Risks

technical, ethical and business issues that could go wrong

This card covers the technical, ethical, and business problems that could go wrong with your AI tool. Naming risks early is not pessimism, it is how you avoid surprises that damage a story or the newsroom's credibility. Some risks you can reduce, and others you simply need to watch.

Questions to explore

// use these as prompts in a workshop or on your own. There are no right answers.

What is the worst that could happen if the tool gets something wrong in a published story?
Where could the tool introduce bias or unfairness into the newsroom's work?
What would a mistake cost in reader trust, not just in time or money?
Which risks can you reduce, and which do you just need to monitor?
How would you know early that something is going wrong?

Expert voices

// notes from the journalists and AI experts who helped shape this kit

“Have a list of what could go wrong and how you will mitigate it. Things will go wrong; turn failure into lessons and rules.”

Zenzele Ndebele, Centre for Innovation and Technology (CITE)

Things to consider

An error in a tool can become an error in a story, so weigh that cost.
Reader trust is hard to rebuild once a public mistake lands.
Decide in advance who responds when something goes wrong.

using this card

Pull Risks when it is relevant and set it aside when it is not. Pair it with the other AI Solutions cards, lay them out on a table, and use the questions above to get everyone on the same page. Capture what you discuss on sticky notes or in a shared doc.