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Anna Hoffman will be interviewing for a faculty position March 2 & 3. Students are encouraged to attend the informal student meeting and are also welcome to attend the job talk (details below).
Anna Lauren Hoffmann is a postdoctoral scholar with the School of Information at the University of California, Berkeley. Her research centers on issues in data, technology, and ethics, with particular attention to how the design and use of information technology can promote or hinder important human values like respect and justice. Her work has appeared in various scholarly journals, including New Media & Society, Library Quarterly, and the Journal of the American Society for Information Science and Technology, as well as popular outlets like The Guardian, Slate, and the Los Angeles Review of Books. You can learn more at annaeveryday.com.
Join us for a special presentation by Dr. Anna Hoffmann, “Data Violence–Dignity, Discrimination, and Algorithmic Identity,” on Thursday, March 2, at 3:30 p.m. in Manning Hall 01.
Today, our “data doubles” – algorithmically-generated, computation-friendly versions of our identities produced by and through digital data – present new challenges for social justice. Among these challenges is the problem of promoting dignity and self-respect, values that provide individuals and groups with a sense that their identities and experiences are valuable and their goals are worth pursuing. For vulnerable or marginalized populations, dignity and self-respect can be undermined by violent actions, symbols, or cultural ideas promoted through mass media, law and policy, or increasingly the design of data-intensive systems that seek to sort, evaluate, and rank people according to opaque or biased criteria.
In this talk, I position “data doubles” as sites of potential violence–especially when they conflict with our own moral self-perceptions, ideas, and beliefs in ways that implicate our dignity. Through an examination of 1) historical human rights abuses perpetrated through population data, 2) current critical discussions of surveillance, algorithms, and data ethics, and 3) the experiences of transgender women navigating systems that fail to account for their particular identities and bodies, I show how institutionalized and other biases work in and through data-driven systems to deprive certain people of what philosopher John Rawls called “the social bases of self-respect.”
