News Corp Australia is generating 3,000 articles per week using generative AI. Even the August Washington Post is using its in-house Heliograph AI tool to automatically generate short reports for its live blog.
Yet traditional media have also expressed fear of the impact of AI on journalism. News Corp’s global CEO, Robert Thompson, is reported as warning (in a tabloid-headline):
“Instead of upgrading and expanding, what you may find is that you have this ever-shrinking circle of sanity surrounded by stores of garbage. Instead of the insights that AI can potentially bring, it will inevitably devolve into the framework of an insect-infested mind.
CNET, a popular technology news website, has had to add correction notices to feature articles generated entirely by artificial intelligence. For example, a numeracy-challenged AI ‘wrote’ an article about compound interest that incorrectly stated that a $10,000 deposit bearing 3 percent interest would earn $10,300 after the first year, not just $300 .
Couldn’t AI come at a better or worse time for traditional media?
A recent article by European academics (Andreas Opdahl et al) points out that while we need trustworthy journalism more than ever, the traditional media business model we rely on to deliver it is broken:
“The last two decades have put pressure on journalists, editors and newsrooms. In terms of content, the news habits of young digital natives differ from those of older media consumers. They rely more on alternative and free information sources and are less likely to pay for a news subscription. Other segments of the population stay away from mainstream media due to perceived political bias and distrust in authorities. These trends may be exacerbated by coordinated disinformation campaigns and amplified in sealed information enclaves such as online echo chambers and so-called search and recommendation bubbles…On the business side, the decline in media income from advertising, subscriptions and sales due to the availability She has come. Free online news sources, social media, search engines and other intermediaries…as broken business models lead to layoffs in newsrooms, these challenges become even more difficult to address, creating a vicious cycle.’
In their article, Opdal and others “attempt to present a vision of how recent advances in AI can support trustworthy high-quality journalism at every step of the journalism value chain.”
Trust in journalism is a two-way equation: the first two steps – gathering and assessing news – require the journalist to trust journalistic sources and the credibility of the information they provide: while the last two steps – creating and presenting The purpose of news is to trust the credibility of the news stories the reader or viewer receives.
How can AI enhance news gathering?
Information gathering is the foundation of reliable news production. Journalists know that trusting any one source is high risk, and so a journalist’s standard operating procedure should be to check a story with as many other sources as possible. Often this will be a puzzle in which different, smaller pieces of the story are verified in a series of different sources, to reach a point where the story can be judged with more probability than not to be true.
Of course, AI is all about finding unobserved or latent correlations in troves of data. As Opdal and others say, “New uses of AI may seek to make content more trustworthy by relying on diverse and reliable sources and by confirming (or triangulating) overlapping information from independent sources.”
AI can also improve the ‘breaking news’ capabilities of traditional news organizations by detecting ‘early shocks’ of news in social media, such as people posting on-the-spot photos of events in real time. Reuters has experimented with News Tracer NLP and ML to detect pre-news events, giving our journalists “an 8 to 60-minute head start on global news outlets in breaking more than 50 major stories”. ‘Get it.
AI can help traditional media get even further ahead of the news curve and identify topics of interest to segments of their audience on which journalists can focus their newsgathering or investigative efforts. For example, The Atlanta Voice, the largest African American community newspaper in Georgia, United States, uses CrowdTangle to identify topics of particular interest to the African American community and monitor trends:
“We use keywords and overperforming data to find trend lines that are not easily researched or discovered through traditional search or data analytics using Google or on-site analytics platforms. The Instagram data we can access is also invaluable for showing growth trends on pages. Example: When “Olde Town Road” became a hit record for Lil Nas X (Georgia native), we were able to research and show when the account gained popularity on Instagram.
AI can be adept at verification in multimedia environments. ‘Deep fake’ photos are a particular challenge for journalists but other AI may require an AI to spot fakes. AI can also verify text against a wide range of other data sources: for example, whether the reported number of participants at a demonstration is consistent with traffic data at the time, and whether supporting images match weather data and lighting conditions. Are consistent with?
Slightly more scary, Opdal and others suggest that AI could be used to test the inherent trustworthiness of the person who is the source of the story:
“Machine learning techniques can be used to train models that recognize human informants based on their historical reputation, their social-network connections, their knowledge background, status, sponsoring organization, and whether they are referred by other informants.” Profile through measures such as. For example, post-event historical analyzes of Twitter feeds can be used to identify and positively evaluate accounts that have consistently reported newsworthy events quickly and reliably.
How AI can improve journalistic evaluation of news
As Opdal and others point out, AI’s unique ability to rapidly process vast stores of data has clear benefits for investigative journalism in our data-heavy world:
- For example, the Panama Papers required the analysis of 4.8 million emails, 3 million database entries, 2 million PDFs, one million images, and 320,000 text documents, totaling 2.6 terabytes of information. Sophisticated analysis of the data was required to uncover the deliberately complex ownership structures used by politicians to hide their corrupt wealth.
