Investigative journalism and ChatGPT: using generative AI for story ideas

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Applications of genAI in the journalism process Pyramid with the bottom 'pre-production' layer highlighted: Idea generation and stimulation: identify and map systems and rules, apply brainstorming frameworks (iceberg model, 5 whys, 8 angles of data journalism). Planning.
Generative AI can be used at all points in the journalism process: this post focuses on pre-production

Last week I delivered a session at the Centre for Investigative Journalism Summer School about using generative AI tools such as ChatGPT and Google Gemini for investigations. In the first of a series of posts from the talk, here are my tips on using those tools for idea generation.

Generative AI tools may not be entirely reliable, but that doesn’t mean that they’re not useful. Journalism, after all, is about more than just gathering information: reporters also need to generate story ideas, identify and approach potential sources, plan ahead, write and edit stories and solve a range of technical challenges. All of these are areas where genAI can help.

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VIDEO: AI in journalism: machine learning and natural language processing

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Machine learning and Natural Language Processing (NLP) are two forms of artificial intelligence that have been used for years within journalism. In this video, part of a series of video posts made for students on the MA in Data Journalism at Birmingham City University, I explain how both technologies have been used in journalism, the challenges that journalists face in using them, and the various concepts and jargon you will come across in the field.

PS: The MA courses at BCU have an open day this month: you can register here.

The examples mentioned in the video include:

Investigative journalism’s AI challenges: accuracy and bias, explainability and resources

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screenshots of guidelines on AI

Having outlined the range of ways in which artificial intelligence has been applied to journalistic investigations in a previous post, some clear challenges emerge. In this second part of a forthcoming book chapter, I look at those challenges and other themes: from accuracy and bias to resources and explainability.

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AI in investigative journalism: mapping the field

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screenshots of various examples of AI being used in journalism, including Serenata de Amor, Leprosy of the Land and The Implant Files

Investigative journalists have been among the earliest adopters of artificial intelligence in the newsroom, and pioneered some of its most compelling — and award-winning — applications. In this first part of a draft book chapter, I look at the different branches of AI and how they’ve been used in a range of investigations.

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VIDEO: How can virtual reality, 360 degree video and augmented reality be used for journalism — and what are the challenges?

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Virtual reality and augmented reality have opened up a range of new opportunities for journalists and publishers — as well as new challenges.

In this video, made for students on the MA in Data Journalism and the MA in Media Production at Birmingham City University, I explain what types of stories and projects suit these technologies, what to consider when using them, and some useful techniques from those who have worked in the field.

The MA courses at BCU have an open day in June: you can register here.

You can find links to all of the examples used in the video on the YouTube page.

This video is shared as part of a series of video posts.

Explainers — explained (unpublished extract from the Online Journalism Handbook)

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Explainers are one of the most widely used forms of ‘evergreen’ content. In this unpublished extract from the latest edition of the Online Journalism Handbook, removed due to word limit, I explore why they are so popular, what types of subject are suitable, and how explainers are structured.

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VIDEO: Using ChatGPT and generative AI tools in journalism

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A few months ago I delivered a webinar for the European Data Journalism Network and DataNinja about the range of ways that journalists can use ChatGPT and other generative AI tools — from idea generation and mapping systems to help with spelling and coding — and what issues they need to be aware of.

The video is now available online and you can watch it below.

VIDEO: How to plan an investigation or large editorial project

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Planning an investigation, or any larger editorial project, raises its own particular challenges — but if you know where to look, you can find resources that are especially useful in anticipating and tackling those.

This video, made for students on the MA in Data Journalism at Birmingham City University, introduces and explores two such resources: Mark Lee Hunter‘s story-based inquiry method; and breaking down an investigation into five roles; . It also touches on issues to consider in undercover reporting or the use of subterfuge.

Further video clips of Mark Lee Hunter and Luuk Sengers are embedded below:

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Olaya Argüeso: “Data journalism stories, when they are done, are really easy to implement on the local level”

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Olaya Argueso Perez: fotocredit: Ivo Mayr, CORRECTIV2
Photo: Ivo Mayr, CORRECTIV.Europe

The CORRECTIV.Europe project, founded by German investigative media outlet Correctiv, aims to help local journalists publish data stories who wouldn’t otherwise have the time or money to do it. Cristina Puerta speaks to its editor-in-chief Olaya Argüeso.

“[CORRECTIV.Europe] is about giving the European citizens a feeling that they are on the same boat together”, editor-in-chief Olaya Argüeso explains.

Local journalism, she says, has been “neglected”, and it is now, when people suffer the consequences of global phenomena — for example, climate change because of flooding and droughts where they live — that they realise how important local journalism is.

News avoidance is at an all-time high, and while Argüeso feels breaking global problems down to a local level cannot be the solution, it can, she says, show citizens what they can do about those problems.

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