Category Archives: AI

Why I’m no longer saying AI is “biased”

2 Replies

TLDR; Saying “AI has biases” or “biased training data” is preferable to “AI is biased” because it reduces the risk of anthropomorphism and focuses on potential solutions, not problems.

Searches for "AI bias" peaked in 2025. In March 2025 twice as many searches were made for "AI bias" compared to 12 months before.
Click image to explore an interactive version

For the last two years I have been standing in front of classes and conferences saying the words “AI is biased” — but a couple months ago, I stopped.

As journalists, we are trained to be careful with language — and “AI is biased” is a sloppy piece of writing. It is a thoughtless cliche, often used without really thinking what it means, or how it might mislead.

Because yes, AI is “biased” — but it’s not biased in the way most people might understand that word.

Continue reading →

How do I get data if my country doesn’t publish any?

1 Reply
Spotlight photo by Paul Green on Unsplash

In many countries public data is limited, and access to data is either restricted, or information provided by the authorities is not credible. So how do you obtain data for a story? Here are some techniques used by reporters around the world.

Continue reading →

7 prompt design techniques for generative AI every journalist should know

Leave a reply

Tools like ChatGPT might seem to speak your language, but they actually speak a language of probability and educated guesswork. You can make yourself better understood — and get more professional results — with a few simple prompting techniques. Here are the key ones to add to your toolkit. (also in Portuguese)

Prompt design techniques for genAI Role prompting One-shot prompting Recursive prompting Retrieval augmented generation Chain of thought Meta prompting Negative prompting
Continue reading →

What are we talking about when we say the “ethics” of AI and journalism?

Leave a reply
A path forking into three
There are three broad paths in ethics. Image by pfly CC BY-SA 2.0

Many people — including me — are quite uncomfortable with generative AI. Most of this discomfort can be traced to the various ethical challenges that AI raises. But an understanding of the different schools of ethics can help us both to better address those challenges and what to do about them.

Three different ethical approaches

The first thing to say about the ethics of AI is that there is no single ‘ethics’. When we engage with ethical issues there are typically at least three different systems that might be in play:

Continue reading →

Identifying bias in your writing — with generative AI

Leave a reply
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 latest in a series of posts on using generative AI, I look at how tools such as ChatGPT and Claude.ai can help help identify potential bias and check story drafts against relevant guidelines.

We are all biased — it’s human nature. It’s the reason stories are edited; it’s the reason that guidelines require journalists to stick to the facts, to be objective, and to seek a right of reply. But as the Columbia Journalism Review noted two decades ago: “Ask ten journalists what objectivity means and you’ll get ten different answers.”

Generative AI is notoriously biased itself — but it has also been trained on more material on bias than any human likely has. So, unlike a biased human, when you explicitly ask it to identify bias in your own reporting, it can perform surprisingly well.

It can also be very effective in helping us consider how relevant guidelines might be applied to our reporting — a checkpoint in our reporting that should be just as baked-in as the right of reply.

In this post I’ll go through some template prompts and tips on each. First, a recap of the rules of thumb I introduced in the previous post.

Continue reading →

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

2 Replies
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.

Continue reading →

Using generative AI as a scraping assistant

Leave a reply
Applications of genAI in the journalism process Research Pyramid with the second 'research' level highlighted: Scope diverse sources, explore documents, form advanced searches, and write/fix code for scraping and analysis
Scraping is part of the research phase of a project

In the fourth of a series of posts from a workshop at the Centre for Investigative Journalism Summer School (the first part covered idea generation; the second research; the third spreadsheets), I look at using generative AI tools such as ChatGPT and Google Gemini to help with scraping.

One of the most common reasons a journalist might need to learn to code is scraping: compiling information from across multiple webpages, or from one page across a period of time.

But scraping is tricky: it requires time learning some coding basics, and then further time learning how to tackle the particular problems that a specific scraping task involves. If the scraping challenge is anything but simple, you will need help to overcome trickier obstacles.

Large language models (LLMs) like ChatGPT are especially good at providing this help because writing code is a language challenge, and material about coding makes up a significant amount of the material that these models have been trained on.

This can make a big difference in learning to code: in the first year that I incorporated ChatGPT into my data journalism Masters at Birmingham City University I noticed that students were able to write more advanced scrapers earlier than previously — and also that students were less likely to abandon their attempts at coding.

You can also start scraping pretty quickly with the right prompts (Google Colab allows you to run Python code within Google Drive). Here are some tips on how to do so…

Continue reading →

Using generative AI as a spreadsheet and data cleaning assistant

1 Reply
Applications of genAI in the journalism process Research Pyramid with the second 'research' level highlighted: Scope diverse sources, explore documents, form advanced searches, and write/fix code for scraping and analysis
Spreadsheet analysis is part of the research phase of a story

Generative AI tools like ChatGPT and Gemini can be a big help when dealing with data in spreadsheets. In this third of a series of posts from a workshop at the Centre for Investigative Journalism Summer School (the first part covered idea generation; the second research), I outline tips and techniques for using those tools to help with spreadsheet formulae and reshaping data.

Whether you come across data as part of story research, or compile data yourself, chances are that at some point you will need to write a formula to ask questions of that data, or make it possible to ask questions (such as creating a column which extracts data from another).

If you find yourself coming up against the limits of your spreadsheet knowledge, then genAI tools can be useful both in breaking through those — while expanding your knowledge of functions and formula writing.

Writing spreadsheet formulae with ChatGPT or other genAI tools

Continue reading →

Investigative journalism and ChatGPT: using generative AI for sourcing and story research

Leave a reply
Applications of genAI in the journalism process Research Pyramid with the second 'research' level highlighted: Scope diverse sources, explore documents, form advanced searches, and write/fix code for scraping and analysis
Generative AI can be used at all points in the journalism process: this post focuses on the research stage

In the second of a series of posts from a workshop at the Centre for Investigative Journalism Summer School (read the first part on idea generation here), I look at using generative AI tools such as ChatGPT and Google Gemini to improve sourcing and story research.

Research is arguably the second-highest risk area (after content generation) for using generative AI within journalism. The most obvious reason for this is AI’s ability to make things up (“hallucinate“) — but there are other reasons too.

Continue reading →