Human Computation: A Symbiosis of Man and Machine

16 Apr

Human Computing can be considered the effort to more effectively solve problems through the collaborative efforts of human and computer. The idea of humans and computers as complementary forces, each compensating for the other’s limitations. There exist human  ideologies and behaviors, such as risk and motivation, that prove difficult to translate into binary taxonomies required for a computer system to interpret and elicit appropriate information.

Man or Machine? Perhaps, one day Machine-Man

Quinn believes that human computation encompasses “problems that fit the general paradigm of computation, and thus might someday be solvable by computers” (2). This idea is akin to Licklider and Engelbart’s vision of computers acting as “tools”, essentially extensions of humans that can augment our intellect. Engelbart envisions

“…a way of life in an integrated domain where hunches, cut-and-try, intangibles, and the human ‘feel for a situation’ usefully coexist with powerful concepts, streamlined terminology and notation, sophisticated methods, and high-powered electronic aids” (Laue, p.9)

The notion of using computers to supplement and improve our own human abilities appears to have been incepted alongside computation itself. The potential limitations and possibilities of fusing logistical machines with human intuition always an attractive thought, with scientific attempts from as early as the 1950’s to instill human-like capabilities, such as language and reason into computers.

As Quinn points out, it is “only recently have we have begun to combine machine capabilities with the natural talents of the billions of Internet users around the world” (Quinn, p.1). Thus, Human Computation is actually one of several online, en-masse phenomena. These phenomena are identified by Quinn as Human Computation, Crowdsourcing, Social Computing, Data Mining, and the all encompassing Collective Intelligence.

What distinguishes these from each other is that while they all have a base group of amassed online entities, the goals and methods of each collective online presence vary wildly. For example, while both Social Computing (i.e., blogs & wikis) and Data Mining both require online activity from users, the former fosters rich inter-user dialogue and information exchange while the latter merely requires user browsing history.

All of these activities fall under the umbrella term of Collective Intelligence. Collective intelligence refers to this ability of virtual communities to leverage the combined expertise of their members. Quinn defines Collective Intelligence as “the notion that large groups of loosely organized people can accomplish great things working together” (4).

Quinn has developed classification systems of what he considers to be six of the most distinguishing and reoccurring factors found within most human computation systems. These factors include Motivation (user participation), Quality Control (maintaining information standards), Aggregation (compilation of research & data), Human Skill, Process Order (worker, computer, requester) , and Task Request Cardinality (flow of work effort from creators to end-user).

Human Computation is considered a burgeoning field in that only recently has technology developed substantially enough to pique our interests as to what the potential future of human/computer symbiosis may yield. It is generally accepted that computers can bolster and enhance our methods of intellect, yet the myriad ways that they already do are easily overlooked and sometimes difficult to discern from one another. Quinn believes in the potential for “systems of computers and large numbers of humans that work together in order to solve problems that could not be solved by either computers or humans alone” (2).

An NPR news story about computers learning to mix flavors better than chefs aligns itself well  with Quinn’s claim about problems that fit the general paradigm of computation. Flavors and tastes could potentially be assigned numerical values and algorithms could be developed so that computers could create appetizing foods.

TED talk in which Shyam Sankar discusses the rise of human-computer cooperation.


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