Synthetic Reality and the Erosion of Epistemic Trust: Deepfake Misinformation, Confirmation Bias, and Democratic Cynicism Among Indonesian Voters

Abstract

Background: Synthetic media generated by artificial intelligence (deepfakes) threatens democratic consolidation, yet most evidence is Western and video-centred and rarely models how such media shapes citizens' political attitudes.

Objective: Grounded in epistemic-trust theory, motivated-reasoning theory, and the Liar's Dividend thesis, this study examined how the illusion of authenticity, confirmation-bias acceleration, and perception of the Liar's Dividend relate to democratic cynicism among Indonesian voters, and whether confirmation bias mediates and synthetic-media literacy moderates these relationships.

Methods: A nested mixed-methods design combined computational extraction of 4,200 synthetic-media items (detector F1 = 0.92), a cross-sectional survey of 3,000 adults recruited by proportional random sampling across three urban centres in Indonesia, and digital ethnography with 50 key informants.

Results: The novel Epistemic Trust Erosion Scale demonstrated strong reliability (total alpha = 0.893; subscales 0.77 to 0.85) and sampling adequacy (KMO = 0.93). Cloned-audio deepfakes were trusted by 76.2% of respondents but consciously detected by only 11.5%, inverting the global assumption of video primacy. Illusion of authenticity (beta = 0.256), confirmation bias (beta = 0.269), and Liar's Dividend perception (beta = 0.212) each predicted democratic cynicism (all p < 0.001), explaining 33.0% of its variance (F(3, 2996) = 492.57, p < 0.001, f-squared = 0.493). Confirmation bias partially mediated the authenticity-cynicism pathway (indirect effect = 0.153, 95% CI [0.135, 0.172]). Synthetic-media literacy lowered cynicism but did not buffer the pathway.

Conclusion: The findings extend deepfake scholarship to oral, messaging-centred Global-South publics and inform electoral-integrity policy.