DOOMERISM AND CHATGPT: DEVELOPERS BECOME DOOMERS FOR THE NEXT DISASTER

Abstract

This study examined the manufacture of conflict in AI discourse, focusing on how developers, executives, and affiliated technocrats articulated doomer narratives surrounding ChatGPT and other advanced AI systems. Drawing on a post-positivist research paradigm, the study employed a qualitative case study design using an online literature review to collect publicly available statements, policy documents, corporate communications, and media reports. Purposive sampling was applied to select materials that exemplified catastrophic risk framing, technocratic authority, and narrative strategies designed to shape public perception. Data were analyzed using thematic analysis to identify patterns in the construction of AI risk, the legitimization of technocratic oversight, and the concentration of power within leading AI organizations. Findings revealed that AI doomer discourse frequently employed metaphors, high-certainty modality, and urgency framing, which amplified perceptions of existential and systemic risk. This discourse not only primed the public for fear-driven compliance but also justified centralized governance, restricted access, and regulatory authority among technocratic elites. The parallels with crisis management during the COVID-19 pandemic demonstrated how manufactured conflict could legitimize technocratic decision-making in global emergencies. The study argued that these dynamics had significant implications for democratic governance, public understanding of AI, and power concentration in the AI industry. It further emphasized the importance of emancipatory AI education to cultivate critical literacy, ethical responsibility, and participatory engagement, countering fear-based narratives and fostering informed public deliberation. By linking discourse analysis with governance and sociotechnical theory, the study contributed to understanding how language, narrative, and expertise intersected to shape public perception and policy in high-stakes technological contexts.