Potential Abstract: This research article investigates the potential of generative artificial intelligence (AI) to uncover and analyze racial inequities within the education system using rhetorical inference techniques. Racial disparities continue to persist in education, perpetuating systemic injustices and hindering equitable access to quality education. Adopting a critical lens, this study explores how generative AI, specifically through the analysis of rhetorical devices, can reveal and challenge the subtle forms of racism embedded within educational practices and policies.
Drawing on a corpus of educational texts, including curricular materials, policies, and classroom discourse, we employ state-of-the-art natural language processing techniques to analyze the presence and impact of rhetorical strategies that reinforce or challenge inequities. Our research framework combines established theories of racism and critical discourse analysis with the emerging field of generative AI. By utilizing deep learning models, such as recurrent neural networks and transformer architectures, we aim to unveil hidden patterns, implicit biases, and rhetorical tactics employed to maintain racial inequities.
This study extends the existing literature by demonstrating the potential of generative AI in providing a critical lens to analyze educational texts. Through rhetorical inference, we expect to identify linguistic and discursive patterns that perpetuate racism, including microaggressions, stereotypes, and exclusionary practices. By exposing these rhetorical strategies, we seek to engender awareness and stimulate dialogue to challenge and transform the educational landscape towards greater equity and inclusivity.
Our findings will have implications for educators, policymakers, and researchers striving to address racial inequities in education. The insights gained from this research will inform the development of interventions, pedagogical approaches, and policy recommendations aimed at dismantling systemic racism in educational settings. Moreover, this study contributes to the emerging field of generative AI in education, highlighting its potential as a tool for critical analysis and social justice advocacy.
Potential References:
- Working toward anti-racist perspectives in attachment theory, research, and practice
- Toward praxically-just transformations: Interrupting racism in teacher education
- AI for Social Good? Inspirations from Participatory Action Research (PAR) to Critical Data Studies
- We Must Find a Stronger Theological Voice: A Copeland Dialectic to Address Racism, Bias, and Inequity in Technology
- How Serious are We About Fairness in Testing and How Far are We Willing to Go? A Response to Randall and Bennett with Reflections About the Standards for …
