Artificial intelligence is eating the news

When it comes to the news media, lot of AI headlines focus on copyright disputes or threats of further mass layoffs. But there is a less prevalent but more interesting thread of AI news experimentation worth paying attention to.

In the past several months, everybody and their dog has announced AI partnerships and strategies. I've been keeping a running tab of the eye-catching ones:

• The FT announced a content licensing deal back in April that allows ChatGPT to make use of "select attributed summaries, quotes and links to FT journalism in response to relevant queries".
• Le Monde & Prisa Media (owners of El País, Cinco Días, As, and El Huffpost) announced another content licensing deal with OpenAI in March.
• German media giant Axel Springer* announced a similar licensing deal with OpenAI back in December 2023 but also hinted at some in-house product development, re: "Axel Springer’s existing AI-driven ventures that build upon OpenAI’s technology".
• In July last year, Reuters announced its own AI initiative designed to make their video library more accessible to users, using machine learning tools to unlock "the ability to quickly find key people and moments within Reuters video output enabling quicker discovery, editing and publishing".
• In February, The BBC released a follow up to its principles of generative AI in the newsroom (released in October 2023) with an overview of 12 pilots it is currently running within its newsrooms. No external partners or service providers have been named.
• Semafor announced a partnership with Microsoft and OpenAI so its journalists "can use with the help of tools from OpenAI and Microsoft to provide readers with analysis and insights on breaking news stories".

These announcements come in two major themes.

First, the licensing of content that has (in all likelihood) already been scraped by OpenAI and other labs in order to feed AI datasets. There is a large ongoing lawsuit from The New York Times on this very issue. To train large language models, you need lots and lots and lots of text; there's quite some suspicion that LLM owners have been taking text whereever and however they can get it**. Large publishers own much of that text and feel aggrieved for missing the content licensing boat with social media platforms twenty years ago; I suspect the big LLMs will have a much harder time of it. It seems they agree with that assessment - hence them signing all these licensing deals. More will follow.

The second theme is perhaps more interesting: how can newsrooms improve their products and processes by using AI models? The impact of AI on the news industry is something that has prompted some very interesting pieces of research in the past few months.

First, the Columbia Journalism Review's "Artificial Intelligence in the News: How AI Retools, Rationalizes, and Reshapes Journalism and the Public Arena" from February. The author, Felix M. Simon , conducted 134 interviews with media people in 35 news organisations to gauge how AI is impacting their work and workflows. The whole report is fascinating, but one thing jumped out to me: AI will exacerbate the have and have-not dynamic that has become so prominent in the Internet-era of news production.

"Winners and losers will emerge. In fact, they already have. News organizations that have been able to invest in research and development, devote staff time, attract and retain talent, and build infrastructure already have something of a head start when it comes to adopting new AI technologies and developing new products and services in meaningful ways. These “winners” are also in a stronger position to demand better terms when negotiating with platforms and technology companies, e.g. regarding the release of news content to train AI technology. While major media outlets or publishing groups like News Corp, Axel Springer, or The New York Times can engage in direct negotiations with the likes of OpenAI, Google, or Microsoft, The Philadelphia Inquirer, Offenbach Post, or the Oxford Mail might not be so lucky."

The shift to online advertising was a death knell to local news and saw many once prominent outlets fall to ruin as they failed to adapt quickly enough. After this fall, we were left with a handful of legacy outlets who were able to adapt quickly enough, but it was local and smaller outlets that really suffered. Recent research from Northwestern University showed that nearly 3000 newspapers have closed in the past two decades and that roughly half the counties in the United States are down to just one, usually weekly, local news source. A comparative study [PDF link***] by Sofia Verza at the European University Institute highlighted similar trends in the EU, with decreasing revenues and declining numbers of local journalists noted across the 27 EU member states.

Even when the original Big Tech giants tried to make reparations for disrupting the media ecosystem, research done by the indefatigable Alexander Fanta showed that most of the media funding from tech companies was being funneled to the big players. We still don't have a model to replace this (as I have written about before) and it looks like the rise of AI will only make matters worse.

Second, and taking more of a scenario-planning perspective, Rasmus Kleis Nielsen released an essay on "how the news ecosystem might look in the age of generative AI" which explores some of the research around trust in media in the digital age and how that might impact AI experiments in the newsroom****. First, a warning:

"Many publishers will produce more content more cheaply in a world where the bulk of news as we know it is already, from the point of view of much of the public, demonstrably largely commoditised, generic, and highly substitutable, and therefore of little value in terms of willingness to pay attention, let alone pay. If publishers primarily use AI to produce more of the same more cheaply, they will further reduce the already limited commercial value of all but the most effectively differentiated news content."

