In the closing weeks of Ghana’s 2024 presidential campaign, a video surfaced of Dr Matthew Opoku Prempeh, then the New Patriotic Party’s running mate, standing before a crowd of small-scale miners and promising that excavators seized during a government crackdown on galamsey would be returned so the miners could go back to work undisturbed. In a country that has watched the Pra and Ankobra rivers turn the colour of wet clay, and that has argued about galamsey at every funeral and barber shop, the clip was incendiary. Within minutes it was everywhere. Environmental campaigners were apoplectic; party supporters were jubilant. Before any journalist had finished making calls, the campaign issued its answer: the video was a deepfake. Newsrooms froze. Reporters had watched the footage from several angles, and a sign-language interpreter could be seen translating the same words beside Prempeh. GHOne consulted two independent interpreters and got two different readings, which only thickened the fog. Ghanaian journalists, lacking forensic tools of their own, escalated the clip to WITNESS’s Deepfakes Rapid Response Force, a global panel of media forensics specialists. Four expert teams examined it. Their verdict was unanimous: there was no evidence of AI manipulation; the video was real. According to a new analysis by Abugre Alebsuure Abayeta, a doctoral researcher in intercultural communication at the University of Jyväskylä, the weapon deployed against Ghana that week was not a deepfake. It was the existence of deepfakes — the corrosive possibility that anything can be fabricated, which means nothing has to be answered for. WITNESS found that in 2024, a third of cases escalated to its rapid-response team involved politicians trying to discredit authentic material by claiming a machine had made it. The AI misinformation story, Abayeta argues, is not really about technology; it is about trust: who has it, who squandered it, and what rushes into the space where it used to be.
Abayeta, who has a background in journalism and development communication, observes that most global conversation about synthetic media is shaped by American and European anxieties: deepfaked candidates, cloned voices in robocalls, AI news anchors. Those are real problems, but they imagine an information environment with well-funded fact-checkers, media-literacy campaigns in schools and institutions that sceptical citizens can consult when something smells wrong. That is not the environment most of humanity lives in, and it is not Ghana’s. Political information there does not travel through newsrooms; it travels through WhatsApp groups — family, church, old students’ associations, market women, constituency youth wings. Across most of Africa’s largest digital economies, more than nine in ten internet users are on the platform, and the voice note has become the continent’s native format: intimate, forwarded, unindexed, unsearchable, unfalsifiable by anyone outside the group. A fabricated clip in this environment does not need to fool an editor at the Daily Graphic or GBC; it needs to fool one uncle, one pastor, one group admin whose word already carries more weight in that room than any government statement. By the time GhanaFact or Dubawa publishes a debunk, the message has been forwarded through forty groups and reshaped into something the original poster would not recognise. The fake does not have to win the argument; it only has to arrive first, wearing a face you love. Trust, too, does not travel the same way everywhere. In some contexts institutional sources carry the most weight; in others, particularly where institutions have a long record of failing people or lying to them outright, interpersonal trust outranks everything official. A message from a relative or community elder can outweigh a correction from an international news agency — not because people are gullible, but because that relative has never lied to them the way the state has. AI-generated misinformation is dangerous precisely because it has learned to exploit this. It does not merely fake a video; it fakes the register of trust: a familiar cadence, a local accent, a Twi or Gurene inflection, a proverb deployed correctly, a joke only people from that district would understand. A deepfake calibrated for a Ghanaian audience looks nothing like one built for a Slovakian or Indonesian audience, because it is not just imitating a person; it is imitating how a culture decides what is real. And Ghana, Abayeta writes, decides largely through people, not paperwork.
The standard prescriptions for fighting synthetic media — watermark AI content, mandate labels, tighten platform takedown policies — all rest on one assumption: label the fake, and the truth wins. But labels only work if you trust the labeller. Ghana already ran this experiment, and it failed inside a single election cycle. During 2024, fake “news cards” — shareable graphics stamped with media-house logos — proliferated with forged branding from trusted outlets. Newsrooms fought back by stamping the fakes with a bold “FAKE NEWS” watermark and posting corrections on their official handles. It was a sensible, low-cost, home-grown defence. Within weeks, partisan actors had stolen the stamp. Any unflattering news card, true or not, was rapidly re-issued bearing its own “FAKE NEWS” label. The instrument of verification became an instrument of confusion. The stamp meant nothing, because the thing it depended on — a shared belief in who had the standing to declare something false — had never actually existed. Abayeta insists this is not a Ghanaian peculiarity. The Electoral Commission of South Africa has recently promulgated a Disinformation Code ahead of the November local-government elections, requiring parties to label AI-generated material as synthetic, publicly correct false claims within 36 hours, and report suspected disinformation through the Real411 system. It is a serious, thoughtful piece of regulation. Yet days before telling parties to label their synthetic content, the commission posted an AI-altered image of its own to promote voter registration. Nobody flagged it. Nobody labelled it. That is not hypocrisy so much as evidence: labelling regimes address the supply of fakes, but they barely touch the demand — the reasons a doctored clip already feels truer to a voter in Bawku or Bekwai than an official correction ever will.
