Search a Great Leveler? Ensuring More Equitable Information Acquisition

Abstract

AbstractThe ubiquitous search box promised to democratize knowledge access by making information universally accessible. But while many search engines cater well for certain user groups, information tasks and content types, they cater poorly for others. Poorly‐served users include those with certain types of impairment (e.g. dyslexia), and weakly‐supported tasks include highly exploratory goals, where it can be difficult to express information needed as a query. Furthermore, the overdominance of search functionality in many information environments has restricted support for other important forms of information acquisition, such as serendipitous information encountering and creative “inspiration hunting.” Search results and recommendations can also promote certain types of content due to algorithmic bias. Rather than act as a great leveler by making information acquisition effective, efficient and enjoyable for all, search engines often unfairly favor some types of user, task or content over others. In short, search is not always equitable. This panel discussion will elucidate the inequity of search as an information acquisition paradigm from multiple perspectives and propose design principles to ensure more equitable information acquisition.