Classification for the digital and cognitive AI hazards: urgent call to establish automated safe standard for protecting young human minds
Ahmed Shalaby
Abstract
Abstract This study presents a novel classification framework for digital and cognitive AI hazards (Shalaby’s Classification for Digital Hazards), aiming to comprehensively categorize risks across pathophysiological impacts, technical sources, content-related risks, algorithmic influences, modification factors, and mitigation measures. It utilizes rigorous literature review methodologies to synthesize existing research and proposes practical implementations, including an AI-driven scoring system for personalized risk assessment and mitigation strategies. The framework addresses the critical imperative to effectively manage evolving digital risks amid rapid technological advancements, while acknowledging challenges such as data availability limitations and ethical considerations.