A less than 40-person newsroom in Hong Kong. A 3-person newsroom in Mexico. A 10-person newsroom in Lebanon. Besides their relatively small team sizes, they all have one other thing in common – high AI adoption ambitions.
Initium Media in Hong Kong would like to deploy an AI-based social media listening tool that analyses and provides more than just keywords.
DataCrítica in Mexico is already deploying AI for investigative stories, specifically using NLP and entity extraction.
Maharat News in Lebanon is developing an AI-based social media monitoring software that can be used in English and Arabic.
While these newsrooms recognise the importance of deploying AI, they also acknowledge that the road to adoption is not easy for smaller news organisations like them.
It begins with access to talent and the global tech workforce shortage.
In the UK alone, for instance, about 518,000 additional workers will be needed to fill the three highest skilled digital roles by 2022. As the use of AI across industries heats up, news organisations are now competing with tech companies, government and other industries for a shrinking pool of talent.
This makes things doubly difficult for smaller news organisations, especially those from emerging economies.
“The world is polarised in a way in which the Global North controls technology. Naturally, the place where the first AI teams and the first data visualisation teams were born, closest to us, is in the US. This model of controlling the technology and being able to build teams around it, is not something that applies to our reality.” explains Gibrán Mena, director of DataCrítica.
DataCrítica is an investigative journalism outlet. All of DataCrítica’s three journalists, for instance, have a humanities background. All three learned to code from scratch to solve the talent acquisition issue and now conduct investigations using AI technologies. Other organisations, like Maharat News, outsource programming tasks based on project requirements.
“The world is polarised in a way in which the Global North controls technology. Naturally, the place where the first AI teams and the first data visualisation teams were born, closest to us, is in the US. This model of controlling the technology and being able to build teams around it, is not something that applies to our reality.”- Gibràn Mena, Director of Data Crítica
Some news organisations in Latin America are replicating larger newsrooms’ model of building separate teams of reporters, programmers and data scientists who can work together. But, not every organisation has the capacity to do that.
The lack of dedicated team members focusing on AI could deeply impact the AI adoption journey of a news organisation. For example, this could lead to a lack of good data management practices.
“Local newsrooms sometimes don’t have great systems for managing data. They don’t get to the point of structuring it or using it to come up with ideas.” says Lisa Gibbs, Director of News Partnerships & AI News Lead at the Associated Press.
In organisations that are AI ready, employees with AI expertise advise on the data acquisition process. They help them acquire a greater variety of data sets and types. They also have a greater ability to link and analyse the data they collect. This ensures that companies have good data to work with as they build AI solutions.
Much of this also rests on costs involved in recruitment, maintenance and deployment.
Take deploying AI for data analysis and to develop tools for reporters, for instance. This costs some organisations about $ 1 million per annum.
Despite their ambitions, the team at Initium Media remains wary about the cost factor:
“There’s no way I can convince my management about the costs involved in implementing AI. It’s impossible to allocate investments on this kind of projects if short-term results are not guaranteed. If it’s one specific project that guarantees results, we might try it.” explains Ning Hui, senior journalist for international news at Initium Media.
“However, if the solution involved is very costly, even if it might be useful down the line, there’s no way we would be able to do it without financial assistance.”
When organisations are also fighting an existential battle to stay in business, the costs involved in developing and implementing AI make them naturally averse to taking risks and less willing to try new technology, says Gibbs.
Finally, there simply aren’t too many newsroom-specific AI adoption playbooks available to learn from.
“Adopting AI is an experimental business. In the end, it’s possible that the solution doesn’t meet the initial goal set out for it. This needs to be acknowledged. The adoption of AI needs to come with a clear methodology so that outcomes can be met as accurately as possible.” says Layal Bahnam, a program manager at Maharat News.
There are possible solutions that could help in democratising AI for all newsrooms, and those often start with collaboration.
Gibbs encourages newsrooms to take part in international collaborative initiatives between news organisations like the JournalismAI Collab Challenges (now JournalismAI Fellowship). Another option is to collaborate with academic institutions that often have more time and resources to develop AI solutions. Early research shows that collaborations like these can increase organisations’ resilience and rewards.
“Adopting AI is an experimental business. In the end, it’s possible that the solution doesn’t meet the initial goal set out for it. This needs to be acknowledged. The adoption of AI needs to come with a clear methodology so that outcomes can be met as accurately as possible.”
- Layal Bahnam, a program manager at Maharat News
JournalismAI has also developed an AI Academy for Small Newsrooms that journalists can take part in for free. (The 2022 cohort will soon be announced.)
In the US, Gibbs and her team at AP have recently received a Knight Foundation grant to help local newsrooms overcome barriers to AI adoption via a series of Readiness Workshops.
One thing is clear though: despite the many hurdles, giving up on AI adoption is not an option for most of these news organisations.
Small and local news organisations already face additional challenges, with tech platforms’ algorithms deciding which content shows prominently on a news feed, says Ning Hui. Resisting the AI journey would mean giving up further competitive edge.
“Long-term, if we don’t keep up our unique ways of engaging with audiences, then sooner or later more massively produced content or bigger newsrooms positions will be affirmed, causing smaller newsrooms to disappear.” adds Ning Hui.
Keeping up with advancements in AI is important for the survival of an organisation, she says. This applies to local outlets as well as digital-native news organisations that cover niche news, filling in the gaps left by mainstream media.
“To make the landscape sustainable, diverse, and with more voices, smaller newsrooms need to stay at it. Otherwise, it’s not going to be a good future we’re looking at.”
This article was written by Lakshmi Sivadas, JournalismAI Community Coordinator.
JournalismAI is a project of POLIS – the journalism think-tank at the London School of Economics and Political Science – and it’s powered by the Google News Initiative.
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