RHE 309K: Rhetoric of Human Computation
fall 2017 — Spring 2018
At the nexus of human talent and technological advancement lies human computation (HC): the practice of using the processing power of people to solve problems and/or analyze data that computers cannot (yet) solve/analyze and, importantly, vice versa. This promising, problematic union of man and machine is certainly not a new phenomenon—the prosthetic extension of human ability via technology is at least as old as the wheel, the stylus, or the sundial. What is novel, however, is the massive scale on which these extensions are taking place in the 21st century. A number of key figures and HC projects are covered, from within academic research circles and without.
I designed "Rhetoric of Human Computation" to offer students a more nuanced understanding of this emerging field and some of the central claims made by its champions and critics, alike. Course readings provide a variety of viewpoints and foster critical thinking about the rhetorical moves made by different texts (including multimodal and born-digital texts). Arguments for and against distinct disciplinary approaches to human computation are be analyzed for their bias/credibility, intended audience(s), underlying assumptions, and appeals to the classical triad of ethos/pathos/logos. Ultimately, this course asks students to analyze and author arguments about human computation, but also to consider the underlying rhetoricity of human-computer interaction and cooperation.
- Project 1: Annotated Bibliography and Research Roadmap (10%)
- Project 2.1: Rhetorical Analysis Paper (10%)
- Project 2.2: Rhetorical Analysis Paper Revision (15%)
- Project 3.1: Argument Proposal Paper (10%)
- Project 3.2 Argument Proposal Paper Revision (15%)
- Project 4: Capstone: Creative or Computational (10%)
Shorter Assignments: Research Summaries 1-4 (15%)
Participation: In-Class, Canvas LMS, and Quizzes (15%)
Instructor Conferences: Prior to Projects 1 & 4 (Mandatory)
Peer Reviews: For Projects 2 & 3 (Mandatory)
Readings on rhetoric, reading, and writing:
- Graff, Gerald, and Cathy Birkenstein. They Say/I Say: The Moves that Matter in Academic Writing. 3rd Edition. New York: W. W. Norton & Company Inc., 2014.
- They Say I Say Twitter Bot. Maintained by @rooksbay, bot script written by @zachwhalen (2015).
- Gottfried, Jeffrey, and Elisa Shearer. “News Use Across Social Media Platforms 2016.” Pew Research Center. May 26, 2016.
- Jack, Caroline. “Lexicon of Lies: Terms for Problematic Information.” Datasociety.com. August 9, 2017.
- Bullock, Richard, Michal Brody, and Francine Weinberg. The Little Longhorn Handbook. 2nd Edition. New York: W. W. Norton & Company Inc., 2014.
Readings on human computation (selections attuned to a given semester's areas of interest are provided to students on Canvas):
- Bogost, Ian. "Gamification Is Bullshit." Bogost.com Blog Post, 2011. *Rhetorical analysis of article, forums, and comment spaces.
Estellés-Arolas, E., and F. González-Ladrón-de-Guevara. "Towards an Integrated Crowdsourcing Definition." Journal of Information Science 38 (2012): 189-200.
Ettlinger, Nancy. "The governance of crowdsourcing: Rationalities of the new exploitation." Environment and Planning 48.11 (2016): 2162-2180.
Feng, Jiashi, et al. "Purposive Hidden-Object-Game: Embedding Human Computation in Popular Game." IEEE Transactions on Multimedia vol. 14, no. 5 (2012).
Fuller, M. Evil Media. Cambridge: MIT Press, 2012.
Kaganer, Evgeny, et al. Managing the Human Cloud. Cambridge: MIT Press, 2013.
Marcus, Adam Marcus and Aditya Parameswaran. Crowdsourced Data Management: Industry and Academic Perspectives, "Human Computer Interaction," "Machine Learning and Artificial Intelligence," "Social Science," "Game Theory," and "Systems and Programming Models" (2015).