Richard Aubrey Slaughter

Richard Aubrey Slaughter is currently a doctoral candidate in the Informatics department at the Donald Bren School of Information and Computer Science at the University of California, Irvine. His MA in Social Science was conducted at the University of Chicago, and his BA in Anthropology at the University of Texas, Austin. He is a recipient of the 2016 DTEI Pedagogical Fellowship, and has received funding from the National Science Foundation for the studies of sameness in scientific sampling. Publication of his latest work is forthcoming in the 2021 Routledge Handbook of Digital Media and Communication. Principally concerned with the intersection between the seen and the unseen in human/infrastructural relations, he specializes in examining non-standard uses of informational technology, such as automated blackmail, ad hoc hacktivism, and magical infrastructures.

The latest advances in cognitive computation are a move inexorably towards a shamanism of the machine, a magical phenomenology based on fanciful but effective latent structures that we lack either the capacity or the sensorium to interrogate.

Bridging concerns from human-computer interaction (HCI) and media studies, this essay theorizes deepfake images in terms of their phenomenological implications: the extent to which they enfold the human viewer in a world of the otherwise unseen. Drawing on comparative phenomenology of Vilém Flusser and Louis Bec, we focus on variational autoencoders (VAEs). We contend that the processes underlying deepfake image construction, as much as deepfake images themselves, evidence a parallel, prosthetic, and computational phenomenology: a study of “that which appears” to a computer, and which appears secondarily to a user-human as image. We use the example of VAEs to argue for the emergence of a second-order, received phenomenology of the augmented human as we reside in an increasingly computational world. 

Contributors

sign up

and get the latest news and calls for papers & projects

Open Access! We have decided to give you full access to all our content until 15th of January 2022!  (support us by subscribing)

Our site uses cookies to improve our services. As an user you need to agree to the usage and accept our conditions. We are currently using only necessary cookies for normal web page functioning. For more information visit our Privacy Policy and Terms of Service. For more information on the cookies that we use please check the list below.  

PHPSESSID
This cookie is native to PHP applications. The cookie is used to store and identify a users’ unique session ID for the purpose of managing user session on the website. The cookie is a session cookies and is deleted when all the browser windows are closed.

I consent to the cookie usage, agree with the Terms of Service and Privacy Policy and want to continue using the web-page.