Political Theory

H14(b) - The Digital Age

Date: Jun 3 | Time: 03:30pm to 05:00pm | Location:

Chair/Président/Présidente : Schuyler Playford (University of Toronto)

Discussant/Commentateur/Commentatrice : Greg Dinsmore (Université de l'Ontario français)

Re-imagining Elemental Politics: Fire, Artificial Intelligence and (Non)Human Politics: Micheal Ziegler (Western University)
Abstract: Western politics is reactive and unimaginative, as seen in our approaches to fire management. This reactive simplicity is incidentally linked to unimaginative Artificial Intelligence (AI) research and development. AI researchers are obsessed with a singular vision of intelligence, i.e., human intelligence. This simplicity ignores non-Western, nonhuman and Indigenous forms of intelligence. My paper celebrates creative and imaginative research practices through land-based, elemental knowledge creation by accepting intelligence as relational and existing in all things: e.g., wind, soil, water and, and important for this paper, fire. The paper is inspired from an intelligent pit fire (a traditional clay firing technique) project I am a lead researcher on. The project re-imagines intelligent action by acknowledging fire as an actant—a nonhuman transformative political thing. In the paper, I build on Jane Bennett’s limited idea of non-material actants. That is, I refuse her idea that only a child’s mind can see non-material actants because that approach infantilizes Indigenous orientations wherein all ages can see it. My approach allows me to re-imagine (non)human politics to better understand unpredictable forces that are indifferent to human wills. I bracket (non)human to reform categorical framings of being human. Primarily, it serves as an expression to illustrate how the human/nonhuman dichotomy is misleading and thus limiting political potential. That is, thinking in line with critical theorists like Arthur Kroker and Brian Burkhart, the borders between human and nonhuman worlds are not demarcated. Ultimately, I argue how an elemental imaginary politics is proactive because of its transformative ontological disposition.

“Only Fake Words” — Revisiting Catharine MacKinnon in the Age of Deepfake Pornography: Tina Yong (University of Toronto)
Abstract: Over 95% of deepfakes contain non-consensual pornographic depictions of women. Free speech jurisprudence has lent credence to an emerging legal argument that deepfakes are immune from prohibition, on the grounds that they qualify as protected speech. In this paper, I revive Catharine MacKinnon’s argument in Only Words (1993) that pornography should not be protected as speech because it constitutes gender inequality — to demonstrate why her work holds renewed salience in the deepfake age. I advance three distinct claims: firstly, conventional pornography and deepfakes are contiguous in their shared endorsement of sexual coercion. Secondly, deepfake pornography falsely constructs and silences women, which warrants its formal designation as discrimination rather than as constitutionally protected speech. Thirdly, drawing upon G.W.F. Hegel’s master-slave dialectic, I illustrate how fully synthetic pornography could constrain women’s sexual freedom in ways unforeseen by MacKinnon’s work, in part due to her myopic focus on the material harm of pornographic production and comparative inattention to how porn structures one’s sense of “self” and “other.” Taken together, I aim to answer the following question: What did MacKinnon get right about pornography, and how can we extend her account to more accurately diagnose novel dangers in the dawning age of artifice?

Assessing the Threat of Generative AI to Democracy: Simon Lambek (University of the Fraser Valley)
Abstract: This paper considers the effects of generative artificial intelligence (AI) on democracy, both as a mechanism for constructing and executing public policy and as a broader societal phenomenon. Specifically, the paper canvases six potential threats generative AI poses to democracy. I argue that AI threatens to: 1) diminish innovation, creativity, and evaluative capacities in citizens and institutions; 2) foster docile citizenship and produce democratic despotism; 3) undermine the broadcasting of diverse perspectives and the possibility of what Hannah Arendt calls the “common world”; 4) perpetuate inequality and systemic oppression in ways both explicit and implicit; 5) produce and sustain misinformation; and, finally, 6) disconnect laws, policies, or regulations from justificatory practices. Articulating and assessing these threats clarifies more precisely how generative AI jeopardizes society’s capacity to meet basic democratic functions such as empowered inclusion, collective agendas, and collective decision making.

Unveiling Political Dynamics in Crisis Narratives: A Computational Literary Analysis: Mahdi Baratalipour (University of Toronto), Emily C. Nacol (University of Toronto)
Abstract: In an era of escalating crises—from pandemics to societal collapse—literature serves as a mirror to the political fault lines of power, resistance, and human resilience, offering rich qualitative insights that computational approaches can further quantify and systematize. This study brings together the interpretive methods of political theory with those of computational analysis to examine political dynamics—resistance, agency, political power, social structures, and temporal disruptions—in six crisis novels: Blindness, The Plague, Severance, The Road, Never Let Me Go, and The Handmaid’s Tale. It addresses sentiment-theme links (RQ1), theme variations (RQ2), and clustering (RQ3). Employing sentence-level DistilBERT sentiment analysis, embedding-based theme tagging (SentenceTransformer), LDA topic modeling, cosine similarity, and clustering, emotional trajectories and thematic prominence are quantified to bridge quantitative patterns with qualitative interpretations. Results show negative sentiment dominance tied to themes (RQ1), method-dependent prominence like high resistance in Blindness and The Plague and power in Never Let Me Go (RQ2), and two clusters: resistance-centered (The Plague, The Handmaid’s Tale) and power/disruption (The Road, Blindness), with hybrids (Severance, Never Let Me Go) (RQ3). This mixed-methods integration yields testable hypotheses that encourage close reading, revealing how crisis narratives shape political imaginaries and affective responses for mobilization research. Keywords: Crisis narratives, Political dynamics, Sentiment analysis, Topic modeling, Cosine similarity, Clustering, Computational methods, Political themes, Emotional impacts.