The Social Iowa Gambling Task: a promising tool for assessing deception detection in real-world contexts in adulthood

Deception detection represents a complex form of social decision making under uncertainty with real-world consequences. Yet reliable tools to identify vulnerability to fraud and exploitation, marked by large individual variability, particularly among older adults, remain limited. Using a short, scalable laboratory task, the Social Iowa Gambling Task (sIGT), we tested whether adaptive social decision making predicts interpersonal and technologically mediated deception detection.

Younger and older adults from a single cohort (Lie Task: N = 153; Deepfake Task: N = 149) completed the sIGT, assessing decision-making in the presence of congruent or incongruent facial trustworthiness cues. Participants judged the veracity of emotional pleas (Lie Task) and face images (Deepfake Task). Deception detection accuracy was analyzed using generalized linear mixed-effects models.

Higher sIGT performance predicted greater lie detection accuracy for deceptive, but not truthful, videos, indicating selective sensitivity to misleading cues. Performance under incongruent facial-cue conditions, requiring resistance to trustworthiness bias, showed a stronger relationship with Lie Task accuracy. For the Deepfake Task, higher sIGT scores were associated with greater discernment of deepfakes from real faces, without moderation by facial-cue condition. For both tasks, predictive effects of sIGT performance were age-invariant.

Study findings indicate that adaptive social decision-making can predict abilities to detect deception perpetrated through lying and AI-based deepfakes. Results suggest that the ability to adapt under conflicting social cues appears central to resisting lies. As a brief, standardized, and scalable laboratory measure, the sIGT shows promise for identifying individual vulnerability to deception and guiding tailored intervention strategies.