Journalists and publishers haven’t had it easy in recent years. The heady days of thirty years ago with coffee shops full of readers brimming with physical copies are gone forever. The move online turned the industry on its head, with unexpected consequences. This began with competition from online content creators, but has moved into an altogether different direction following the introduction of machine learning algorithms.

How did we get here

Newspapers were often heckled for being slow to move online, but it would be hard to argue that now. They are simply faced with a difficult position where anyone can generate competing content instantly, and for free. What's more, the online advertising methods they use are typically deemed invasive by readers, leading to the use of advertising blockers and lowering the appeal of trusted media sites.

It is a challenge that has been made all the more difficult by shifts in the way ‘news’ is consumed. It is now expected for news to break on social media. This reduces a media outlet’s appeal, changing its focus and increasing the need for greater scrutiny in the reporting process.

And fact verification is no easy task, as epitomised by reporter John Carreyrou’s book Bad Blood. In it, he explains how many media outlets, including his own, were reporting favourable but largely unsubstantiated news at the time of his investigative research into medical startup Theranos.

Why machine learning is so disruptive

This brings us onto why now is such a pivotal moment. Well, despite having a difficult business model to pull off, journalists had one strength up their sleeve. They were devoted to news coverage. This meant having a full and constant eye on it, making them able to place one announcement in context with another. This added an intangible quality to their reporting, a quality that content marketers would struggle to replicate.

Yet, this strength is being eroded by machine learning algorithms, which select the stories to cover. It is a crucial turning point as it removes the need for journalists to have a complete picture of day to day announcements. It also changes the career opportunities available to them, as journalists often aspire to become editors. Further still, it presents a bleak outlook for the steady stream of graduates looking to follow in their footsteps.

Of course, this is before the inherent bias within algorithms is taken into account. We are all constantly micro-manipulated by advertising algorithms. If all news follows the same process, it's likely to have significant societal consequences.

Establishing the impact on job losses

There is striking evidence to suggest the algorithms are coming. Notably, as we’ve analysed previously, publishers are laying people off because of the pandemic’s impact. Quartz has cut 40% of its workforce, Economist has cut 7% and Vice has cut 5%.

This has increased the appeal of machine learning as a means to gaining greater efficiency. Vice’s Nancy Dubuc is quoted as saying Big Tech is “posing a great threat to journalism”, inspiring this blog. Further still, just a few days later, Microsoft decided to replace more than 75 editorial staff with machine learning (The Verge). Although MSN News and Microsoft News are hardly mainstream press, the announcement sent shockwaves through the industry.

And the pandemic is merely symptomatic of the state of travel for the industry. BBC delayed 450 redundancies to make sure it could adequately cover the Covid-19 crisis. Meanwhile, stalwarts such as The Sun and The Evening Standard are both fresh from laying off people in 2019.

And the wider impact on content creation

This impact is of course being felt within the PR industry too. PR people are a crucial part of the machine, feeding journalists with stories. This fragile and often tempestuous relationship is also an essential one. Journalists must use their nous to evaluate the hundreds of pitches they receive a day.

Handing this task over to an algorithm reduces the opportunities for PR people to shape a pitch, a move that has forced many agencies to diversify their offerings. This in turn furthers the challenge journalists have to cut through against carefully crafted content marketing pieces and social media campaigns.

Any upside?

Of course, you may be thinking there’s always an upside. We do too. The beauty of good journalism is not knowing whether it is likely to stoke the public’s interest. It is this intangible quality that separates a great journalist from an also-ran. Perhaps machine learning could be trained to promote journalists that possess this intangible quality and ensure that more people are exposed to the highest quality pieces, a feat that would help us all navigate the internet.

We hope you’ve enjoyed this blog. If you would like to read about all the brands that made redundancies up to June, then we’ve conducted a full analysis. Remember, we are not paid for any recommendations. We believe impartiality is crucial.

Until next time.