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Generative AI Is Already Helping Fact-Checkers, But Proving Less Useful for Small Languages
webreutersinstitute.politics.ox.ac.uk·reutersinstitute.politics.ox.ac.uk/news/generative-ai-alr...
Relevant to AI deployment equity and governance discussions; illustrates real-world limitations of LLMs in public-interest applications, particularly the risk of capability gaps across languages in high-stakes information verification contexts.
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Importance: 42/100news articlenews
Summary
A Reuters Institute report examines how fact-checkers are adopting generative AI tools to improve efficiency, while highlighting a significant disparity: these tools perform substantially worse for low-resource languages, creating equity concerns in global misinformation detection. The piece explores both the practical benefits and structural limitations of AI-assisted fact-checking at scale.
Key Points
- •Generative AI tools are being actively adopted by fact-checkers to speed up research, claim identification, and evidence synthesis.
- •Performance drops significantly for languages with less training data, disadvantaging fact-checkers in non-English-speaking regions.
- •The language gap raises concerns about equitable access to AI-assisted misinformation detection globally.
- •Fact-checkers report AI is most useful for drafting and summarization, less so for nuanced verification judgment.
- •The findings highlight deployment risks when AI tools designed for high-resource languages are applied in diverse linguistic contexts.
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# Generative AI is already helping fact-checkers. But it’s proving less useful in small languages and outside the West
Experts from Norway, Georgia and Ghana discuss the limitations of this technology. Will AI platforms improve things in the years to come?
A screengrab of [Faktisk Verifiserbar's map made assisted by AI which verifies](https://www.faktisk.no/artikler/0vpy8/stort-kart-disse-videoene-og-bildene-har-vi-verifisert) images and videos showing attacks on hospitals and schools in the Middle East.
[Gretel Kahn](https://reutersinstitute.politics.ox.ac.uk/people/gretel-kahn)
29 April 2024
In a year where more than [50 countries](https://www.economist.com/interactive/the-world-ahead/2023/11/13/2024-is-the-biggest-election-year-in-history) are holding elections, bad actors are ramping up their disinformation campaigns with [fake images](https://www.boomlive.in/decode/how-ai-generated-images-took-centre-stage-in-telangana-elections-24076), [fake videos](https://www.theguardian.com/technology/2024/jan/12/deepfake-video-adverts-sunak-facebook-alarm-ai-risk-election) and [fake audios](https://www.france24.com/en/live-news/20240205-biden-robocall-audio-deepfake-fuels-election-disinformation-fears) created with the [use](https://reutersinstitute.politics.ox.ac.uk/news/how-ai-generated-disinformation-might-impact-years-elections-and-how-journalists-should-report) of generative artificial intelligence. But just as AI is revolutionising the spread of falsehoods, could it also help debunk them?
To answer that question, I spoke to three fact-checkers from Norway, Georgia, and Ghana who are applying artificial intelligence to their work. But our conversations soon turned to the limitations of this new technology when applied to diverse geographical contexts, for example in non-Western countries or in countries with underrepresented languages in training models.
### **How AI can help**
The dawn of generative AI has made many fact-checking organisations embrace this technology in different ways, with the promise of accuracy and speed.
[Faktisk Verifiserbar](https://www.faktisk.no/tema/organisasjon/faktisk-verifiserbar) is a Norwegian cooperative fact-checking organisation that focuses mostly on fact-checking conflict areas using OSINT techniques. They have been experimenting with different aspects of AI to facilitate and automate their work. Henrik Brattli Vold, a senior adviser for the organisation, explained they have been using an AI photo geolocation platform called [GeoSpy](https://pro.geospy.ai/), which extracts “unique features
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