Papers

This project has been inspired by, influenced, and guided by a number of papers. They and their abstracts can be found below:

1. W. Wu and J. Lingel, "'I am Neuro, who are you?': Performances of authenticity in an experimental AI livestream," New media & society, Dec. 2025, doi: 10.1177/14614448251406904.
   • Authenticity is simultaneously part of the appeal and anxiety surrounding GenAI (generative artificial intelligence) technologies, which are often evaluated in terms of whether their speech and interactions can "pass" as authentically human. This study explores collective negotiations of authenticity in AI–human interaction by looking at AI virtual livestreams, focusing particularly on the performer Neuro-sama. Drawing on non-participant observation and textual analysis, we identify three key components in the performative evolution of authenticity: transparency, emotion, and potentiality. Our analysis offers a nuanced perspective on the relational and performative construction of authenticity, advancing discussions of how human–machine interactions reshape our understanding of a sociotechnical landscape increasingly reshaped by AI.
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2. O. D. Sanwoolu, “Kantian deontology for AI: alignment without moral agency,” Ai and ethics (Online), vol. 5, no. 5, pp. 5425–5437, Oct. 2025, doi: 10.1007/s43681-025-00784-8.
   • This paper explores the potential application of Kant’s moral philosophy to artificial intelligence (AI) and addresses two major objections. The first objection is that AI cannot fulfill Kant's standards for moral agency. I contend, however, that AI alignment with Kantian principles does not require moral agency in Kant's sense. I propose that the Categorical Imperative (CI) can serve as a useful framework for AI alignment, guiding the creation of maxims governing AI actions and testing their universalizability, particularly using the first principle of the CI which is the formula of the universal law (FUL). The second objection I address is the particularist critique to Kantian universalism, which is that Kantian universalism cannot tell us how to form maxims in a way that it allows sensitivity to context. I maintain that Kant’s framework can indeed accommodate context-sensitivity through practical judgment. But since AI are not the kinds of things to have practical judgment, I show that they have a functionally equivalent mechanism—transformer models—which can allow them form maxims that consider morally salient facts. Thus, supporting the claim that AI alignment is possible within a Kantian framework.
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