Photo Steward: A Deliberative Collective Intelligence Workflow for Validating Historical Archives

CI '23: Proceedings of The ACM Collective Intelligence Conference(2023)

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摘要
Historical photographs of people generate significant cultural and economic value, but correctly identifying the subjects of photos can be a difficult task, requiring careful attention to detail while synthesizing large amounts of data from diverse sources. When photos are misidentified, the negative consequences can include financial losses and inaccuracies in the historical record, and even the spread of mis- and disinformation. To address this challenge, we introduce Photo Steward, an information stewardship architecture that leverages a deliberative workflow for validating historical photo IDs. We explored Photo Steward in the context of Civil War Photo Sleuth (CWPS), a popular online community dedicated to identifying photos from the American Civil War era (1861–65) using facial recognition and crowdsourcing. While the platform has been successful in identifying hundreds of unknown photographs, there have been concerns about unverified identifications and misidentifications. Our exploratory evaluation of Photo Steward on CWPS showed that its validation workflow encouraged users to deliberate while making photo ID decisions. Further, its stewardship visualizations helped users to assess photo ID information accurately, while fostering diverse forms of stigmergic collaboration.
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