How Europe is handling robo-journalists in the AI age
The Council of Europe has recently adopted key resolutions concerning AI and its intersection with media and journalism.
Should computers write the news? What about AI-controlled newsfeeds? If AI tools remove deliberately misleading information, is that an infringement of freedom of expression, or does it protect public discourse?
During the recent Council of Europe Ministerial Conference (10 and 11 June), a final declaration and four resolutions were adopted to address these worries.
The resolution domains included digital technologies, safety of journalists, the changing media and information environment, and the impact of the Covid-19 pandemic on freedom of expression.
This short sentence belies the scope of the concerns and the magnitude of what they address.
The press release from the council specified the need for “regulatory conditions surrounding automated processes for creating and disseminating news, including natural language processing (NLP), robo-journalism and algorithmically prepared newsfeeds”.
The examples provided by the council aren’t arbitrary but represent three major areas of concern.
A 37-page document on the implications of AI-driven tools on the media served as a basis for much of the discussion of the two-day conference. Written by Prof Natalie Helberger, associate professor Sarah Eskens and three other colleagues, the report addressed the implications of AI for freedom of speech.
In their paper, they discuss AI tools used by journalists (NLP), AI tools replacing journalists (robo-journalism) and AI tools that affect the spread of journalism (newsfeeds).
First off are the AI-driven tools, which usually aim to help journalists sift through vast amounts of information.
Picture the prototypical political journalist, Robert Caro, in his writing of the 1974 Pulitzer-winning biography The Power Broker.
In researching the infamous New York politician Robert Moses, Caro spent years trawling through the New York Public Library and its documents to write his 1,162-page opus.
In the age of NLP and digital documents, AI aims to cut this process to an afternoon.
NLP exists at the intersection between computer science, linguistics and artificial intelligence. By using computers to analyse and process vast amounts of documents, NLP is particularly suited to this investigative style of story.
It has already been used to some success, with a team of Reuters journalists using NLP tools to tread though 10,300 legal documents relating to the US Supreme Court. While this process required oversight and modification of the tools, AI vastly reduced the legwork required in their journalism.
Two issues are spotlighted in the comprehensive document from Helberger et al: an understanding of these tools, and who will get to use them.
On a purely practical level, journalists would need to understand these tools to properly engage with the data. This means understanding incomplete data, the limitations of modelling, sampling bias, as well as any technical skills needed to run these programs.
But if the world is becoming increasingly digital and some professions require upskilling as a result, why should journalism be excluded?
It shouldn’t, but this leads to the second, and perhaps more consequential issue. If there is a financial barrier between journalists and these tools, the report authors warn of the decreasing feasibility of small and local news organisations.
They fear this could lead to the monopolisation of the news industry by large organisations, and the stamping out of smaller organisations. If these organisations aren’t around to provide local news, there may be a failing of journalism to act as public watchdog at anything but a national (or even international) level.
The report cites open-source software as one solution. This would level the playing field so that small organisations have all the software of bigger organisations, even if they’re missing some hardware.
