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Articles by Jonathan Stray

Jonathan Stray is a senior scientist at the Center for Human-compatible AI at UC Berkeley, where he studies how algorithmic media drives political conflict. Previously he was an editor at the Associated Press and taught computational journalism at Columbia University.
@jonathanstray
We need to get beyond counting pageviews and ad impressions and build better ways of judging how our work changes the world around us.
There’s too much news for anyone to consume. Three key words should determine who gets served what: Interest, effects, and agency.
Algorithms can help, but more fundamentally, we need to figure out what we want a diverse pool of information to look like.
Does the quest for balance in news stories open journalists up to claims of bias? It’s all about the framing.
Technologists and humanists take different approaches — and speak different languages.
How we report on everything from murders to burglaries is tied to pre-Internet realities, Jonathan Stray argues. What would a digital-native crime report look like?
In the start of a regular column for Nieman Lab, Jonathan Stray argues that a too-narrow definition of the work of journalism limits the field’s potential.
December 16, 2010
August 5, 2010
June 25, 2010