The media is sleeping on AI

Media & Technology have been inexorably intertwined since the advent of radio in the early 1900s. Often though, the media is slow to adapt and is often one of the first victims of the forces of disruption.

Personally, I've taken advantage of this lag, intentionally moving away from TV & Radio into digital in the early 2000s, then away from the news industry entirely and into sport, following the money. Eventually I moved into the building of products and the technology itself as a way of staying fresh – and to continually feed my insatiable appetite for curiosity and emerging trends.

But the arrival of Artificial Intelligence (AI) – and at such a breakneck speed – has made one thing certain: this technology is leaving an indelible mark on the world of the media. While these emerging tools are inching their way into newsrooms and content creation workflows, the mainstream media – and particularly traditional broadcast media – seem unprepared for how drastically things are about to change.

The arrival of the Google's Pixel 9 phone has brought with the ability to manipulate photos on the fly with incredibly realistic results. In a world where so much of the nightly news on our commercial networks is driven by photos and videos captured on our phones, the lines are about to blur to a point where this content will no longer become reliable. In a new paradigm that began with Donald Trump crying out 'fake news!' on reporting he disagreed with, being able to throw compelling photos (and soon video) onto this dumpster fire is going to make truth-telling far far more complicated.

Photos have changed the world multiple times over the past 120 years - what happens now? Or as succinctly put here - we are fucked.

Can tech can be part of the solution?

Any attempt to hold back these AI advances is now futile; the genie is absolutely out of the bottle. It's time to lean in. And there are opportunities to use tech to help.

Blockchain is an incredibly powerful tool that can be used as a transparent way to verify the sources of content. After inadvertently publishing misinformation during the Covid-19 pandemic, an Italian news agency worked with EY to build a blockchain-powered solution that allowed readers to readers to trace the origin of the agency’s stories and track each one through its entire history of updates and reposts on third-party news websites. Something that would have been useful in trying to quell the recent race riots across Britain.

However the very nature of journalism itself is likely to change, dramatically.

We're already seeing journalists using AI for tedious tasks like interview or podcast transcriptions, data analysis, and even initial drafting, all done with lightning speed and precision by intelligent algorithms. A recent study from the Associated Press has revealed nearly 70% of staffers are using these tools to help craft social media posts, newsletters & headlines. This would make sub-editors of old red with rage to see that great craft of headline writing handed over to the machines.

There is an argument that these tools would free up valuable time for journalists to focus on the art of storytelling, deep investigative reporting, and delivering incisive, context-rich narratives to their audiences.

We're also seeing news organisations harness the power of AI to enhance productivity and personalisation. The Associated Press, for instance, has been using natural language processing models to generate thousands of stories on topics like corporate earnings and sports recaps. The end product may lack the nuanced touch of a human writer, but it nonetheless provides readers with a steady stream of factual information in a timely manner.

Again, there's a clear counter-argument here that writing these articles play an important role in teaching the craft of journalism to cadet reporters and others new to the industry. But is this still valid in an AI-driven world? Does the very nature of journalism and how it is practised take on a whole new meaning?

I'm not sure we are quite there yet, because the fears and risks of AI in journalism are clear. These technologies can create echo chambers, amplify biases, and erode the fundamental tenets of human editorial judgment. Remember, the Large Language Models (LLMs) and algorithms powering these AI tools are, at their core, a reflection of the data and assumptions fed into them by their human creators. And lets be honest, the Internet isn't exactly a shining example of the human experiment, and a quick search outlines a healthy roster of AI disasters. If that data remains skewed or the underlying biases go unchecked, the outputs could reinforce harmful narratives or fail to surface crucial perspectives.

Some academics are clear in their fears that LLMs pose a genuine risk to society and regulation is urgently needed to ensure this technology adheres to basic tenets of truth, accuracy and fairness.

Associate Professor and Research Associate Dr Chris Russell at the Oxford Internet Institute goes even further, saying in this paper:

'While LLMs are built so that using them feels like a conversation with an honest and accurate assistant, the similarity is only skin deep, and these models are not designed to give truthful or reliable answers  The apparent truthfulness of outputs is a ‘happy statistical accident’ that cannot be relied on.'

While regulation may be urgently needed, governments are notoriously ill-equipped to move quickly enough to stay ahead of this rapidly moving technology. In the meantime we are left to fend off a network of AI-powered misinformation and weapons of misdirection. Given the impact of misinformation on some recent elections, it will be a difficult path to navigate for the immediate future.

As we look to the future, the next decade in AI-driven journalism will likely see a continued push towards automation and personalisation. Newsrooms will harness AI to track and analyse audience engagement patterns, optimise content distribution, and tailor the news experience to individual preferences. But the true test will be in striking the right balance – leveraging the speed and efficiency of AI while preserving the human judgment, ethical oversight, and commitment to truth that has long defined the journalistic profession.

The path forward will require a concerted effort from news organisations, technology providers, and policymakers to develop robust ethical frameworks, transparent algorithms, and rigorous fact-checking mechanisms. Only then can we ensure that AI serves as a tool to empower journalists, rather than a threat to the very essence of their craft.

In the meantime – cast a critical eye over that content on news sites and socials – because there's every chance that what you're seeing isn't real.