Opening the black box: reporting on algorithms, big data and artificial intelligence

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Credit: Michael Dziedzic on Unsplash

Algorithms, big data and artificial intelligence. These are tricky topics to navigate but ones which many journalists are increasingly grappling with as tech stories become more mainstream.There have been some teething issues though. The classic example in 2015 was when NPR mapped the most common job in every US state using data derived from the Bureau of Labor Statistics. Truck drivers dominated the map.The issue is in the nuance of what ‘truck driver’ means; the category includes anything from delivery drivers to those driving 16-wheel lorries. Subsequent articles which reported that 1.8m truck drivers could lose their jobs to robots were criticised for being speculative and inaccurate.The point is that as tech becomes more complex and commonplace, there are more pitfalls to consider and more jargon to unpick for readers.At the Centre for Investigative Journalism’s Logan Symposium event this week (17 November 2020), tech journalists weighed in on some of the frequent issues.There have since been useful examples on how to do the topic justice. The standard rule of journalism is to never assume knowledge in your reader and that is very applicable to reporting on big tech.Embrace explainer articlesTim Maughan, …

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