A few months ago, Cathy N. Davidson wrote a blog post on HASTAC in which she argues that all schoolchildren should be taught computer programming in order to achieve a “basic computational literacy.” She laments the lack of demographic diversity in programmers and wonders “What could our world look like if it were being designed by a more egalitarian, publicly educated cadre of citizens, whose literacies were a right not a privilege mastered in expensive higher education, at the end of a process that tends to weed out those of lower income?”
USC Phd student Alex Leavitt followed her proposal by inviting other academics to make 2012 their “Year of Code.” Numerous people across the twitterverse are also participating in Codeacademy.com‘s #codeyear.
Davidson and Leavitt’s calls to code, both of which espouse a leftist politics of democratic or Do It Yourself coding, make me reflect on the different values that are currently competing in the software programming and academic spheres; proprietary models v. open access/open source models. In particular, the academic debate about open access to academic knowledge recently reared its head in Congress, when in December of 2011 the Research Works Act, an act that would block mandates of public access to federally-funded research, was introduced to the House of Representatives. This act is likely a response to recent moves on the part of the Obama administration toward better access to scientific publications (see the America COMPETES Reauthorization Act of 2010 and the subsequent Request for Information on Public Access to Digital Data and Scientific Publications). While the Research Works Act will probably not pass, it speaks to the conflict inside and outside academia between privileging information and disseminating information, between profit and public interest.
What, one might wonder, might code coming from within the academy, produced, as Davidson envisions, by an educated public, look like? And, in terms of student grades or professional tenure, how would it be evaluated?
It is an interesting exercise to compare Google and Facebook with academia. Google and Facebook are widely successful because they are a contradiction–they are free to the public and friendly to the non-expert, yet their code is secret and they make money from said public through ads. They are open but closed, profit-making but free. American academia, on the other hand, makes its “secrets” available, but only to those who pay large amounts of money and who strive to become experts.
Traditional academic tenure and evaluation is alien to the kind of collaborative (and proprietary) code farming that Google encourages. How could a tenure committee evaluate one coder out of a team of hundreds? Even with a trail of changes made by each individual, it would be almost impossible to separate that person’s work from that of others. Of course, not all coding is done collaboratively, but I would argue that most large scale projects with major impact are. As more examples of academic coding emerge, the tenure process will hopefully adjust to accommodate new modes of authorship in the digital age.
One high-profile academic seems frightened at the prospect of academia’s descent into the digital. Stanley Fish calls “‘blog'” “an ugly word” for its impermanence. As someone who wants his critical insights to be “decisive” and “all [his],” Fish dislikes thinking of himself as a blogger–a figure who seems so interconnected with everything around him that he ceases to exist. Fish is disturbed by this possible loss of identity and “linearity,” by the web’s tendency to move “into a multi-directional experience in which voices (and images) enter, interact and proliferate in ways that decenter the authority of the author who becomes just another participant.” Poor Stanley Fish experiences this every time he opens his browser.
Fish goes on to quote Kathleen Fitzpatrick as affirming this death of the author: “all of the texts published in a network environment will become multi-author by virtue of their interpenetration with the writings of others.”
I would argue that coding and other digital forms of authorship do often invoke this sense of the networked self to an even greater extent than traditional scholarship. In part that is probably because online social networks allow scholars to continually mix and concentrate their ideas with the ideas of others. Seeing one’s own voice as just one tweet in a tsunami of tweets can be a bit humbling. But then again, when people band together and find like ground, their accomplishments can be even grander than what one can do alone. There is a happy medium that can be found between solo pursuits and selfless proprietary software. I am optimistic to note that a vast amount of software developed through academic institutions is open access and open source, including as Sakai, Weka, and Stanford NLP software.