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Friday, May 29 • 9:00am - 10:15am
Machine Data, Human Scale

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In his seminal book, A Critical Theory of Technology (1991, Oxford UP), Andrew Feenberg argued that a person’s interactions with a computer and best viewed not as occurring between a human and a machine, but rather as an interaction between a human user and a human programmer (107). Nearly a quarter century later, we are well advised to recall and revisit this approach, as digital humanists explore the implications of the software, the firmware, and the hardware used to conduct our work.

Accordingly, this structured conversation will center on the ideology inherent in programming choices and the concomitant implications for research and scholarship in the humanities by asking questions such as, what onus is upon humanists to shape the tools for scholarly use? In what ways do the tools, filters, and practices color humanistic analysis, invention, and engagement with digital scholarship? How vigilant should and must we remain about investigating the provenance of the media platforms we use for research?
By approaching the topic from multiple perspectives, we seek to open up the conversation in provocative ways.

Justin Hodgson will focus on the ways in which scalability and tolerance function as both conceptual apparatuses and as algorithmic filters. In the realm of digital tools, these entities come to shape how we encounter and/or visualize data, how we articulate our manipulations and/or representations of data, and how we go about augmenting, exchanging, and/or constructing data for analytical and inventive purposes. As such, at their core these technical affordances of algorithmic engagement are rhetorical, and understanding them as rhetorical has significant implications for digital humanists doing digital things with digital tools.

Michael Simeone will explore decision science. It is well established that modeling complex systems can be beneficial for scientists, policy makers, engineers, and citizens alike. Domains such as health care and ecology, with objects of study consisting of multiple interdependent systems that encompass data from numerous sensors, databases, and subjects, benefit from considering a prediction as a compound calculation that stretches broadly for input. How do we responsibly model humanistic insights for the purposes of predictive modeling? In the event that mathematically modeling humanistic analysis and evidentiary procedures is unacceptable, how do we present and use a historical or cultural analysis alongside statistics in a multi-display environment that does more than simple juxtaposition, where layout is not a substitute for integrative analysis?

Virginia Kuhn will consider possibilities for supporting information representation and data analysis through the combined use of multiple perceptual modalities such as sight, touch and kinesthetics. How might novel visualization techniques, paired with touch-based and gesture-based interfaces helped to spread the cognitive load required to deal with the massive amounts of data we face in contemporary life? How might this approach support grounded cognition and aid real time decision-making? Finally, what sort of research methods would this approach make possible?

avatar for Justin Hodgson

Justin Hodgson

Assistant Professor, Indiana University
Digital Rhetoric, New Aestheticism, Digital Dissertations, Rhetorical Invention, The Journal for Undergraduate Multimedia Projects
avatar for Virginia Kuhn

Virginia Kuhn

Faculty, School of Cinematic Arts, University of Southern California, United States of America

Michael Simeone

Directory, Data Science and Analytics, ASU Library

Friday May 29, 2015 9:00am - 10:15am EDT
Room 105 Kellogg Center

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