[Editor’s note: The report on AI and Machine Learning in emerging markets was jointly prepared by International Media Support, The Fix, and El Clip. You can find the full version here. Over the coming weeks we will be sharing articles diving deeper into some of the issues raised in the report.]
Artificial Intelligence and Machine Learning are sometimes referred to as the media sector’s third wave of disruption. First came the web, then social platforms. Now these new technologies are fundamentally changing how media operate – how they gather data, create stories, promote content, monetize their audiences….
There has been a fair amount of panic about robots displacing journalists – as well as debate about the ethics of using AI and ML. However, the current research suggests the AI and ML story in media is one of augmentation rather than displacement.
“Machine learning, automation, personalisation, data analysis and natural language processing tools can supercharge the modern news media”, argues Charlie Beckett, LSE professor and head of the global JournalismAI project, in the foreword to the report.
“They can help boost your audience retention and revenues. They can do a lot of the difficult or boring work, leaving the human journalists to concentrate on adding creativity and judgement.”
More from The Fix: AI and journalism ethics: a conversation with Mirabelle Jones
But the current picture of how newsrooms are adopting (or building) AI/ML is a bit one-sided. Indeed, much of research on the topic to date focuses on larger, wealthier Western newsrooms – who are often on the forefront of innovation. This ignores the reality of the vast majority of media from emerging and frontier markets.
The current report, jointly prepared by International Media Support, The Fix and El Clip, aims to specifically address this gap. It focuses on media houses using varying degrees of AI, ML and Data Processing as part of their core business operations in 20 countries in Latin America and Central and Eastern Europe. The data was collected via deep dive case studies of 44 media outlets and over 33 hours of interviews with experts.
Disrupting publishing in emerging markets
The report finds that a growing number of media organizations in both LATAM and CEE are using AI/ML technologies across their entire value chain (see image below), albeit particularly for use cases focused on managing subscriptions, generating stories and automating content production.
Several organizations in the CEE region are aiming even higher, by creating solutions with global reach and scale. Third-party, AI-power solution providers like Deep BI (based in Warsaw and New York) already provide subscription management services to publishers around the world. The open-source platform REMP2030, currently being developed by Fat Chilli in Bratislava, aims to do so in the near future.
“In CEE, digital natives are embracing AI/ML solutions and the region has been produced a few AI/ML based third party solution providers with global reach or ambitions”, the report reads.
But also points to the risk of growing inequalities in access and utilization of these technologies. Over the course of the research, this point was underscored time and again.
At the heart of the rift between the AI-haves and AI-have-nots is the ability to attract, grow and retain talent. In this respect, media face an uphill battle. The transition to digital models, accelerated by the pandemic, means that all industries are frantically pursuing data scientists, engineers and developers with AI/ML skillsets.
This means media companies need to compete in terms of wages with significantly wealthier industries – a problem that is especially tricky in emerging markets where IT outsourcing industries are on the rise.
Arguably an equally challenging issue is creating the right environment to integrate digital staff and keep them interested. Many legacy newsrooms are insular – editorial staff don’t talk to, or even look down on other departments. But even welcoming organizations can struggle to create an exciting place of work for digital specialists.
“An unexpected problem to attract and retain top data and digital talent is that the challenges are too small,” Carl-Gustav Linden, a professor at the University of Bergen in Norway, explains. “The [digital specialists] get bored”.
More from The Fix: Artificial Intelligence in the editor’s seat
Interestingly, one of the key findings was that having digitally savvy leadership (especially founders), was a major factor in helping media get their AI/ML operations off the ground. This serendipity – having the right person at the right time, can kick off a virtuous cycle. They make sure departments talk to each other and understand what they are talking about.
The problem is that this is not an easy solution to transpose. Many newsrooms lack even basic knowledge of how new technologies work and what they have to offer. Editorial and commercial teams struggle to even explain in technical terms the types of problems they experience – the starting point for creating a useful AI-powered solution.
That is a huge challenge for both media organizations and the media development community in years to come. But it’s one worth investing in if we want the media sector to ride this next wave of disruption better than the previous ones.