The practical capacity to tell real from fake, meanwhile, remains grotesquely unequal. Dubawa, a prominent fact-checking organisation, has noted that tools for detecting manipulated audio vary widely in effectiveness, and the robust ones are paid products most African newsrooms simply cannot afford. The problem compounds when doctored audio is buried inside video. In the Opoku Prempeh case, some Ghanaian journalists could not resolve the clip domestically at all; they had to send it abroad. Compare that with the investment platforms pour into content moderation, AI labelling and political-ad transparency around elections in wealthier countries. Compare it with AI governance across the continent, where only a handful of states have dedicated strategies and the rest fold the whole question into cybersecurity legislation written before generative models existed. “We are being asked to defend a more sophisticated attack with a fraction of the equipment,” Abayeta writes. This resource gap has political consequences. When verification depends on foreign experts and paid tools, the timeline for a correction stretches far beyond the half-life of a WhatsApp forward; the original falsehood has already done its work. And because the cost of creating convincing synthetic media keeps falling while detection remains expensive, the asymmetry grows worse each election cycle. The voices that might build local responses are too often excluded from global AI-safety conversations, even though the risks behave differently in Accra, Manila and São Paulo than they do in Washington, Brussels or London. That, Abayeta argues, is a structural failure rather than a moral one, but it reliably produces solutions shaped to the wrong problem.
If misinformation is intercultural before it is technological, Abayeta argues, the response must be too. First, localise media literacy instead of importing it. A campaign designed in Brussels and translated into Ewe or Ga is not the same as one built around how a particular community actually verifies things: through whom, and why. The useful question is not “can you spot a deepfake?” but “who in your life would you ring to check?” Build from that answer. Second, back the messengers people already believe — chiefs, imams, pastors, assembly members, community-radio presenters, market queens. These are precisely the figures disinformation impersonates, which makes them the strongest available interruption, if they are equipped and included rather than bypassed. The most effective counter-measure of Ghana’s last election, he says, came from exactly this instinct: GHOne began embedding voice notes into its news cards with a prominent “SOUND ON” tag, letting the public hear politicians in their own voices. No watermark, no policy paper, no foreign vendor; just a fix that understood how Ghanaians actually consume information. Third, fund the verification layer that already exists — GhanaFact, Dubawa, Fact-Check Ghana, the MFWA coalition and the newsroom desks that stayed up through December 2024 chasing audio clips. They are under-resourced and over-relied upon. Detection tooling and forensic training for Ghanaian journalists would cost a rounding error compared with what is currently spent debating AI safety in conference halls where no Ghanaian has a seat. Fourth, put the people being hit hardest in the room where the rules are written. Most global conversations about AI and election integrity are led from Washington, Brussels and London, about risks that behave completely differently in the Global South. Unless African researchers, civil-society organisations and election officials are present, the rules that emerge will default to protecting wealthier information environments.
The technology will keep improving, Abayeta concedes. The fakes will keep getting harder to catch with the naked eye, and the cost of making one will keep falling until it is effectively zero. But the thing that determines whether a fake succeeds was never resolution or realism; it is whether the lie speaks a language of trust the community already knows, and whether anything credible is left standing to contradict it. That is the real casualty — not belief in any particular falsehood, but the slow death of the possibility of being held to account. A politician who can no longer be caught saying something can always suggest a machine said it for him. A citizen who has been fooled twice stops believing the third thing, even when the third thing is true. What follows is not a country full of people who believe lies; it is a country full of people who believe nothing, and vote accordingly. Ghana goes to the polls again in December 2028. The tools will be cheaper by then, the fakes better, the voice notes more convincing. The question, as Abayeta puts it, is whether Ghana will still have spent those years waiting for someone in San Francisco to solve a problem they have never had to live with. Abayeta is a doctoral researcher in intercultural communication at the University of Jyväskylä, where his work examines algorithmic bias and intercultural digital inclusion in generative AI. His analysis draws on reporting by WITNESS, Dubawa, GhanaFact and the Media Foundation for West Africa, and on his own background in journalism and development communication.
