end, even the creativity of contributing social producers depends on pre-production goods with a price tag, at least those necessary for his or her personal subsistence.

Kazman/Chen use the term crowdsourcing in just this two-pronged way. A rather useless way of conceptualizing crowdsourcing is to define it as a synonym to commons-based peer production. Kazman/Chen use this definition in an article on the rather interesting “Metropolis Model”, which they conceive as a sucessor of for software-development models such as agile development, Rational Unified Process or waterfall model. “Crowdsourcing—the popular term for commons-based peer production—is used to create value in information technology, the arts, basic research, and retail business.” {Kazman 2009} I will discuss commons-based peer production in another blog entry. But for now: It is rather sloppy to define “crowdsourcing” as a production technique for proprietary services with the words “commons-based”. For Kazman/Chen, co-creation, crowdsourcing, commons-based peer production, community-based service seem to be synonyms. That certainly is a conceptual mess: “Examples of co-creation have emerged, from OSS to Wikipedia, Facebook, Amazon’s Mechanical Turk, and many other community-based service systems (CBSSs). Each is a complex software-intensive or software-enabled system co-created by its participants—the crowds.” {Kazman 2009@77}

Summing up, there are at least three different definitions of crowdsourcing used by scientists and journalists: In the first, narrow sense, crowdsourcing refers to a mode of production (or problem solving) in which — following Howe — a central firm harnesses selected contributions from individuals who respond to an open call for proposals. In a second, slightly wider sense, crowdsourcing doesn’t only call for individual proposals, but also includes self-organized collaboration amongst individuals of the crowd. Both definitions assume the propertization of the contributions of the called by the central organisational firm or actor, while the latter also assumes that collaborating individuals can produce more innovative results than the ingenious virtuoso. A third definition, the widest one, equals crowdsourcing to commons-based peer production. This definition however would almost level the conceptual differences between crowdsourcing and open source-like production modes. (More on that in subsequent posting.) The crucial differentiator to open source models is that the crowd’s product can be appropriated. Commons-based peer production-like crowdsouring would resemble something like software produced with an GPL libraries in an open-source way, but licensed with a Microsoft EULA.

———-

Here’s a preliminary scheme of production modes (I’ve left out crowdsourcing III, i.e. commons-based peer production-like crowdsourcing, as it doesn’t make sense at all.)

———-

References

Brabham, D C. “Crowdsourcing As a Model for Problem Solving: An Introduction and Cases.” Convergence 14, no. 1 (2008): doi:10.1177/1354856507084420. http://con.sagepub.com/cgi/content/abstract/14/1/75.

Brabham, D C. “Moving the Crowd at Istockphoto: The Composition of the Crowd and Motivations for Participation in a Crowdsourcing Application.” First Monday 13, no. 6 (2008): 1-22. http://firstmonday.org/htbin/cgiwrap/bin/ojs/index.php/fm/article/viewArticle/2159/1969.

Howe, J. “The Rise of Crowdsourcing.” Wired Magazine 14, no. 6 (2006): 1-4. http://www.wired.com/wired/archive/14.06/crowds_pr.html

Kazman, R, and H M Chen. “The Metropolis Model a New Logic for Development of Crowdsourced Systems.” Communications of the ACM 52, no. 7 (2009): 76-84. http://portal.acm.org/citation.cfm?id=1538788.1538808

more magazine articles on Crowdsourcing: http://crowdsourcingexamples.pbworks.com/Acknowledgements-and-Sources

Wired’s series on Crowds: http://www.wired.com/techbiz/media/news/2007/07/assignment_zero_all

When Germany’s leading webpolitics site netzpolitik.org brought the message (“Toll Collect wird offen”), its leading brain Markus Beckedahl asked his broad and usually helpful audience how, with which tools and techniques some 10,000 pages of contract papers could collaboratively be analyzed to quickly find the rascalities that everyone was expecting to find there. I was split on whether this could work out or not, whether such a task is suited for social ad-hoc collaboration or not.

