Fight Fire With Fire: How Does AI‐Powered Technology Empower the Elderly Anti‐AI Fraud Through a Socio‐Technical Systems Theory Lens?
Sima, Herbert ; Chen, Jie ; Wei, Junlong ; Chen, Wei ; Thaichon, Park (2026) — Journal of Consumer Behaviour
DOI:
10.1002/cb.70106
Type:
Journal Article
Country:
China
Synopsis (AI-Generated)
This piece examines Fight Fire With Fire: How Does AI‐Powered Technology Empower the Elderly Anti‐AI Fraud Through a Socio‐Technical Sys within the broader context of online fraud and mediated communication. It outlines common patterns documented in the literature, describes how offenders cultivate trust and shift interactions onto controlled channels, and notes the role of staged identities, persuasive scripts, and escalating commitment. The discussion situates these elements within themes frequently reported by victims, including emotional grooming, urgency cues, and isolation from outside advice. The work also highlights typical areas of inquiry for researchers and practitioners: factors associated with victim susceptibility, the influence of platform affordances, and touchpoints where prevention or disruption is most feasible. Attention is given to reporting barriers, financial harms, and downstream impacts on wellbeing. Implications emphasize the value of cross-sector collaboration, clearer platform policy enforcement, and targeted awareness strategies informed by real case dynamics. Presented in Journal of Consumer Behaviour, the piece contributes to ongoing efforts to translate observed scam mechanics into actionable guidance for detection, education, and support.
Identified Gaps (AI-Generated)
Gaps identified include: (a) prior work often treats AI technology and vulnerable consumers separately, lacking a joint STS framework; (b) insufficient empirical validation of co-designing social and technical subsystems for the elderly; (c) limited attention to brand trust dynamics under AI-enabled fraud; (d) need for generalizable governance roadmaps and policy interventions; (e) under-representation of elderly digital literacy in design; (f) calls for inclusive, accessible design to preserve autonomy.
Methods (AI-Generated)
This study adopts a product-oriented, in-depth single-case study of the Silver Guardian project within the Cyber-Shield Security Ecosystem. It uses socio-technical systems theory to analyze joint optimization of technical and social subsystems for elderly users (low digital literacy, high emotional vulnerability, cognitive limits). The investigation follows stages of product formation, iteration, and cloud-based prevention upgrades, noting how an iterative governance model—described as 'controlled, cooperative, and evaluative'—improves AI fraud detection and reduces risk. By integrating literature on consumer fraud, elderly vulnerability, AI's double-edged nature, and STS, the paper offers a holistic framework for elder protection through algorithmic governance and brand trust.
Limitations (AI-Generated)
Limitations stem from the single-case, qualitative orientation of a product-focused study within one national context. Generalizability to other cultures or fraud contexts may be limited, and empirical measurement of outcomes is constrained by available documentation rather than randomized trials. The reliance on ongoing corporate projects may introduce context-specific biases in governance and stakeholder interactions. While the STS lens offers integration of social and technical factors, transferability of the joint-optimization insights to different platforms or populations should be done cautiously. Future work should validate findings across settings and with quantitative impact metrics.
Future Work (AI-Generated)
Future research should broaden empirical coverage beyond a single case to test cross-country applicability of the integrated STS framework. Comparative studies across different elderly populations and fraud types would illuminate contextual contingencies. Further work could translate joint optimization of social and technical subsystems into actionable design guidelines and governance protocols, including privacy-preserving AI, accessible UX, and policy interventions. Longitudinal studies could assess effects on elder well-being, trust, and fraud resilience over time. Collaboration among policymakers, platforms, and financial institutions would help translate insights into scalable, ethical anti-fraud solutions.
AI-Generated Content Notice
The synopsis and research notes on this page were generated with AI from available publication information and, when available, the uploaded paper text. They may contain errors, omissions, or interpretation issues. Readers should follow the DOI or source link, review the original publication, and make their own judgment about the content.