Changing our default settings – part 4: Unpaid digital labour

Put simply, data and the consumption of data are not just a new natural resource – they are the key commodity in today’s knowledge-based economy. (Hofheinz and Mandel 2015)

Students as unpaid digital labourers

So far in this series of posts, I’ve tried to argue that the data produced by students as they interact with our educational institutions are ‘commodities in today’s knowledge-based economy’. Or, as Trebor Scholz and Laura Y. Liu have put it, “Our digital footprint becomes somebody else’s business” (2010, p. 12).

For Karl Marx, the notion of a commodity was so significant that he began his monumental work Capital with an analysis of it. Marx (1859) states that commodities are “the result of expended human energy” or labour. By extension, the production of a ‘digital commodity’ such as data could be called ‘digital labour’.

One prominent educational technology company which profits from the digital labour of students is TurnItIn. According to Introna (2015), who has written of “the algorithmic governance of academic writing on an unprecedented scale”, TurnItIn “is embedded in the educational practices of 3500 higher education (HE) institutions globally.”

To be more precise, students pay educational institutions (or, in many cases, the government does), who then pay TurnItIn for the ability to upload student papers (123,000 per day in 2013, according to Introna) which then contribute to the economic value of the service offered by TurnItIn. In other words, then, TurnItIn profits in two different ways, neither of which are transparent to the student responsible for the intellectual property necessary for this exchange. In this context, “academic writing is an important commodity” (Introna 2015).

To add another couple of layers to the ethical mess:

Students often do not have the ability to opt out of this wealth transfer if they prefer not to participate.
Not only are students not paid for this digital labour, they themselves in fact have to pay for the dubious privilege of having their work scrutinised by a third party for-profit organisation.

Worse still, the service itself is of highly questionable value. In 2007, Susan E. Schorn tested the effectiveness of ‘plagiarism-detection software’, including TurnItIn.

For the 2007 test, Schorn created six essays that copied and pasted text from 23 sources, which were chosen after asking librarians and faculty members to give examples of commonly cited works. Examples included textbooks and syllabi, as well as websites such as Wikipedia and free essay repositories.

Of the 23 sources, used in ways that faculty members would consider inappropriate in an assignment, Turnitin identified only eight, but produced six other matches that found some text, nonoriginal sources, or unviewable content. That means the software missed almost two-fifths, or 39 percent, of the plagiarized sources.

In fact, it was found to be less effective than using Google. In my own experience, I’ve found that DuckDuckGo is also more use than TurnItIn. And it’s free. And it doesn’t track me.

In his article on the topic from July this year, Carl Strausheim quotes Schorn as saying:

The real ethical question is how you can sell a product that doesn’t work to a business — the sector of higher education — that is really strapped for cash right now…We’re paying instructors less, we’re having larger class sizes, but we’re able to find money for this policing tool that doesn’t actually work. It’s just another measure of false security, like having people take off their shoes at the airport.

Another 2013 report concluded that the

largest problem is that Turnitin stores the papers on US servers, if the user does not manage to find and turn off this function. Universities must be clear as to whether the non-disclosure agreements that they may have agreed to permits the theses to be uploaded to the companies servers. They would also be advised to obtain the explicit permission from the students for using their papers in this manner.

Teachers as unpaid – and gradually deskilled – digital labourers

In April 2015, it was announced that TurnItIn had acquired a company called LightSide Labs and its Scoring Engine. According to 25-year-old Elijah Mayfield, ‘vice president of new technologies’ at TurnItIn and formerly CEO of LightSide, the “current process for mass assessment of student writing is appalling” (quoted in the article I just linked to). In response to this ‘appalling’ situation, Mayfield thinks his Scoring Engine will “let instructors focus more on helping students learn to write and focus less on preparing for tests and grading test essays.”

What this kind of enthusiastic rhetoric obscures, however, is the unpaid digital labour required to make the Scoring Engine work.

This screenshot indicates what’s actually going on behind Scoring Engine. First, students upload their papers to TurnItIn and teachers grade them and provide feedback through the Scoring Engine. Then, the Engine’s algorithms go to work to analyze “the lexical, syntactic, and stylistic features of writing, such as word choice and genre conventions, unlike other automated essay scoring programs that rely on simple metrics like word count” and, in doing so, “discovers the unique, content-based patterns in an existing set of hand-scored essays and learns to replicate that judgment as an accurate, reliable, on-demand assessment of student writing.” It can then “accurately score an unlimited number of new essays quickly and reliably.”

Finally, once the algorithms have ‘learnt’ how to grade the papers to a level that Mayfield and his colleagues can live with, the work is automated and teachers are no longer needed. This process is referred to as ‘deskilling’: “the reduction of the scope of an individual’s work to one, or a few, specialized tasks”, partly as a consequence of technological development (Sociology Index). So, as teachers deskill themselves through the use of the Scoring Engine, they are simultaneously increasing the exchange value of the Engine in terms of what TurnItIn can charge the institutions interested in ‘quickly and accurately scoring an unlimited number of essays’.

And who, ultimately, stands to gain the most? Unquestionably, that would be TurnItIn and its private equity firm and sovereign wealth fund owners who are, presumably, keen to see some return on their $752 million investment. The benefits for students and educators are minor by any measure, but they are minuscule in comparison to the benefits for TurnItIn.

In summary:

it could be argued that the increased use of digital technology in education serves mainly to increase the ability of dominant powerful groups to control the actions of others. This control is achieved primarily by influencing, shaping or even determining expectations of what is possible and what is preferable. (Selwyn 2014)