Machine learning in the wild -- #wins and #fails
For several years, machine learning has been a tantalizing Siren for reporters, promising to sort through your documents and find the juicy ones, or providing a road map to the people and places in your collection. After a few experiments in the wild, we'll help separate myth from truth, unpack the confusing language of the discipline and provide tips about when it might, and might not, serve your stories.
The panel is good for: Anyone. No statistics or math required. This session will be most useful if you are seeking new methods in reporting original stories.
Sarah Cohen is the Knight Chair in Journalism at the Walter Cronkite School at ASU. Previously, she worked as the editor of a data reporting team at The New York Times focused on long-term enterprise and investigative stories, and as a database editor for The Washington Post. Her awards include the Pulitzer Prize in Investigative Reporting, the Goldsmith Prize and the IRE medal. She is a past president of IRE, and served on the board for eight years.
Steven Rich is the database editor for investigations at The Washington Post. He's worked on investigations probing the National Security Agency, tax lien sales, asset forfeiture, policing and college athletics. He has been a reporter on two teams awarded Pulitzer Prizes, in 2014 and 2016, and on a team awarded a Peabody in 2018. Steven is a graduate of Mizzou and Virginia Tech. He was elected to IRE’s Board of Directors in 2015. @dataeditor
Janet Roberts heads the data journalism team at Reuters and has been wringing stories out of data since she was a student in Phil Meyer’s journalism class at UNC. Before Reuters, she worked at the New York Times, the St. Paul Pioneer Press and the Wilmington Star-News. She has been a finalist for the Pulitzer Prize in Explanatory Journalism and the Goldsmith Prize for Investigative Reporting. @jersey_janet
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