Category Archives: AI

How to reduce the environmental impact of using AI

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Generative AI: reducing environmental impact Disable AI or switch tool Compare AI vs non-AI Compare models Prompt planning Prompt design and templating Measuring and reviewing Run locally

One of the biggest concerns over the use of generative AI tools like ChatGPT is their environmental impact. But what is that impact — and what strategies are there for reducing it? Here is what we know so far — and some suggestions for good practice.

What exactly is the environmental impact of using generative AI? It’s not an easy question to answer, as the MIT Technology Review’s James O’Donnell and Casey Crownhart found when they set out to find some answers.

“The common understanding of AI’s energy consumption,” they write, “is full of holes.”

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9 takeaways from the Data Journalism UK conference

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Attendees in a lecture theatre with 'data and investigative journalism conference 2025 BBC Shared Data Unit' on the screen.

Last month the BBC’s Shared Data Unit held its annual Data and Investigative Journalism UK conference at the home of my MA in Data Journalism, Birmingham City University. Here are some of the highlights…

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Teaching journalism students generative AI: why I switched to an “AI diary” this semester

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The Thinker status
Image by Fredrik Rubensson CC BY-SA 2.0

As universities adapt to a post-ChatGPT era, many journalism assessments have tried to address the widespread use of AI by asking students to declare and reflect on their use of the technology in some form of critical reflection, evaluation or report accompanying their work. But having been there and done that, I didn’t think it worked.

So this year — my third time round teaching generative AI to journalism students — I made a big change: instead of asking students to reflect on their use of AI in a critical evaluation alongside a portfolio of journalism work, I ditched the evaluation entirely.

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

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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.

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

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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.

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7 prompt design techniques for generative AI every journalist should know

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

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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:

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Identifying bias in your writing — with generative AI

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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.

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

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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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