Law in the Internet Society

FoldIt and "Citizen Science"

-- By AaronChan - 19 Oct 2011

Online Models of Volunteerism

Information access does not need to be unidirectional. Instead of traditional broadcast models, information is a two-way street on the Internet. Online access is a tool for empowerment, not just by giving power to users, but also in allowing them to contribute. The Web is now a vast depository of human knowledge; it can be leveraged for greater societal goals. For example, the success of Wikipedia demonstrates what can be accomplished with collaborative experience.

Why does Wikipedia work? Under traditional capitalistic models, it should not. There is no payment, no remuneration for the hours upon hours editors put into it, yet it still exists and is constantly improved. The problem with understanding the new Information Goods Society where marginal cost of informational goods is zero is in grafting old models of compensation that ill fit the reality of online collaboration.

Is it na´ve to believe that people will contribute to the greater good merely out of their desire to improve the human condition? The failure of communism in practice was in the old economy where marginal cost does not equal zero. In the Informational Goods Society, economic models of compensation hold less weight. Eben speaks to this in the dotCommunist Manifesto. If compensation is not the model in the Informational Goods Society, then what is the main motivation for work?

Michael Goldhauber suggests that motivation on the Internet is driven by reputation. This is further refined by Rishab Aiyer Ghosh, who reapplies economic concepts to the Internet. Yet whatever the form the remuneration takes, it is still premised on a quid pro quo. What this fails to anticipate however, is altruistic actions driven by a higher purpose. People engage in self-sacrifice for the greater good. They can be motivated not out of any intrinsic personal benefit, but because they believe in something more.

Games and Citizen Science

FoldIt is computer game designed by University of Washington researchers that allows players to design protein structures by folding amino acids. Given the complexity of folding dozens, if not hundreds, of amino acids into viable protein structures, brute force computing power would not be a practical way of solving the problem with the current technology. Humans have an advantage in recognizing patterns and certain three-dimensional spatial intuitions that computers cannot currently simulate. What had stumped scientists for more than a decade, a retrovirus protease in rhesus monkeys, was solved by a worldwide consortium of players in ten days. The vast majority of these players had little biology or chemistry experience, relying only on the rules of the game as dictated by real physics. The discovery of the retroviral protease has been published in a scientific journal, naming a team of players, the FoldIt Contenders Group (FCG), as coauthors. In an interview with one of the FCG members, “mimi” preferred to be credited pseudonymously or anonymously. The main motivation for many of these players was advancement of science, not fame or recognition. They were not paid for their participation; many simply wanted a challenge and to work towards something big.

Video games, at their most fundamental level, are sets of puzzles. Why create arbitrary puzzles when real life puzzles exist with greater implications for their completion? FoldIt is only one of several other projects collectively grouped together as “citizen science.” These projects crowdsource because they benefit from certain human attributes that are not duplicable in computers currently. I have roughly divided them into three types of projects, though the distinctions are weak and mostly result of current computing capabilities. FoldIt fits in the group that requires certain human ingenuities that computers have not been able to simulate so far. This may include spatial reasoning, like in FoldIt. Some may benefit from human creativity, like creating RNA for nano functions in EteRNA. Others may rely on an eye for seeing patterns, like in comparing interspecies DNA in Phylo.

Another group of games are projects that require human interpretation of analog data streams. While human involvement may only be necessary now because of the limits of software or computing power, there are still uses for human interaction. This is the technological hurdle fueling CAPTCHA algorithms now. But as with CAPTCHA, eventually computers defeat them too. Ancient Lives is a project categorizing a trove of ancient Greek and Roman writings found in an Egypt. OldWeather sets players abroad ships and task them with digitalizing handwritten weather logs.

While the previous two categories are projects that can conceivably be accomplished completely by computers with improved software, the third category involves the physical world. These projects rely on players gathering data, rather than solving puzzles. They are different types of games, driven by collection rather than problem solving. After the Fukushima meltdown in Japan, a volunteer network of scientists and tech enthusiasts formed Safecast to track radiation levels in nearby areas. The group created jury-rigged Geiger counters and tasked residents of these areas with collecting data on radiation concentrations and distributions. The Global Amphibian Blitz has participants photograph frogs they encounter and upload their GPS locations. It has helped scientists track populations of amphibians for conservation and research purposes.

These projects all share one central trait—the participants, or players, are not paid for their work. In some cases they may receive credit, such as named as coauthors in publications or the opportunity to name discovered asteroids, but they receive no direct benefit. Whatever reason compels them to contribute, they are not driven by capitalistic models. Perhaps this is no different than volunteer models in the old economy, but the Information Goods Society has empowered the same efforts on much larger scales. Citizen science is driven more than volunteerism, it also leverages the human desire to solve puzzles. Maybe this model would not be compelling enough to uproot the traditional capitalism, even on the Internet, but by giving the tools to accomplish these goals to more people, there will be a larger volunteer pool.

I think this is a good first draft. You've identified some phenomena you want to write about, and you've understood them to be linked to other phenomena, of which they are illustrations.

What the next draft needs is an idea about these phenomena that you can explore with your readers, rather than presenting the illustrations at the heart of the essay. Your theoretical propositions in this draft are sketchy at best. They don't lead you to a thesis which can organize your reader's new acquaintance with the material you're discussing, as you can tell from your first paragraph, which indulges at first in mystification (no one actually ever thought communication was a one-way process, after all) and winds up in obviousness. Nor does it lead to a conclusion, as your last graf shows.

You've seen that there's an economy of peer production, but you haven't figured out what you want to say about it. The best place to start is with the wonderful piece Yochai Benkler wrote ten years ago, Coase's Penguin, or, Linux and the Nature of the Firm, where peer production in general and scientific peer production in particular is given a rigorous theoretical location. From where Yochai leaves matters you should be able to pick up in one of the obvious directions, generating a new idea or two of your own.

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r3 - 06 Nov 2011 - 16:03:37 - EbenMoglen
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