Congratulations to our newest PhD graduate, Dr. Kem-Laurin Lubin, who successfully defended her dissertation, "Ethotic Heuristics in Artificial Intelligence: A Rhetorical Framework for Guiding Responsible Data Design Praxis in Healthcare and Surveillance." The dissertation supervisors were Dr. Randy Harris and Dr. Lai-Tze Fan, and the readers were Dr. Marcel O'Gorman and Dr. Danielle Deveau. The external examiner was Dr. Robert Gehl, and the internal/external examiner was Dr. Kim Nguyen. The defence was chaired by Dr. Yingli Qin.
Abstract
This thesis investigates the convergence of artificial intelligence (AI), human-centered design, and rhetoric across three interconnected essays.
This dissertation centers on design heuristics as its primary analytic and unifying framework, drawing from traditions such as Data Feminism and rhetorical inquiry. It explores three interrelated domains: (1) AI-driven human-computer interaction (HCI) design; (2) the implications of AI-powered design for women’s health privacy, particularly in the post-Roe v. Wade U.S. context; and (3) critical discourse surrounding AI in surveillance technologies. Using a multi-method approach—including rhetorical analysis, Critical Discourse Analysis (CDA), case studies, and stakeholder perspectives—this research interrogates how AI systems construct algorithmic ethopoeic representations that commodify user data.
The first essay introduces practical heuristics for HCI designers by integrating Design Thinking principles, thereby promoting ethical dialogues and enhancing human-centered approaches amid rapid AI advancements. The second essay uses rhetorical analysis to explore the construction of algorithmic ethopoeia in sensitive areas, emphasizing the need for robust protections around personal data integrity. This section, grounded in Data Feminism, empowers designers, activists, and policymakers to advocate for more secure and transparent AI applications, particularly in the domain of women’s health privacy. The final essay employs CDA[1] to critique the discourse surrounding AI-driven surveillance, focusing on predictive policing and facial recognition technologies. Through the analysis of competing narratives and stakeholder perspectives, it reveals ethical dilemmas related to systemic biases and authoritarian practices, ultimately arguing for rigorous oversight and regulatory frameworks. Surveillance contextual heuristics are proposed to guide the responsible deployment of AI in public safety while safeguarding civil liberties.
Collectively, these investigations underscore the imperative for ethical, context-sensitive, and rigorously informed design heuristics to guide the responsible integration of AI across diverse domains. They advance the discourse on user privacy, regulatory compliance, and human-centered innovation, while simultaneously promoting the development of design practices that are both ethically sound and equitable.
[1] Critical Discourse Analysis (CDA) is a qualitative research approach examining how language, power, and ideology interact in social practices. For foundational discussions of CDA, see Fairclough (1989) Language and Power and Wodak & Meyer (2009) Methods of Critical Discourse Analysis.