The dark side of Artificial Intelligence – Risks arising in dating applications
Fletcher, Rachel ; Tzani, Calli ; Ioannou, Maria (2024) — Assessment and Development Matters
Type:
Journal Article
Country:
United Kingdom
Synopsis (AI-Generated)
This is a narrative source review. The authors conducted general internet searches using terms concerning AI, dating applications, social media, romance fraud, and sextortion, and explored empirical literature. Findings synthesize concerns raised across internet and empirical sources; no original participant data collection, systematic search protocol, or primary analysis is reported. AI-driven automated bots in dating applications can impersonate genuine conversational partners to obtain personal information, induce malicious-link clicks, or solicit financial details. Catfishing using fake profiles and imagery is described as a common precursor to romance fraud and sextortion. The article relies on general internet searches alongside empirical literature and does not report a systematic review protocol, inclusion criteria, search dates, or appraisal of source quality.
Identified Gaps (AI-Generated)
The article identifies a lack of empirical research on harmful AI uses in dating and social-media contexts. Specific gaps concern psychological effects and support for deepfake targets, effective deepfake detection and distribution prevention, the contribution of facial recognition to harassment and stalking, and the current prevalence and nature of fraudulent dating applications. Existing romance-fraud advice based on reverse-image searches may also be outdated where perpetrators use original deepfake content.
Methods (AI-Generated)
This is a narrative source review. The authors conducted general internet searches using terms concerning AI, dating applications, social media, romance fraud, and sextortion, and explored empirical literature. Findings synthesize concerns raised across internet and empirical sources; no original participant data collection, systematic search protocol, or primary analysis is reported.
Limitations (AI-Generated)
The article relies on general internet searches alongside empirical literature and does not report a systematic review protocol, inclusion criteria, search dates, or appraisal of source quality. Several claims are framed as concerns, anecdotal evidence, or speculation about emerging risks rather than direct evidence of prevalence or causal impact. Its broad scope combines dating-app fraud with sextortion, child sexual abuse material, and cyberstalking.
Future Work (AI-Generated)
Research should examine the psychological consequences of deepfake victimization and available emotional support; develop and evaluate detection and prevention strategies for deepfake material; investigate whether facial recognition contributes to stalking and harassment; update evidence on the prevalence and operation of fraudulent dating apps; and identify practical solutions to block their distribution. Public education should also be developed so users can recognize AI-enabled criminal methods and protect privacy.
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.
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