3 to Read: Moderating with machine learning | Expelled from Egypt | Street newspapers halt sales

Moderating with machine learning: The New York Times is learning some lessons while using machine learning to edit its comment section, writes Matthew J. Salganik and Robin C. Lee for the New York Times. Since 2017, the Times has used a form of machine learning called “Moderator” to review comment submissions and filter out spam. However, its Community Desk team still had to work to overcome some of the implicit biases incorporated into machine learning software.

Expelled from Egypt: It’s never easy being a foreign correspondent. Make that reporting from one of the most undemocratic countries in the world, and throw in a pandemic, and everything is way more difficult. Ruth Michaelson, in the Columbia Journalism Review, recounts her experiences working as a foreign correspondent in Egypt, one of the most dangerous countries for reporters, ranking 166th out of 180 countries in the 2020 World Press Freedom Index. Journalists who report on the crisis in a variety of undemocratic countries are currently facing fines, jail time and deportation for doing their job, a risk that is heightened under COVID-19 as countries seek to suppress reports of high infection rates.

Street newspapers halt sales: The loss of street newspapers has impacted homeless communities, where many people make their living as vendors, according to Kristi Eaton in Poynter. Many vendors have been hard-hit by the pandemic not only because of the loss of income, but because of the loss of social interaction that comes with quarantine. In response, organizations like Real Change are stepping up to provide vendors with food, money and help filing for social services like unemployment.


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