Earlier this month I was pleased to receive an invitation from the Centre for Research in the Arts, Social Sciences and Humanities (CRASSH) at the University of Cambridge to contribute to a workshop called ‘How Can Public Interest Journalism Hold Algorithms to Account?’.
Nick Diakopoulos from the University of Maryland gave an interesting talk on algorithmic accountability and computational journalism and Jonathan Gray and I gave a preview of the Public Data Lab’s A Field Guide to Fake News, to be launched next month at the International Journalism Festival in Italy.
The field guide is a collection of recipes to trace the production, circulation and responses to fake news online. Its production is supported by the First Draft Coalition. The aim is to suggest different ways of mapping and responding to fake news beyond identifying and fact-checking suspect claims – including “thicker” accounts of circulation as a way to develop a richer understanding of how fake news moves and mobilises people, more nuanced accounts of what fake news is, and responses which are better attuned to the phenomenon.