Glory Ebube Nwankwo, a media researcher at Centre for Journalism Innovation and Development (CJID), a West African media innovation and development think tank, verifying a claim on Dubawa Chatbot on Whatsapp in Abuja, Nigeria on July 23, 2026. Photo: Ibrahim Ismail, bird story agency
Improvements in generative artificial intelligence are being made every day but misinformation is on the rise too. Tools developed and trained in Africa by Africans are now assisting journalists and the general public in distinguishing between true and fake information. Monsur Hussain and his team are at the forefront of a quest to check fake info at the door.
By Ibrahim Ismail, bird story agency
In their modest office in Abuja, Nigeria, Monsur Hussain and his team of software developers and AI researchers, are debating ways to better the next generation of fact-checking technology. Laptop screens flash lines of code and machine learning models while the group compares test results, revised algorithms, and demonstrated how artificial intelligence could better identify fact from fiction.
Hussain is the innovation head at the Centre for Journalism Innovation and Development (CJID), a West African media innovation and development think tank that employs investigative journalism, research, and technology to improve journalism, promote accountability, and combat misinformation across the region.
He led the development of Dubawa AI, a fact-checking tool launched in 2024 to help journalists and the public evaluate claims before they spread online.
“Basically, deciding what to build, how to build it, and what problem we are looking to solve, identifying the problem itself, and working along with journalists and fact checkers to ensure that the solution we’re envisioning is the right one,” he says.
The name Dubawa is derived from Hausa, a language extensively spoken in northern Nigeria and areas of West Africa. While it literally means “look,” in the sense of fact-checking, it is most closely translated as “check” or “verify.”
The team began by focusing on one challenge: teaching artificial intelligence to detect factual claims that needed to be verified.
“There’s a difference between questions and claims. What we want to focus on is claims,” Hussain says. “We started with training a model on understanding what claims are, especially claims that have an impact on society, like health related claims, political claims, and others.”
The Nigerian Communications Commission (NCC) reports that Nigeria has over 148 million active internet subscriptions, making it Africa’s largest online market. At the same time, advancements in generative artificial intelligence have made modified photos, videos, and audio more convincing, putting more pressure on journalists to check content before release.
For Abuja based software engineer Japhet Johnson, locally developed artificial intelligence models are increasingly important because they are trained using regional information that many global models overlook.
“Most of these AI models are trained maybe for Europe or the United States,” he says. “When we want to actually prove or get information, we find that most of those AI might hallucinate. They might not be able to give you good information about Africa. That is where Nigeria needs to step in. We need AI that understands how our news is being presented.”
Johnson believes strengthening local data infrastructure will be critical if African AI systems are to remain reliable while complying with national data protection laws.
“What we need to do now is ensure we have companies that follow the Nigeria Data Protection Regulation rules so that a lot of our data is stored internally.”
The team created a chatbot for the Dubawa website and WhatsApp, allowing users to check claims in seconds. It also has an audio tool that pulls claims from recordings for fact-checking.
“If you go to dubawa.org, you would find the Let’s Fact Check icon on the bottom right corner,” Hussain says. “You put in the claim, click submit, and it’s able to give you the verdict on that particular claim.”
According to Hussain, the chatbot has verified more than 6,000 claims and has been used in over 32 African countries, with growing adoption in Ghana, Gambia, Liberia, Sierra Leone and Senegal.
To train the algorithm, the developers linked years of verified Dubawa fact checks to a machine learning model, which can detect trends in previously reviewed allegations.
“We built a website with Python and connected Dubawa’s database where all the fact checks were stored,” Hussain says.
Instead of launching the platform right away, the team created a minimum viable product and tested it with journalists and fact checkers, polishing it through regular feedback.
“We built a minimum viable product, got feedback and then did a lot of iterations until we got something that was more satisfactory.”
The research emphasizes the magnitude of the challenge. A study titled Fake News and Public Trust in Online Media: A Study of Abuja, Nigeria discovered that 75 percent of internet users polled frequently encountered fake news on their principal social media platforms.
For journalists, verifying fast-moving claims frequently entails exploring different databases, tracking down original sources, and cross-checking evidence before publishing. Hussain believes that artificial intelligence may shorten the time spent on those jobs while preserving editorial judgment.
“It’s about trying to reduce the misinformation that flies everywhere and trying to monitor what people are saying, what claims people are making, and how we can put a control on it so that people understand there’s a form of accountability.”
For Glory Ebube Nwankwo, a media researcher at CJID, the chatbot has changed how she monitors information gathered from social media and other online platforms.
“My work as a researcher involves a lot of media monitoring and a lot of information on social media,” she says. “Doing it manually before Dubawa AI actually takes a lot of time, days sometimes.”
The ability to verify information on a mobile phone has also changed how she works while away from her desk.
“I don’t have to bring my laptop to check for information or sources. If I take my phone, I’m able to do it, and that really made my life easier.”
Because artificial intelligence models can create false data, the team implemented protections before making the chatbot public.
“We implemented certain changes and put in guardrails to ensure the model does not go out of context in a lot of situations,” Hussain says.
For Hussain, however, the platform’s success depends less on the number of people using it than on whether it changes how people consume and share information.
“I think what we want to build is a culture where people learn to check before they forward information, before they send something out.”
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