Back in 2004, I was working with a

small team of consultants for an ICT provider that was about to louse up an e-government project and thus wanted external expertise to learn what was going wrong. After days interviewing key persons, on-site inspections and analysis of key-documents it was obvious that the ICT provider had developed a prototype that simply didn’t meet the specifications of its clients. Worse, no one actually knew exactly which features should have been implemented in the first place.

It turned out that the contractual basis for the project consisted of a dozen of substantially different contracts between the ICT provider on the one hand and distinct German bundesländer (federal states) or groups of them on the other. As no one had thoroughly read the contracts before, the ICT provider had developed for two years and implemented functions they assumed they had to develop. Just to know how deeply they were in trouble, some several thousands of pages of contract paper had to be reviewed very rapidly. On the one hand, you have to dive deep into the text to understand it, but you also have to get an overview to get into the complexities of such set of contracts—a task you simply can’t split up and delegate to several persons. On the other hand, some tasks were handed over to trainees. They were gathered in a small lab, got copies of text analysis software installed on their desktops and created series of reports and text extracts. Those more senior cared about the overall strategy and the big picture.

In a sense, crowdsourcing is similar has similar characteristics. It is a mode of production that invokes a coordinating center and supportive helpers. The poster-child of web-based collaborative production, Wikipedia, is steered by the Wikimedia Foundation, a small organisation with 34 employees and $5.6 million turnover (or expenses) per year. Analogue foundations are set up for regional Wikipedias in more countries all over the world. Tens of thousands of contributors are coordinated by this central organisation and its national siblings. Notwithstanding this centre, Wikipedia’s contents are more the result of more egalitarian modes of production than created in a crowdsourced mode. But what is crowdsourcing then actually?

Jeff Howe, who allegedly came up first came up with the term “crowdsourcing” with his 2006 Wired article and acts as its evangelist ever since, has two definitions of crowdsourcing: a “White Paper Version: Crowdsourcing is the act of taking a job traditionally performed by a designated agent (usually an employee) and outsourcing it to an undefined, generally large group of people in the form of an open call.” And then a “Soundbyte Version: The application of Open Source principles to fields outside of software.” (Jeff Howe’s Blog) I would prefer a more generic definition that doesn’t see crowdsourcing just as the activity of outsourcing to the crowds, but as a distinct mode of production that is characterised by a designing and controlling center and the production at the edge by “an undefined, generally large group of people in the form of an open call” (ibd).

A prominent example of political ad-hoc crowdsourcing was launched earlier this year by the Guardian. The British daily had within a few days set up an web-based system, which enabled interested users to participate in a distributed analysis of MPs’ filed expenses. Users could contribute to the overall effort of reviewing 457,000 pages in total, and select and review a few of them. The designers of the crowdsourced solution admitted later on that “keeping up the interest is hard” (http://www.slideshare.net/simon/crowdsourcing-with-django). Too hard, obviously. Hardly 50% of all the documents online have been reviewed by the reading electorate. (Guardian)

It is helpful to know the limits and potentials of crowdsourcing. The recent debates about Wikipedia (Wall Street Journal) point at generic problems of social production: accuracy, breadth and reliability. In a sense, any organisational form has to struggle with these targets, yet crowdsourced production models are especially prone to run into difficulties with these organisational targets. For products to be reliable, modern production techniques comprehend quality management, training and certified qualifications—nothing a person working for free and for fun is too keen on. At commercial organisations, breadth of service offering is guaranteed by economic interests of service providers—more services, higher revenues, higher profits. For crowdsourced endeavours however, breadth of service offering implies more unpaid, yet somewhat differently compensated work. Wikipedia has to go on road-shows to sell work to others. This is not an option for smaller projects. Guardian’s crowdsourced expenses intelligence system seems to have stalled as the respective discourse vanished from news headlines.

