The algorithm knows what you want, but journalism must know what really matters

Every time we open a digital platform, an algorithm is making decisions for us. It learns what we watch, what we skip, what we search for, how long we stay and what brings us back. Over time, it becomes remarkably good at answering one question: What are you most likely to watch next?

But journalism has to answer a very different question: What do you need to know? That distinction, I believe, will become increasingly important to the future of news, and on World News Day, it is a conversation worth having.

There is a fundamental difference between predicting what someone wants to consume and deciding what deserves their attention. There is nothing inherently wrong with personalisation. In fact, technology has made news more accessible, immediate and relevant than ever before. But if news becomes entirely optimized around individual preferences, the most important story of the day may not always be the one that reaches you and we risk creating millions of personalized versions of reality.

That creates an interesting paradox: we have never had access to more information, yet we may increasingly experience less of the world outside our individual preferences.

Good journalism must break that bubble.

It must go beyond what captures our attention to what deserves our attention - the stories that shape our communities, our economy, our country and the world around us. Its responsibility is to tell you something you may not be searching for. To ask an uncomfortable question. To put an event into context rather than reduce it to a clip. And occasionally, to tell you that what is going viral is not actually the most important story of the day.

This is where the newsroom continues to matter.

Behind credible journalism is not simply a content engine. There are reporters on the ground, editors questioning information, producers checking facts and people taking responsibility for what ultimately goes on air or gets published. Technology can strengthen that process, but it should not replace the accountability behind it.

That is why I see AI as a co-pilot, not the editor.

AI can help newsrooms analyse information faster, identify patterns, support research, translate and regionalise content, create summaries and personalize how stories reach different audiences. Used well, it can free journalists from repetitive processes and give them more time to do what technology cannot easily replicate - report, investigate, ask the right questions and exercise judgement.

Thus, AI can make journalism faster, but speed cannot become a substitute for judgement. Human judgement must still ask: Is it credible? Why does it matter? What is the context? What are we missing? And what are the consequences of getting it wrong?

Television has long built its relationship with audiences on this institutional credibility and accountability. Digital has transformed the speed, accessibility and reach of news. Today, the same viewer moves seamlessly between television, social media, connected TV, video platforms and mobile. The opportunity is to take the credibility and accountability associated with a trusted newsroom and make it travel across every screen.

AI can help us reach the right person, in the right language, on the right platform, at the right moment. But it should not decide, on its own, what society considers important.

As AI capabilities become widely available, speed, automation and even personalisation will become easier to replicate. Trust will not.

Trust is built story by story. It comes from getting the facts right, acknowledging when we get something wrong, separating information from noise and having the courage to prioritize significance over popularity.

On World News Day, that distinction is worth remembering.

The algorithm may know what you want. The enduring responsibility of journalism is to know what really matters - and to earn your trust when it tells you why.