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Cited by 16Misinformation and Its ImpactsDigital Media Forensic DetectionDeception detection and forensic psychology

Individual Deep Fake Recognition Skills are Affected by Viewer’s Political Orientation, Agreement with Content and Device Used

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Sütterlin, Stefan, Ask, Torvald F., Mägerle, Sophia, Glöckler, Sandra, Wolf, Leandra, Schray, Julian, Chandi, Alava, Bursac, Teodora +4 more·2023·Lecture Notes in Computer Science
DOI 10.1007/978-3-031-35017-7_18

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Abstract

AI-generated “deep fakes” are becoming increasingly professional and can be expected to become an essential tool for cybercriminals conducting targeted and tailored social engineering attacks, as well as for others aiming for influencing public opinion in a more general sense. While the technological arms race is resulting in increasingly efficient forensic detection tools, these are unlikely to be in place and applied by common users on an everyday basis any time soon, especially if social engineering attacks are camouflaged as unsuspicious conversations. To date, most cybercriminals do not yet have the necessary resources, competencies or the required raw material featuring the target to produce perfect impersonifications. To raise awareness and efficiently train individuals in recognizing the most widespread deep fakes, the understanding of what may cause individual differences in the ability to recognize them can be central. Previous research suggested a close relationship between political attitudes and top-down perceptual and subsequent cognitive processing styles. In this study, we aimed to investigate the impact of political attitudes and agreement with the political message content on the individual’s deep fake recognition skills.In this study, 163 adults (72 females = 44.2%) judged a series of video clips with politicians’ statements across the political spectrum regarding their authenticity and their agreement with the message that was transported. Half of the presented videos were fabricated via lip-sync technology. In addition to the particular agreement to each statement made, more global political attitudes towards social and economic topics were assessed via the Social and Economic Conservatism Scale (SECS).Data analysis revealed robust negative associations between participants’ general and in particular social conservatism and their ability to recognize fabricated videos. This effect was pronounced where there was a specific agreement with the message content. Deep fakes watched on mobile phones and tablets were considerably less likely to be recognized as such compared to when watched on stationary computers.To the best of our knowledge, this study is the first to investigate and establish the association between political attitudes and interindividual differences in deep fake recognition. The study further supports very recently published research suggesting relationships between conservatism and perceived credibility of conspiracy theories and fake news in general. Implications for further research on psychological mechanisms underlying this effect are discussed.

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Crossref · 10.1007/978-3-031-35017-7_18

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  • People's agreement with the content of a message significantly affects judgments of the authenticity of videos.

    “Studies have shown the importance of assessing message content itself as people ' s agreement with the content of a message signi fi cantly a ff ects judgments of the authenticity of videos [38, 39].”

    From Human Performance in Deepfake Detection: A Systematic Review (2025) · cites this paper as [38]

  • Those with conservative political attitudes may be less likely to correctly identify deepfakes, especially when video content aligns with their political views.

    “Those with conservative political attitudes may be less likely to correctly identify deepfakes, especially when video content aligns with their political views [38].”

    From Human Performance in Deepfake Detection: A Systematic Review (2025) · cites this paper as [38]

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Authors
Sütterlin, S., Ask, T. F., Mägerle, S., Glöckler, S., Wolf, L., Schray, J., Chandi, A., Bursac, T., Khodabakhsh, A., Knox, B. J., Canham, M., & Lugo, R. G.
Affiliations
  • Tallinn University of Technology (EE)
  • Østfold University of Applied Sciences (NO)
  • Albstadt-Sigmaringen University (DE)
  • Norwegian University of Science and Technology (NO)
Corresponding author
Sütterlin, Stefan
ORCID
Venue
Lecture Notes in Computer Science
Publisher
Springer Nature Switzerland
Published
2023
Pages
269-284
ISSN
  • 0302-9743 (ISSN-L)
  • 1611-3349
DOI
10.1007/978-3-031-35017-7_18
OpenAlex
W4383616947
Cited by
16
References
41
Citations by year
2026: 5 · 2025: 4 · 2024: 3 · 2023: 4
FWCI
14.86
Type
conference paper
Language
en
Open access
Licence
Locations
  • Lecture notes in computer science (publishedVersion)
  • PsyArXiv (OSF Preprints) (submittedVersion, cc-by)
  • PsyArXiv (OSF Preprints) (submittedVersion)
Funders
Norges Forskningsråd (302941)
Topics
  • Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Digital Media Forensic Detection
  • Social Sciences › Psychology › Social Psychology › Deception detection and forensic psychology
Keywords
political attitudes, social conservatism, economic conservatism, individual differences, device type, social engineering attacks, misinformation, authenticity judgments, conspiracy theories

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