UCLA

Visual media without alternative text descriptions are inaccessible to blind and low vision (BLV) people. While mainstream automated solutions often focus on achieving acceptable results based solely on visual media, they neglect the essential engagement of internet users in contributing to accessibility. With an explosion of data, diverse media formats, and constant updates, the responsibility of ensuring accessibility and equity cannot rest solely on the shoulders of a select few. The sheer volume of digital contents demands a community effort where each individual becomes an advocate for accessibility. With the central goal of effecting this community-level change, I design and develop intelligent user interfaces that engage internet users in making visual media accessible at three progressive levels: i) extracting visual information from human-authored texts in metadata to generate in-context descriptions; ii) nudging people to use visual descriptive language in online activities; iii) creating symbiotic information seeking experiences that connect sighted and BLV people of the same community. Three practical application scenarios, online shopping, online video watching and commenting, online research paper reading, are explored to demonstrate the implementation of each engagement level. Moving beyond paid crowdsourcing, this dissertation envisions a future where user advocacy plays a crucial role in creating a more unified and inclusive internet.