The global decline in democratic governance suggests that more innovative approaches are required if civic engagement in the process of policy development is to be enhanced or maintained. This research explores the role of generative artificial intelligence and natural language processing in this context through a case study of three Canadian parliamentary Bills: Bill C-12 (Canada Net-Zero Emissions Accountability Act), Bill S-211 (Fighting Against Forced Child Labour in Supply Chains Act), and Bill C-18 (Online News Act). Using Python-based tools and OpenAI’s 4o-mini, this study analyses transcripts of parliamentary debates to extract key argumentative themes and to generate policy recommendations. AI-generated recommendations are then compared with the actual content of the Bills, identifying areas of alignment, complementarity, and divergence. The findings demonstrate AI's potential to provide an analytical lens on legislative processes, surfacing underemphasised arguments and revealing alternative policy dimensions; aspects often absent in final legislation. Ultimately, this study underscores AI's capacity to augment, rather than replace, traditional governance methods, offering a pathway to strengthen the quality and transparency of democratic deliberation.
Koshy et al. (Wed,) studied this question.
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