The Impact of AI Attitudes on Detecting AI-Generated Political Content

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Abstract

The rise of generative artificial intelligence (AI) raises critical questions about users’ ability to distinguish AI-generated content from human-generated content, particularly in the political domain. This study investigates the relationship between subjective attitudes towards AI and the accuracy of detecting AI-generated political content. In an experiment involving political science students (n = 60), participants were asked to identify definitions of “political values” generated by the ChatGPT model and to assess their degree of ideological bias. The results revealed that, on average, only about half of the participants correctly identified the artificial origin of the definitions. However, the group of “optimists”, who hold a positive view of AI development, demonstrated significantly higher detection accuracy compared to the “neutral” group. Paradoxically, it was the “neutral” respondents who were significantly more likely to rate AI-generated content as completely objective and devoid of ideological bias. This suggests that a neutral, rather than a skeptical, stance towards AI may create a blind spot for potential ideological influence, as such content does not undergo sufficient critical reflection. The study contributes to understanding how user attitudes mediate the perception of political content in the age of generative AI.

About the authors

Dmitriy I. Kaminchenko

Lobachevsky University; Neimark University

Author for correspondence.
Email: dmitkam@inbox.ru
ORCID iD: 0000-0002-3193-3423
SPIN-code: 4176-7427

PhD in Political Sciences, Associate Professor of the Department of Political Science, Lobachevsky University; Senior Researcher of the Cognitive Security Lab, Neimark University

23 Gagarin Ave, Nizhny Novgorod, 603022, Russian Federation; 6 Nartova St, Nizhny Novgorod, 603057, Russian Federation

Aleksandr Yu. Petukhov

Lomonosov Moscow State University; Neimark University

Email: Lectorr@yandex.ru
ORCID iD: 0000-0002-7412-5397
SPIN-code: 2704-2219

PhD in Political Sciences, Associate Professor, Head of Laboratory of Mathematical Methods of Political Analysis and Forecasting, Lomonosov Moscow State University; Director of Science and Head of the Cognitive Security Lab, Neimark University

1 Leninskie Gory St, Moscow, 119991, Russian Federation; 6 Nartova St, Nizhny Novgorod, 603057, Russian Federation

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