Curating a MediaCommons Collection on Algorithms

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MediaCommons website screen capture: November 24, 2015

I was flattered a few months ago to be asked to develop a MediaCommons Field Guide survey on the general topic of algorithms. In consultation with (and following the sage advice of) the MediaCommons editorial team, I formulated the following question to be addressed by respondents:

What opportunities are available to influence the way algorithms are programmed, written, executed, and trusted?

This survey question seeks to explore ways that digital humanities pedagogy and praxis might influence, produce, direct, or capitalize on the automated activities of algorithms. As algorithms seek to more intelligently predict what we might like using profile data mined from our archived and ongoing online activities, how might our access to ideas and experiences may be limited or expanded by the predictive power of self-learning algorithm-based decisions? Will our access to and ability to explore the vast range of opportunities available to us be enhanced, or will the predictive authority of algorithms reshape the landscape and horizons of our existence? Might the predictions algorithms make prove so accurate that we have little need to see or experience beyond the horizons shaped by algorithms? Contrastingly, are there positive implications for the ways in which algorithms shape our various digital experiences? The question encompasses composing or running an algorithm along with the results of algorithmic activity.

Responses may explore any aspect of the question; some possible approaches include:

  • The role(s) of algorithms in the digital humanities
  • Ways algorithms are involved in communication
  • (Dis)connections between artificial and human intelligences
  • Coding ethical algorithms
  • Influences of algorithms on humanistic pursuits
  • Computer games as algorithmic praxis
  • “Hidden” and/or “visible” algorithms that influence human activity
  • Algorithms, surveillance, and privacy
  • Government and corporate interest/investment in algorithms
  • Big data, data analysis, algorithms and humanities research

I reached out to a wide range of colleagues, friends, acquaintances, and heroes of scholarship I’ve encountered in my doctoral studies and asked for 600± word responses to this question.

The response and results are exceeding my wildest expectations. Responses to my email requests for contributions were greeted with warmth and encouragement. Those who were unable to contribute made their apologies with grace and recommended other scholars I might consider contacting to request contributions. I followed up with those scholars, too, who turned out to be as warm and receptive as the first round of respondents; several of them, in turn, contributed to the project. The experience of requesting contributions has been pleasant, as has the process of collecting those contributions and getting them posted.

I’m currently in the process of curating the collection of contributions, encouraging conversations and engaging other scholars in the dialogue that’s emerging around these posts. You can join the conversation at MediaCommons. I’m taking this opportunity to share with you what’s out there and to encourage you to join the conversation. More posts are coming after the Thanksgiving holiday, when I’ll add a post to include them.

  1. Curator’s Introduction: Organisms in a World of Algorithms — Daniel Hocutt, University of Richmond & Old Dominion University
  2. Algorithms and Rhetorical Agency — Chris Ingraham, North Carolina State University
  3. The Essential Context: Theorizing the Coming Out Narrative as a Set of (Big) Data — Marc Ouellette, Old Dominion University
  4. Algorithmic Discrimination in Online Spaces — Estee Beck, UT-Arlington
  5. Toward Ambient Algorithms — Sean Contrey, Syracuse University
  6. How Will Near Future Writing Technologies Influence Teaching and Learning in Writing? — Bill Hart-Davidson, Michigan State University
  7. algorithms at the seam: machines reading humans +/- — Carl Whithaus, UC Davis
  8. How Are We Tracked Once We Press Play? Algorithmic Data Mining in Casual Video Games — Stephanie Vie, University of Central Florida
  9. Crowdsourcing Out the Sophistic Algorithms: An Ancient View — Walt Stevenson, University of Richmond

If you’re interested in the way algorithms are being used across a variety of fields, disciplines, industries, and situations, you will find something interesting among the posts in this collection. These contributions are intended to generate conversation — I hope you’ll read one or more and join the conversation. I can attest that the scholars whose contributions you’ll be reading are approachable and more than willing to enter into dialogue.

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