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data pipelines

Chris Gilliard Visits the Podcast: Digital Redlining, Tech Policy, and What it Really Means to Have Privacy Online

2021-04-06
By: Jane Rohrer
On: April 6, 2021
In: Chris Gilliard
Tagged: Big Data, data pipelines, digital privacy, Ed Tech, Education, Information Ecosystems, race, racism, surveillance

The history of surveillance in the United States is a long one. Our guest for the podcast on March 31, 2021, Dr. Chris Gillard, studies this very fact; Dr. Gillard’s scholarship focuses on digital privacy, institutional tech policy, surveillance capitalism, and digital redlining—a term that he defined on the podcast as “the creation and maintenance of tech practices, policies, pedagogies, and investment decisions that enforce class boundaries and discriminate against marginalized group.” As many of our Seminar guests have attested, too, access and relationships to contemporary digital technologies falls along racial, gendered, and classed lines, and the Internet—and the tools we use to access it—are made overwhelming by and for wealthy, straight white men in urban environments. And as Dr. Gilliard points out, access to the Internet is not the only thing historically minoritized groups are robbed of; these groups are also overwhelmingly stripped of their autonomy and privacy online. Although worries about CCTV and post-Patriot Act wiretapping seem especially twenty-first century, eminent scholars have recently illustrated how the very foundation of our nation, including its formation of racial and class differences, depended on the institution of surveillance. In her groundbreaking Dark Matters: On The Surveillance of Blackness, Simone Browne makes clear the connections between “the Panopticon, captivity, the slave ship, plantation slavery, racism, and the contemporary carceral practices of the U.S. prison system,” illustrating how contemporary surveillance technologies of all kinds have been formed and informed by the U.S.’s methods of policing and categorizing Black life under slavery (Browne pg. 43). This is evident all Read More

Data Pipelines, Data Fluidity: Colin Allen on the “Useful Fiction” of Curated Data

2020-02-28
By: Jane Rohrer
On: February 28, 2020
In: Colin Allen
Tagged: Big Data, Darwin, data pipelines, Topic modeling

Colin Allen, distinguished professor in the Department of History and Philosophy of Science at the University of Pittsburgh, is both an invited speaker and an ongoing participant in our Seminar; on February 28th, Dr. Allen talked with his fellow participants about his work in what he (and others) call “data pipelines.” Broadly speaking, using data pipelines means that data are collected and recorded in one of many particular ways—but eventually used for purposes other than why they were originally collected. And this means, Dr. Allen pointed out, that data are highly fluid, flexible, and even self-perpetuating. An especially potent example of this in Allen’s own work is his current role as Associate Editor of the Stanford Encyclopedia of Philosophy. While this project has one discreet start date back in 1995, it has been anything but static since then; as of March 2018, the site has approximately 1,600 entries each of which is routinely reviewed and updated. Each new post adds to what is now a highly dynamic reference work containing data culled from all over the web—a pipeline, indeed. Dr. Allen thoughtfully pointed out that as our relationship to data changes over our collective futures, it is important to remember that data does not enter into our world on its own but, rather, it is collected and curated. Allen co-authored an article, “Exploration and Exploitation of Victorian Science in Darwin’s Reading Notebooks,” with Jaimie Murdock and Simon DeDeo in 2017. Charles Darwin left careful records of the books he read from 1837 to 1860, making this Read More

Invited Speakers

  • Annette Vee
  • Bill Rankin
  • Chris Gilliard
  • Christopher Phillips
  • Colin Allen
  • Edouard Machery
  • Jo Guldi
  • Lara Putnam
  • Lyneise Williams
  • Mario Khreiche
  • Matthew Edney
  • Matthew Jones
  • Matthew Lincoln
  • Melissa Finucane
  • Richard Marciano
  • Sabina Leonelli
  • Safiya Noble
  • Sandra González-Bailón
  • Ted Underwood
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