Dynamic Content Filtering

The automated process of selectively showing or hiding web content based on computed relevance to a user's goals, preferences, or context. Dynamic content filtering uses AI models (such as large language models) to assess which page elements are relevant to a specific task and adjusts their visibility accordingly. Unlike static content removal (such as ad blockers), dynamic filtering adapts to different user goals on the same page, making it a flexible tool for both accessibility and productivity. This approach can dramatically reduce the time screen reader users spend navigating irrelevant content.