Debiasing the Influence of Demographic and Appearance Cues in Social Engineering via Role-Taking: Negative Results

2025-09-27

AI Summary

This study investigates how appearance-based cues—such as gender, age, race, and attire—influence trust judgments and risk decisions (in financial and rental advice contexts) within social engineering scenarios, and evaluates whether a multimodal digital literacy intervention—incorporating role-taking, reflective practice, and situational simulation—can mitigate such appearance biases. Using a mixed-factor experimental design, the study employs validated credibility scales, word-of-mouth propagation metrics, and issue involvement assessments, with pre-/post-tests and multi-group controls to analyze behavioral outcomes. Results reveal no significant within- or between-group differences in trust propensity or risk-taking among intervention participants, indicating that the integrated debiasing strategy fails to effectively attenuate appearance cue effects in ecologically valid social engineering settings. This work pioneers the integration of experiential role-play and media literacy pedagogy into high-ecological-validity social engineering experiments, demonstrating the resilience of appearance-based bias and the limitations of current interventions—thereby providing critical empirical grounding for future cognitive inoculation and structured anti-manipulation training frameworks.

Technology Category

• Cognitive Modeling & Cognitive Systems: Social Cognition And Interaction
• Application Domains: Humanities & Computational Social Science
• Data Mining & Knowledge Management: Representing, Reasoning, and Using Provenance, Trust

Application Category

• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI
• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems
• Security and Privacy: Large-scale security measurements

Abstract

This study investigates the efficacy of role-taking and literacy-based interventions in reducing the influence of appearance cues, such as gender, age, ethnicity, and clothing style, on trust and risk-taking in social engineering contexts. A-4 (Group: Control, Literacy, Persuader, Persuadee) * 2 (Time: Pre, Post) mixed factorial design was implemented over two weeks with 139 participants. The control group received no material. The literacy group attended two sessions focused on how behavior can be similar regardless of appearance cues. The persuader group completed three sessions, learning how to use such cues to influence others. The persuadee group attended three sessions involving the selection, justification, and reflection on personas and scenarios. Scenarios centered on financial and rental advice. A one-week gap followed before post-intervention testing. In both pre- and post-tests, participants assessed personas combining appearance cues, offering mobile hotspots with potential risk. They rated trust and willingness to take the risk. Validated measures and scenarios were used, including word-of-mouth and issue involvement scales. It was expected that cue influence would diminish post-intervention. However, no significant within- or between-group differences emerged. Findings raise concerns about the effectiveness of debiasing efforts and call for reconsideration of approaches using literacy, role-taking, rehearsal, drama, and simulation.

Problem

• Reducing appearance cue influence on trust in social engineering
• Testing role-taking interventions for demographic bias mitigation
• Evaluating debiasing effectiveness for gender, age, and ethnicity cues

Innovation

• Role-taking interventions to reduce appearance cue influence
• Literacy training on behavior similarity across demographics
• Persuader and persuadee sessions for debiasing social engineering