News avoidance is a real and persistent phenomenon*****. Simply creating more low quality content at a lower marginal cost isn't going to move the needle - even if it cuts costs by allowing newsrooms to lay off ever more journalists.

In the short term, Nielsen suggests it is "unlikely that generative AI will have anything like the transformative impact the current hype suggests" (at least within news production) but it will lead to further cost cutting efforts. Having said that, is it really possible for AI to be that much cheaper than chronically underpaid journalists?

Those cost cutting measures are pre-emptive, to some extent, as publishers expect to see a continuation of revenue decreases. The recent announcement that Google AI is going to cannibalize media outlets' traffic is creating concerns (via Brendan Hodgson's excellent Substack): “‘This will be catastrophic to our traffic, as marketed by Google to further satisfy user queries, leaving even less incentive to click through so that we can monetize our content,’ Danielle Coffey, the chief executive of the News/Media Alliance told CNN.

During a panel at the UK Society of Editors Conference in April, the director of news distribution and commercial innovation at ITN acknowledged the problems such tools could present when companies outside of the media industry ran them. “I think it’s going to be really problematic for us all,” she said. “It’s not simply that they would use our copyright to build their models, but they’re actually going to develop their relationship with audiences by using our material without attribution and without driving traffic back to us.”

This all points to a vicious cycle of layoffs, automation, loss of trust and the further decline of news media. But that doesn't mean there aren't opportunities for newsrooms who have a definitive AI strategy, as Nielsen puts it:

"AI may be helpful for those publishers who are able and willing to define and double down on what makes them different, who are genuinely interested in meeting people where they are, and who can resist the temptation to further commodify the journalism they offer."

This chimes with something Jim Vandehei - Politico and Axios co-founder - said on a podcast recently regarding the coming explosion of AI:

"For me, as someone running a media company, what does that mean? How would people be getting news and information? And the conclusions we came to is even if that’s the case, people are still going to need human expertise, human sourcing... In essence, media companies shouldn't try to compete with tech companies on synthesizing information or on speed of its delivery to consumers - Big Tech wins on that, every time. What they need to do is invest in personalities that people trust and are drawn to."

As somebody who tries to make use of media personalities to influence policymakers, this chimes with my experience.

Most people aren't persuaded by the FT writing about something; they're persuaded by that smart reporter at the FT writing about something. No doubt there is still a halo effect from big name, trusted media outlets, but ultimately the really influential journalists are influential individuals on their own merit. When they move to another outlet, they'll remain influential.

Interestingly, this converges with many strategy discussions in the world of think tanks and advocacy orgs. Our main assets, too, are our experts. It's their standing, their connections, their persuasiveness that helps us move the needle. Much of my thinking as I'm building up the comms and PA offering at Centre for Future Generations (CFG) is centered around how we, as an organisation, can provide extra value to our experts, partly to help them be more influential on our behalf and partly to make them want to stay put for the long term.

While news publishers may not quite have the experimentation budgets to match Big Tech, they operate at a different order of magnitude to most advocacy organisations. So I'm going to be watching the AI experiments of Axios, the BBC and various others extremely closely - this is a rich well of innovation for the policy comms community to draw from.

This is part of a monthly series aimed at examining the underlying narratives of European affairs, with a healthy dose of media criticism along the way. Read the previous article here.

Note that these are personal takes and do not represent the position of my employer.

*I wrote about the impact and trajectory of Axel Springer's most prominent Brussels outlet, Politico Europe, earlier this year.

**News publishers aren't the only aggrieved parties. A number of comedians, writers and artists have also filed lawsuits in the past year - see this overview for more.

***Not to get on my soapbox but... It is wild to me that we're in the year 2024 and major research centres still rely on PDFs to distribute their work. My organisation is less than a year old and I am hard at work eliminating PDFs from out outputs - the fact established universities haven't dropped this format, invisible to Google, is frankly insane. It makes me think of the thunderously effective meta-study from the World Bank, now ten years old, which showed that more than 31% of its own reports were never downloaded and almost 87% were never cited. Ban PDFS! Free your content!

****Worth noting that Nielsen also echoes the finding of the CJR study: "the decline of most publishers’ commercial revenues and societal relevance will only be further accelerated by generative AI".

*****This has been a frequent topic of mine on here but was probably most core to this essay from February 2023.