SafeScreen: A Safety-First Screening Framework for Personalized Video Retrieval for Vulnerable Users
In an era dominated by digital content, open-domain video platforms have emerged as powerful tools providing personalized content that can enhance health, caregiving, and educational experiences. However, the engagement-optimized recommendation algorithms typically employed by these platforms can pose significant risks, particularly for vulnerable users such as children and individuals in dementia care. These users are at a heightened risk of being exposed to inappropriate or harmful material, necessitating a more careful approach to content delivery.
To address these concerns, a new framework called SafeScreen has been introduced. This innovative system focuses on safety-first video screening, ensuring that all retrieved videos meet individualized safety constraints before being presented to users. Unlike traditional algorithms that prioritize relevance or popularity, SafeScreen treats safety as a fundamental prerequisite for content exposure, implementing a sequential approval or rejection process for potential video candidates.
Key Components of SafeScreen
SafeScreen is built upon three essential components that work in tandem to facilitate a safe and personalized video retrieval experience:
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Profile-Driven Extraction of Individualized Safety Criteria:
This component identifies and extracts safety criteria tailored to the unique profiles of users, ensuring that the content aligns with their specific needs and vulnerabilities. -
Evidence-Grounded Assessments:
SafeScreen employs adaptive question generation and multimodal VideoRAG (Video Retrieval-Augmented Generation) analysis to assess the safety and appropriateness of the content. This process enables the framework to evaluate videos based on concrete evidence rather than assumptions. -
LLM-Based Decision-Making:
Utilizing advanced language models, SafeScreen verifies the safety, appropriateness, and relevance of videos before they are presented to users. This layer of decision-making ensures that only content meeting safety standards is shown, contributing to a more secure viewing experience.
Evaluating SafeScreen’s Effectiveness
The efficacy of SafeScreen has been put to the test in a dementia-care reminiscence case study. Researchers evaluated the framework using 30 synthetic patient profiles and 90 test queries. The results were promising, demonstrating that SafeScreen successfully prioritized safety over user engagement in 80-93% of tested scenarios. This marked divergence from platforms like YouTube, which typically focus on engagement metrics, highlights the framework’s commitment to safety-first content delivery.
Furthermore, SafeScreen maintained high levels of safety coverage, sensibleness, and groundedness throughout its evaluations. These outcomes were validated not only by assessments from language models but also by domain experts, underscoring the framework’s practical applicability in real-world settings.
Conclusion
As digital content consumption continues to rise, the need for frameworks like SafeScreen becomes increasingly vital. By prioritizing safety and implementing individualized constraints, SafeScreen offers a promising solution for ensuring that vulnerable users can access personalized video content without the risk of exposure to harmful material. As this technology evolves, it holds the potential to significantly enhance the safety and well-being of users in sensitive environments.