By Matt Carroll <@MattCData>
Oct. 6, 2018: Cool stuff about journalism, once a week. Get notified via email? Subscribe: 3toread (at) gmail. Originally published on 3toread.co
- How a college drop-out became a champion of investigative journalism: Bellingcat broke (another) big scoop when it identified one of the Russians suspected in nerve gas poisoning in Britain as a member of the Russian intelligence service. Give credit to Bellingcat’s founder, mild-mannered Eliot Higgins, who might have taken an entirely different career path if the technology he was playing with in college had been a little better. Jamie Doward for The Guardian.
2. Why the NYT did a short version of its mammoth Trump investigation: Because it has learned how to the web right, that’s why. Alongside its amazingly detailed — and incredibly long — investigation into the Trump family history of real estate shenanigans that enriched them all, was a much shorter piece: “11 Takeaways From The Time’s Investigation in Trump’s Wealth.” Not so long ago it would’ve been another newsroom, like BuzzFeed, which would have taken the NYT story and boiled down — earning itself more hits than the original. Those days are over. Laura Hazard Owen for Nieman Lab.
3. How nonprofit newsrooms are seeking other revenue sources (beside philanthropy): Nonprofit newsrooms are often perceived to survive only because of the largesse of one or two major benefactors. That’s not the case these days. The nonprofits are finding many different revenue streams. A good report by Christine Schmidt for Nieman Lab.
btw: No “3 to read” the next two weeks.
AI, Media and the Threat to Democracy
Interested in the intersection between Artificial Intelligence and the Media?
We have just the conference for you.
When: Friday, Oct. 12
Where: Northeastern University, Boston
Cost: Free & open to the public
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Keynote: Danielle Citron, Morton & Sophia Macht Professor of Law at the University of Maryland Francis King Carey School of Law
1. AI on the Beat: How journalists are using — and covering — bots, algorithms and whatever comes next
2. AI, big data, and bias in sociotechnical systems
3. Legal and Policy Responses to AI and the Media
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