Extending the Technology Acceptance Model for Political Artificial Intelligence Adoption with Trust and Transparency
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Abstract
This conceptual review examines the scholarly literature on AI adoption in political engagement, arguing that technical utility alone is insufficient. While the core Technology Acceptance Model (TAM) factors (Perceived Usefulness and Ease of Use) drive initial intentions, the analysis highlights that acceptance critically hinges on non-technical elements: social trust, political affiliation, and ethical concerns. The study addresses the critical intention-action gap between intending to use AI and its actual implementation in politics. To guide future scholarship, the paper advances existing TAM-based research by proposing an extension of TAM that formally integrates trust, transparency, and ethical perception as fundamental factors. The findings suggest that future research prioritize testing this conceptual extension and shifting focus toward tracking measurable, real-world AI use in elections. Successful, responsible AI integration is found to rely significantly on building public trust through stringent ethical safeguards.
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