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Full-Text Articles in Science and Technology Studies
Human Supremacy As Posthuman Risk, Daniel Estrada
Human Supremacy As Posthuman Risk, Daniel Estrada
The Journal of Sociotechnical Critique
Human supremacy is the widely held view that human interests ought to be privileged over other interests as a matter of ethics and public policy. Posthumanism is the historical situation characterized by a critical reevaluation of anthropocentrist theory and practice. This paper draws on animal studies, critical posthumanism, and the critique of ideal theory in Charles Mills and Serene Khader to address the appeal to human supremacist rhetoric in AI ethics and policy discussions, particularly in the work of Joanna Bryson. This analysis identifies a specific risk posed by human supremacist policy in a posthuman context, namely the classification of …
The Affective Politics Of Twitter, Johnathan C. Flowers
The Affective Politics Of Twitter, Johnathan C. Flowers
Computer Ethics - Philosophical Enquiry (CEPE) Proceedings
Given the increasing encroachment of Twitter into offline experience, it has become necessary to look beyond the formation of identity in online spaces to the ways in which identities surface through the formation of affective communities organized through the use of technocultural assemblages, or the platforms, algorithms, and digital networks through which affect circulates in an online space. This essay focuses on the microblogging website Twitter as one such technocultural assemblage whose hashtag functionality allows for the circulation of affect among bodies which “surface” within the affective communities organized on Twitter through their alignment with and orientation by hashtags which …
Rethinking Algorithmic Bias Through Phenomenology And Pragmatism, Johnathan C. Flowers
Rethinking Algorithmic Bias Through Phenomenology And Pragmatism, Johnathan C. Flowers
Computer Ethics - Philosophical Enquiry (CEPE) Proceedings
In 2017, Amazon discontinued an attempt at developing a hiring algorithm which would enable the company to streamline its hiring processes due to apparent gender discrimination. Specifically, the algorithm, trained on over a decade’s worth of resumes submitted to Amazon, learned to penalize applications that contained references to women, that indicated graduation from all women’s colleges, or otherwise indicated that an applicant was not male. Amazon’s algorithm took up the history of Amazon’s applicant pool and integrated it into its present “problematic situation,” for the purposes of future action. Consequently, Amazon declared the project a failure: even after attempting to …