Another approach to crowdsourcing involves payments for the work of the amateurs, as can be seen on websites such as iStockphoto. Crowdsourcing here creates “distributed labor networks [that] are using the Internet to exploit the spare processing power of millions of human brains” {Howe 2006}. Mechanical Turks so to speak, according to Amazon. This is the name for a “Human intelligence tasks” (HIT) brokerage website owned by Amazon. (Mechanical Turk) The seekers for these Mechanical Turks have “access to a global, on-demand, 24 x 7 workforce” that only gets paid “when you’re satisfied with the results”. A capitalist’s dream come true. According to Jeff Howe a “network of passionate, geeky volunteers could write code just as well as the highly paid developers at Microsoft or Sun Microsystems”.

The the underlying principle of crowdsourcing is “to connect with brainpower outside the company”. By R&D crowdsourcing, businesses can find people who could assist them in developing products and decrease time-to-market. {Howe 2006} On Innocentive, so called solution seekers “pay solvers anywhere from $10,000 to $100,000 per solution”. Many of these solvers allegedly are hobbyists or undergraduate student. One of Howe’s interviewees stated, “We have 9,000 people on our R&D staff and up to 1.5 million researchers working through our external networks”. An R&D managers dream come true.

Now, as the mode of crowdsourced production has been around for a few years, it is used in a range of markets. Anjali Ramachandran of London-based consultancy Many By Many has set up a wiki that enlists the types of businesses that currently make use of this mode of production. She categorizes them into four groups: “1. Individual businesses or sites that channel the power of online crowds 2. Brand-sponsored initiatives or forums that depend on crowdsourcing. I’ve included those that are no longer active as well, for reference. 3. Brand initiatives that allow users to customise their products, 4. Brand-sponsored competitions/challenges focussed on crowdsourcing”.

But what about crowdsourcing in politics? The ideal of a democracy is quite the opposite of a sheep market—a felicitous word for crowdsourcing coined by artist Aaron Koblin, who used Amazon’s Mechanical Turk in one of his art projects. (Interview with Koblin in Wired)

Mary Joyce has summed up the problems of applying crowdsourcing in politics or political activism. The definitional key of crowdsourcing is, “the task is defined at the center, produced at the edge”. (digiactive)

To come back to Wikileaks, Toll Collect and the call for collaborative contract analysis by netzpolitik.org: Such a thing wouldn’t turn out to be a crowdsourced net activism. While some nodes in bottom-up political networks will be more influential as others, none of them will be so influential to become the node that controls all the process and chops up the project into small chunks for the masses, into HITs. Or, to use the analogy of Aaron Koblin, to turn net freedom activists into sheep. A differentiator between crowdsourcing and peer production is the frequency and intensity of relations among the smaller nodes. Wikipedia’s problem might be that they have morphed from a peer-to-peer production model to crowdsourcing. And, by the way, it’s peer production, not crowdsourcing that is going to have an impact on existing political institutions.

Readers of netzpolitik.org came up with only a few suggestions how this massive contractual framework could be collectively analyzed. The aforementioned Guardian solution (presentation of the developer on technical details) was mentioned. Another approach is Bundestagger.de, a web platform that provides an API, the ability to comment and tag certain text passages of plenary session protocols of the German Bundestag.

A third user recommended to just use “grep”, the Unix command line tool to search text files. But nothing was ready to go. A day or two later, heise.de journalist Detlef Borchers, a notorious critic of German eGovernment projects gone wrong, had already published an article with key statements of the contracts. At such complex tasks, nothing beats a dedicated professional with attitude. As someone who makes a living with selling his computational brain cycles, I’m relieved. But where does it leave social ad-hoc investigation? Is there still some collaborative analysis going on in this matter? Maybe peer-produced net politics just needs more time to develop more effective tools and techniques.

Update 4.12.2009

“Given enough eyeballs, corruption and waste are similarly shallow problems.” (Brito, J. 2008. Hack, mash & peer: Crowdsourcing government transparency. Colum. Sci. & Tech. L. Rev. 9:119-122. http://www.stlr.org/html/volume9/brito.txt.)