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Journalism isn’t just reporting, it’s witnessing history, challenging power, amplifying unheard voices, and making sense of a chaotic world.

Media organisations using AI should set clear newsgathering and production guidelines to protect journalistic integrity and maintain audience trust.

Different news stories have a different value for your audience and for your business. Giving news items a 'weighting' can lead to impact and efficiencies.

With the spread of fake news, journalists need to recognise and understand the different categories, types, elements, and phases of information disorder.

Data journalism, also known as data-driven journalism, is the process of finding, understanding, and processing information in order to produce news stories.

The journalist in charge of a news website is like a shopkeeper who sets out their stall. If the items are badly displayed the customer might miss them, if they are not fresh people won't buy them.

Our role as journalists is to unearth information, prepare it and then display it for the benefit of the audience. We are not there to fabricate, manipulate or force.

Journalists who want to inform the audience need to keep records so that they can add context to breaking news stories without having to rely on others for background information

Journalists can sometimes present an inaccurate or false version of events by trying too hard to 'balance' a story or incorrectly treating elements of a story as being roughly equal.

Computer-Assisted Reporting (CAR) refers to the use of digital tools such as spreadsheets, databases, and basic statistical analysis to interrogate large datasets.

Discover why journalists use open-source intelligence (OSINT) to verify information, expose manipulation, and strengthen public trust in the news.

Most journalists are generalists, who can cover any kind of story.  But there is also a place for specialists, providing expertise on particular subjects.