- Analysis of such vast stores of data often involves large teams from multiple media organizations: the Panama Papers involved 100 news companies and 400 journalists. Opdahl and others say that “(AI) tools that analyze social networks and that connect the right people inside a distributed and possibly global news organization.. (can) ensure that each news story is delivered with complementary capabilities. is supported by a single team and avoids duplication) or even inconsistent reports about the same incident.”
- A common approach of interviewers is to claim ‘alternative facts’ as the truth. Opdal et al state that “(d)uring the interview, the veracity of claims made and information provided can be assessed in real time… (i) information retrieval and NL inference techniques are used against appropriate background Questions may be asked to provide information and follow-up suggestions.
How AI can enhance news production and distribution
The most obvious role of AI in helping a journalist write an article is to generate a basic or initial narrative from source material, which the journalist can then build upon, polish, and edit.
But Opdal and others say AI can be used as a writing tool in more sophisticated ways that could enhance the quality of human-written journalism. NewsCube is a three-dimensional storytelling tool that lets people compile complex stories and tell them from multiple perspectives, developed by Psyche Doherty, a journalist and winner of the Walkley Grant for Innovation in Journalism. NewsCube can facilitate the journalist in the writing process to identify different ‘angles’ of the story, even weakly supported or known false positions, and test whether they potentially form in the news report. Should be mentioned from.
Google is reported to be developing a personal assistant for journalists called Genesis, which automates certain tasks, such as creating headlines or writing in different styles. Google sees Genesis not as a replacement for journalists, but as an opportunity to help “shunt the publishing industry away from the pitfalls of generative AI.”
AI can also broaden and deepen content:
- “Media consumption has shifted from one-dimensional linear content streams (e.g. linear TV, static HTML) to multiple platforms capable of customization and interactivity (e.g. phones, smart speakers, smartwatches, tablets, etc.)…(and once the original The story is written).. Generic multimodal representation models can be used to create transmedial narratives that can be presented on a variety of multiple platforms.
- AI can be used to translate content into multiple languages to reach a wider audience.
- AI can also be used for “credibility…or for example, when presenting a story on a TV screen, credibility can be underlined by providing deeper information such as background facts, related social-media content, examples, links and the like.” Could.” Other information is available through the viewer’s mobile phone at the same time.
Are robot journalists inevitable?
While painting this optimistic picture of AI’s potential benefits for journalism, Opdahl and others are realistic enough to admit:
“(i) At a moment when many newsrooms are struggling with a crisis of distribution and revenue – problems for which generative AI provides no obvious help – the most obvious use for any type of automation is cost reduction. “
“Augmented news production pipelines will begin an irreversible process driven by business concerns toward increasingly automated news, in which journalists gradually turn into high-level observers and maintainers of journalistic information flows.”
KPMG has estimated that 43% of the work done by writers, authors and translators could be done by AI tools. BILD, Germany’s largest tabloid newspaper, laid off 20% of its staff, partly justified by the increased use of AI.
Yet at a recent Oxford Internet Institute-Mindru Foundation conference on AI and journalism, the widely held view was that there is an inherent ‘humanity’ to journalism that AI cannot replicate:
“Jobs in journalism involve a combination of tasks, only some of which can be automated. For example, several speakers were convinced that AI could not match the writing skills of a journalist (two of them described AI’s writing as ‘boring’ and dull). Similarly, the ability to report or identify new facts and opinions are skills that will likely remain difficult to automate. Other participants highlighted that humans are unbeatable at understanding the meaning and context of information – something that, along with accuracy, remains the core of good journalism…For many journalistic tasks, thinking and reasoning The human ability to draw intuitive conclusions is based on other inferences – the remains of the abstract. ‘Why does this story matter?’, ‘Why is it important?’, and ‘What does it mean in a given context?’ Questions like. “Only a human being can ask and give a proper answer.”
There is also a view that the decision not to use AI, i.e. recognize articles as ‘written by humans’, could become a byword for quality journalism. SMH reports Crikey CEO Will Hayward said that AI is “eliminating all inauthentic reporting and regurgitating non-journalism provided by all mainstream outlets” by replacing original news and information delivered directly to readers by publishers. Rewarding will have the opposite effect. ,
But this belief in the essential, irreplaceable humanity of journalism may be misplaced: SMH also quotes Lisa Davis, CEO of the Australian Associated Press: “AI is like a cadet journalist. “It is spirited and prone to making mistakes, but one day it will be better than you.”
Read more: Trustworthy journalism through AI