Newsroom AI Insight

JournalismAI Collab Challenge

Over the next few months I’m going to be collaborating with the Polis team at LSE, BBC News Labs and many others, to lead an exciting Journalism AI collaboration focused on finding new ways to tell news stories using artificial intelligence. I’ll be representing Clwstwr, who are supporting me as part of my News Storytelling R&D work. Below, I outline why I think this work is so important, and why collaborating is the best way to do it.

The first phase of my News Storytelling R&D threw up surprising, exciting and radical new ideas that have attracted really gratifying attention from around the world. The project turned out very differently from how I first envisioned it, but that just goes to show that research is a dynamic process – the more you find out, the more you start to see new paths, approaches and potential outcomes. 

It was a really successful project in many ways, but it’s always important to critically analyse your own work, and think about how it might be improved in the future. It was something I needed to do before setting out on the second phase of my research. The biggest problem was something I’d known all along – R&D projects like my work in news storytelling are normally carried out by multi-disciplinary teams with a range of editorial, technical and design skills and experience. My work was largely just me, sitting in my spare bedroom, trying to figure things out. I often felt the lack of people to bounce ideas off, to learn from and to challenge my perspectives. There’s also the fact that “you don’t know what you don’t know” of course. Maybe I was restricting my ideas to the envelope of things that I believed to be possible, but working with other people could have opened my eyes to bigger and better opportunities.

It would be easy to think of the research that led to my “7 Building Blocks of Reflective Journalism” as just lovely abstract thoughts that aren’t grounded in the real-world cut and thrust of newsrooms. That would be wrong for a couple of reasons – firstly, my research was built on more than 25 years’ experience across all of the UK’s major broadcast newsrooms, in pretty much every role – from directing and vision mixing, to shooting and editing on the road, to programme editing on network news. 

Secondly, I always had an eye on how my work might be modularised and automated – in order to produce effective journalism at scale. I also believe modular journalism (the process of breaking down “stories” into small units of information that can be put together in different ways across platforms and formats) is potentially more inclusive and trustworthy than traditional news stories. That’s because it’s the (largely superfluous) interstitial writing that glues together legacy journalism that also contains all the journalists’ or organisations’ biases. Modular “units” of journalism are also MUCH easier to translate into multiple languages than more wordy traditional writing. This is really important if we truly want to reach all audiences and fill information gaps,  and this is exactly why my work is very hard-nosed on the potential for AI and machine learning to help us do more and better journalism.

Finally, I also came to another realisation about myself, that really I’d understood all along. One of the possible outcomes of R&D is of course that you create intellectual property that can be monetised, or exploited in other ways. The other side of that coin is that you have to protect that intellectual property and restrict access to it, essentially to those that are willing and able to pay for it. What I realised was that that approach doesn’t interest me in the slightest. 

With one of my other “hats” on, I’m a Community Organiser at The Bureau of Investigative Journalism, and in everything I do I’m committed to building better journalism produced with and for communities and it’s the best and most important job I’ve ever had. I just want journalism, and the world, to be better. I want to find ways to build public interest journalism that reaches everyone and tells stories in ways that are inclusive, informative and engaging. My mantra is that “journalism is for citizens, not journalists”, and it’s obvious that I wasn’t going to be able to build that better journalism by working alone and focusing on how best to make myself rich!

That’s why working with the team at Polis on their JournalismAI Collab Challenge feels like such an important opportunity to build exactly the kinds of relationships that I think we need more of, in both journalism and society. I think many of us are starting to realise that we can achieve more in collaboration than we can in competition and we need to find imaginative new ways to do that.

I’m really looking forward to working with the team at Polis, BBC News Labs, NorthWestern University’s Knight Lab, and collaborators from all over the EMEA region over the next few months. If you want to explore how we might use AI to tell new stories in new ways, then you can read more about the work of the JournalismAI team here.

Has this sparked ideas for you?

Do get in touch if you want to pick up on any of these thoughts.

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