The growing demand for information during the pandemic has not been met with an adequate increase in journalistic resources. In fact, the opposite has been true. According to the Poynter Institute, in the US alone over 33,000 journalists have been laid off, furloughed, or given pay cuts as a direct consequence of the coronavirus, resulting in a reduced capacity to cover fundamental public health issues. Despite the dire situation, the crisis has shown a secondary, positive side effect: accelerating the speed of journalistic innovation.

Take the case of British local wire service Radar AI. The joint venture between Press Association and Urbs Media leverages machine learning to dynamically generate regionalized COVID-19 news digests, distributed to local news media in the UK.

“In May alone we produced 17,000 local news stories. We realized that we had an important role to play in helping our subscribers tell that story to readers at a local level. Usage of AI-driven content by our subscribers have been at record levels throughout, climbing each month since April.”

Gary Rogers, co-founder, and Editor in Chief, Radar

Covid’s impact on ad revenues

But this accelerated tech adoption on the newsgathering side is not enough to alleviate the immense pressure local news industry faces, exacerbated by a steady decline in advertising revenues. According to FTI Consulting, newspaper ad revenues in Q2 of 2020 have declined by 20%–30% compared to the same period last year.

“The challenge is that there has been no market response to the growth of digital information. In particular local advertising has collapsed, I would say disappeared, as a result of the financial crisis in the sector. A long and serious economic crisis awaits us.”

—Stefano De Alessandri, CEO and Managing Director
of the Italian news agency, ANSA


A weakened local news ecosystem leads to a public that is less informed, which is problematic, especially during a pandemic, where analysis of public health data is essential for many communities to stay up-to-date on the virus’ impact on their towns and local health care systems.

The ultimate data story

Elsewhere in the industry, other news leaders recognize that coronavirus represents an inflection point for journalism. In fact, this pandemic is the “ultimate data story,” as Bloomberg senior executive editor Chris Collins explained in a recent conversation with the London School of Economics JournalismAI research initiative. Indeed, Bloomberg is one of many organizations using AI alerting systems to monitor social media and other data sources for coronavirus related insights to notify reporters as soon as a trend or anomaly emerges from data.

British Philosopher Alain de Botton’s thought-provoking description of journalism as “the determined pursuit of the anomalous” is taking on a literal meaning, as news organizations race to adopt algorithmic practices. Statistical outliers in the data help anticipate newsworthy events, leading journalists to their next story: Where is the next Covid-19 outbreak going to be? Will the healthcare infrastructure be prepared to deal with an influx in patients?

News organizations have been looking for signals in data for a long time by analyzing movements of stock indexes and deducing their potential impact on the economy. What has changed is that journalists now have a multitude of data indexes — measures of ground truth — at their disposal, and powerful AI tools to derive insights. During the Covid-19 pandemic, reporters have been using economic data and health metrics across countries, regions, and cities to find the next outliers of this ongoing story.

“This crisis changed our business. Key areas where we’re focusing on such as sports coverage became obsolete within days of the pandemic disrupting normal life. We had to reinvent our business and focus on creating value for our customers, namely providing Covid-19 content.”

David Llorente, CEO of A.I.-powered news agency, Narrativa

Alternative ways to contextualize reporting

Leading health news publication STAT News which has grounded some of its reporting on data tools including our Covid-19 tracker and the County Health Preparedness score, which estimates the impact of the pandemic on the healthcare system by leveraging public data and statistical models. This new measurement derived through data science developed by Applied XL and data from the Center on Rural Innovation is not only providing context to STAT’s reporting; it is also being leveraged by organizations such as US News & World Report and FOX News to quantify the impact on health infrastructure in rural areas.


“The beauty of this use of data is that it speaks for itself. It’s essentially unfiltered so readers can explore and interpret and analyze the information themselves in real-time. As much as we write critical news and feature stories on Covid-19, our tracker has been vital in helping readers grasp the enormity of a public health crisis whose scope and scale sometimes seems beyond comprehension.”

Rick Berke, co-founder and executive editor, STAT News


Newsrooms are quickly identifying new ways of contextualizing information beyond traditional metrics. For example, digital publication Axios is using data on the share of beer taps pouring at open locations to measure consumers’ confidence about reopening cities amid the pandemic.

This form of data-led reporting through alternative indexes is here to stay after the pandemic ends, with ever-growing data sources that extend to other parts of news organizations’ coverage: transportation, housing, local economy, law enforcement, education, and more.

Bridging the innovation gap in small newsrooms

Local news organizations can take advantage of open-source data analysis tools and free online courses for journalists to leverage machine learning libraries for reporting. Collaboration with other newsrooms and partnerships with academic institutions to share knowledge and resources can also accelerate the pace of adoption. London School of Economics’ media think-tank Polis, for example, recently announced a partnership of more than 20 international news organizations to prototype AI-powered journalistic solutions and discuss the impact of AI on journalism during the Covid-19 pandemic.

Stanford University’s Big Local News

“Given the importance of data in telling the story of COVID19, both nationally, and locally, there are some interesting ways to leverage automated content production to bolster local news about the crisis. A nice example of this is the Big Local News Case Mapper, which offers an embeddable map and chart that local outlets can use. There are perhaps untapped opportunities for AI to be applied here as well, such as to detect and alert reporters when particular locations exhibit spikes in cases or have a worrisome trend.”

Nick Diakopoulos, computational journalism professor, Northwestern University


By leveraging data science and artificial intelligence, news organizations will be able to provide in a more effective manner with real-time data of events and information catered to a reader’s specific city or neighborhood. In an industry beset by declining revenue, local news on public health can indeed become a crucial entry point for driving audience engagement and future revenue.

Author’s note: for more on how AI is changing and journalism, check out “Newsmakers: Artificial Intelligence and the Future of Journalism.”

A version of this article was previously published here.