It may come as a bit of a surprise that paper can play a crucial role in developing digital humanities projects. For me, one of the most powerful aha! moments at this year’s Digital Humanities Summer Institute came through a paper-prototyping exercise in our crowdsourcing class.
Before arriving in Victoria, my conception of crowdsourcing was limited to projects which asked the public to perform work that would normally take undergraduate and graduate assistants hundreds of hours to do. What I admired most about projects like Zooniverse’s Ancient Lives or UCL’s Transcribe Bentham were their ability to engage with a broader audience based on a common interest; by crowd-sourcing transcribing tasks, thousands of hand-written documents became more searchable, accessible, and readable in a relatively short amount of time.
This course challenged my assumptions about “the public” and what the crowd could—and should—be asked to do. By targeting an audience with a shared interest in our research materials, humanities projects often limit the scope of our audience to a relatively small proportion of people. In other words, Transcribe Bentham’s success is enviable, but not necessarily repeatable with smaller, more esoteric collections. Furthermore, relying on free or cheap labor to perform tasks that we would normally pay workers to do benefits projects with limited funding, but we should be conscious of the ethics of such a decision, especially in light of new regulations barring workers from outside the US from Mechanical Turk.
More importantly, humanists often approach crowdsourcing projects with a limited understanding of what they can do. Our instructor, Edith Law, encouraged us to think of crowdsourcing as a means to generate new data rather than as a vehicle for enriching previously-existing collections. She reminded us of fundamental differences in the ways that disciplines approach research. Computer scientists tend to use crowdsourcing to gather data as a way of answering a research question; humanists typically use research to problematize previous answers.
Breaking out of this data-enrichment mindset was challenging at first. As we looked at examples of successful citizen-science games like Stupid Robot, I realized that it would be hard to pitch tasks like adding metadata and transcribing to a broader audience as…well…fun.
Paper prototypes not only gave an abstract idea shape and direction, but it also facilitated collaboration. With Edith Law’s help, Karen Bourrier, Joanna Schmidt, and I began to develop a transcription game. Moving from an abstract concept into a play-able prototype required us to think about content, design, and game mechanics simultaneously. Because paper prototypes are not bounded by the limits of my patchy coding vocabulary, this exercise gave my creativity free reign. Transitioning from a paper to a digital prototype was much smoother (and much less intimidating) because we had a very clear sense of the final product.
Our hope is that future iterations game balance enriching pre-existing archives with generating new data. Early versions of the game will be used to test designs which use information-gap theory to engage gamer’s curiosity. This information could be extended to a number of citizen-science and humanities games to create win-win situations for users and researchers. More broadly, designing a crowdsourcing project gently reminds us humanists that there is a broader public by encouraging us to focus on the user. Unlike many traditional formats through which we express our research, digital humanities projects require us to be highly conscious of visual design and layout.