An AI-Media Literacy Competency Framework for AI-Augmented Adolescent Cyberbullying: A Scoping Review

ABSTRACT

Artificial intelligence is altering how cyberbullying manifests among adolescents. Generative tools now make it much easier to create fake photos, cloned voices, and fabricated screenshots, reducing the cost of impersonation and deception. At the same time, ranking and recommendation systems on digital platforms can exacerbate the harm when they promote embarrassing content to larger, more widespread audiences and keep harmful content visible for longer periods. Those developments make it more difficult to trace blame and protect usable evidence, and to act quickly. But many of today’s prevention efforts and media literacy efforts continue to focus on AI-related risks in a narrow sense. To address this gap, the study conducted a PRISMA-ScR-guided scoping review of multidisciplinary studies published between 2018 and 2025. Following deduplication, 2,249 records were reviewed and 58 were added to the final synthesis. This paper clusters the evidence into four emergent AI-enabled threats: fabrication and impersonation, amplification driven by visibility dynamics, automation at scale, and gaps in governance and adjudication. Based on this evidence map and a five-stage overview of cyberbullying, the paper develops an AI-Media Literacy Competency Framework that establishes links between the threat areas and teachable competencies, stakeholder responsibilities, and actionable response plans. The framework establishes five teachable domains: syntheticmedia verification, platform and algorithm knowledge, privacy and identity preservation, reporting and redress, and prosocial bystander behavior. Rather than collecting new human-subject data, this paper synthesizes the existing evidence into a usable, AI-informed framework for prevention and response in contexts of uncertain authenticity, algorithmically amplified visibility, and continuous cross-platform recirculation.

KEY WORDS

Adolescents. Artificial Intelligence Literacy. Cyberbullying. Deepfakes. Generative AI. Media Literacy. Recommender Systems.

DOI

https://doi.org/10.34135/mlar-26-01-01