One recent example of crowdsourcing- found on the travel search site Flightfox– points up the close relationship between crowdsourcing and prosumption. While some members of Flightfox’s “crowd” of 900 “experts” may be traditional producers (e.g. 20 % of the experts are travel agents), the vast majority are likely to be prosumers. To be chosen as a prosumer by Flightfox, experts one must have demonstrated the ability to find low fares.
Flightfox “uses a contest format to come up with the best fare that the crowd- all Flightfox-approved users- can find” (Stross, 2011: 3). Once a contest to find the lowest fare for a given itinerary is posted, the crowd is invited to find and submit the lowest fare. The member of the crowd who comes up with the lowest fare gets 75% of Flightfox’s fee for that itinerary. Flightfox employees do no work on any given contest, although work was/is involved in setting up and maintaining its computerized system. The winner of the “contest” does a great deal of work and is rewarded, but many others do as much work, or more, for no reward at all. Not only are they not paid for their work, but it spurs on all involved, including the eventual winner, to work that much harder in order to have a chance at winning.
In fact, the crowd does work that involves far more variables than could be built into an affordable computer program. As the co-founder of Flightfox says, “`There are too many variables for it to be economically feasible to build an algorithm that covers every aspect of travel” (Stross, 2011: 3). Thus the crowd not only works hard, but it functions better than available computer programs. Thus Flightfox needs the members of the crowd, but it could never afford to hire the 900 of them and pay them a living wage.
Flightfox sees itself as having “commercialized” what “flight hackers” do normally and very much enjoy doing- hunting for low fares. Also part of the crowd is travelers looking for ways to finance their travel. The problem is that on any given search, only one member of the crowd benefits economically (and then quite modestly- 75% of a finder’s fee that ranges from $34 to $59). The many “losers” work for nothing (except, perhaps, for the joy of the hunt, the competition, and in this case the success of Flightfox). This system only works for the commercializing entity when all but one (or a few) of the crowd works for nothing.
In light of the exploitative nature of this relationship, Stross (2011: 3) comes to a truly astounding conclusion: ”It’s most heartening to see that in the domain of travel planning, humans still manage to hold their own. Every contest concluded at Flightfox is a small win for the species.” In strong contrast, my view is that yes, it is nice that humans, at least collectively, show that they can do things computers cannot do. However, the big winner here is Flightfox which has a crowd of prosumers working for it for no pay and contributing to its bottom line. As in most cases of commercialized prosumption, it is the capitalistic organization that is the big winner.
Bruns is also concerned with the way business adapts to groups of produsers (what he calls the “hive”). Produsers are used in crowdsourcing to serve the early needs of business, but later the business can “feed” (through recognition), help (provide services), harbor (host), harness (use the results obtained and offer recognition), harvest (use what is produced and add value), and hijack (lock in the produsers in such a way that the business profits) the hive. Exploitation does not play a prominent role in Bruns’s analysis except in the hijacking of the hive, but it is a major issue to students of prosumption (Fuchs, 200 ; Rey, forthcoming).