[Un]Ethical Algorithms: The Social Justice Dilemma of Automated Writing Technologies

Abstract

This dissertation examines the use of AI-based technologies in providing legal assistance to resource-constrained populations and its potential impact on social justice. Using a mix of qualitative and quantitative methods including usability testing, interviews, surveys, and participant-generated image session, I explore how the rhetorical and computational design of the Legal Navigator wesbite (Note: Throughout the rest of this dissertation, “the Legal Navigator website” will be referred to simply as “Legal Navigator.”) affects the agency, access to justice, and problem-solving abilities of resource-constrained users. Informed by scholarship in digital rhetoric and social justice, I analyze how algorithmic systems like Legal Navigator computationally and rhetorically influence users’ perceptions, values, and actions in the legal domain. The findings highlight the shared, co-constitutive agency emerging from the interactions between human and nonhuman actors in the digital network, illustrating how the algorithmic and interface design, as well as the broader spectrum of human factors such as literacy levels, digital skills, and personal preferences influence the overall rhetorical efficacy and user experience of such algorithmic systems. By integrating these findings and collaborating with the web development team of Legal Navigator, I propose the CARE Model, a comprehensive framework for enhancing the accessibility and effectiveness of AI-driven legal support services through user-collaborative design (Co-creation), diverse outreach efforts (Advertising), community resource mobilization (Resources), and pathways for professional legal consultations (Expertise). Ultimately, this dissertation seeks to contribute to the growing body of literature on digital rhetoric and social justice studies in writing studies, rhetoric, and technical communication, advocating for the critical role of our field in shaping the ethical development and deployment of AI technologies to empower historically underserved communities.