Machine learning and investigative reporting
Has your editor ever asked for a couple of examples? What if you could use machine learning to find some of those examples and investigate a real phenomenon?
Join reporters who have used machine learning as a tool in investigative reporting. You’ll hear about how we used machine learning to find patients whose deaths were potentially linked to medical devices; tracked fake news and identified illegal ads on Facebook; investigated potential campaign finance fraud; and did financial muckraking in the tax records of a global financial corporation.
We’ll answer important questions like: What is machine learning? What kind of stories could it help with? and What do you need to take into account to get started?
Meredith Broussard is an assistant professor at the Arthur L. Carter Journalism Institute of New York University and the author of Artificial Unintelligence: How Computers Misunderstand the World. Her research focuses on artificial intelligence in investigative reporting, with a particular interest in using data analysis for social good. Follow her on Twitter @merbroussard or contact her via meredithbroussard.com.
Emilia is ICIJ’s research editor. She has taken part in cross-border projects such as ICIJ's Implant Files, Paradise Papers and the Pulitzer winner investigation Panama Papers. She has been a professor at the Central University of Venezuela and a contributor for the Washington Post, the magazine Poder y Negocios, Venezuelan media El Universal, El Mundo and Armando.info, which she co-founded. She was previously the investigative reporting coordinator at IPYS Venezuela.
Jeff Ernsthausen is a data reporter at ProPublica. He joined ProPublica from the Atlanta Journal-Constitution, where he worked as a data reporter on the investigative team. Prior to his time in journalism, he worked as an economic analyst and researcher at the Federal Reserve.
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