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Using generative AI to help review your reporting: subbing, jargon, brevity and factchecking

Applications of genAI in the journalism process 
Pyramid with the third 'Production' tier highlighted: 

Identify jargon and bias; improve spelling, grammar, structure and brevity

In the fifth of a series of posts from a workshop at the Centre for Investigative Journalism Summer School, I look at using generative AI tools such as ChatGPT and Google Gemini to help with reviewing your work to identify ways it can be improved, from technical tweaks and tightening your writing to identifying jargon.

Having an editor makes you a better writer. At a basic level, an editor is able to look at your work with fresh eyes and without emotional attachment: they will not be reluctant to cut material just because it involved a lot of work, for example.

An editor should also be able to draw on more experience and knowledge — identifying mistakes and clarifying anything that isn’t clear.

But there are good editors, and there are bad editors. There are lazy editors who don’t care about what you’re trying to achieve, and there are editors with great empathy and attention to detail. There are editors who make you a better writer, and those who don’t.

Generative AI can be a bad editor. Ensuring it isn’t requires careful prompting and a focus on ensuring that it’s not just the content that improves, but you as a writer.

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