Communication is the backbone of crisis management, and Yushau Shuaib’s AI in Crisis Communication in Nigeria: Challenges and Prospects places this truth at the center of its analysis. The book explores how artificial intelligence is reshaping crisis communication in Nigeria, examining adoption patterns, effectiveness, public trust, implementation barriers, and policy pathways.

In the foreword, Kashifu Inuwa Abdullahi acknowledges a global reality: AI is transforming public service delivery, yet it brings concerns about accountability, information integrity, and the future of human interaction in an increasingly digital world. This tension frames the book’s exploration of how societies—especially developing ones—must adapt technology to their unique social and cultural contexts.

The book draws a clear contrast between developed and developing nations. Countries like Japan integrate AI directly into emergency systems. During the 2011 Tohoku earthquake and tsunami, Japan’s use of AI was effective largely because of high digital literacy, strong public trust, and widespread smartphone ownership. Africa’s experience is more gradual. Kenya leads East Africa in digital crisis response, even deploying an AI chatbot, Zuri, to provide verified health information during outbreaks.

Nigeria has made notable progress too. AI-powered flood early warning systems in states like Kogi and Anambra have saved lives. Yet the digital divide remains a major barrier. With smartphone penetration at only 30–40 percent, compared to Japan’s 83 percent and Kenya’s 91 percent, millions of Nigerians remain excluded from advanced AI tools. Weak internet connectivity and frequent power outages deepen this gap.

One of the book’s strengths is its historical sweep. Crisis communication in Nigeria began with traditional town criers and missionary messaging, evolved into propaganda-heavy tactics—such as the use of images of starving children during the Biafra crisis, a practice now recognized as poverty pornography—and later shifted to institutional frameworks like NEMA and the Centre for Crisis Communication (CCC). Colonial-era communication was one-directional and biased. For years, government agencies and private sectors such as aviation and banking underestimated the importance of crisis communication. Only after repeated crises did they begin embracing public accountability instead of excuses and defensiveness.

Using questionnaires and interviews across public and private institutions, the study found strikingly consistent patterns. Seventy-five percent of respondents were familiar with AI in crisis communication, and most believed their organizations already use AI tools. Public information dissemination is the most common AI application. Social media is the first place people seek crisis updates, followed by radio. AI chatbots—such as ChatGPT—are heavily used when official channels fail. The study also found that AI-generated responses did not reduce public trust, especially when used in rebuild strategies that emphasize accountability.

The study set out to understand how AI supports public-sector crisis communication, how AI-driven information shapes public perception, and how technology can bridge gaps between government and citizens. It successfully addressed these questions with evidence-based insights. Still, legitimate concerns remain. Automated systems may misinterpret cultural or religious nuances. Deepfakes and misinformation pose serious threats. Public reluctance to verify information can escalate tensions. Institutions like the Nigerian Institute of Public Relations (NIPR) are therefore advocating for responsible AI use. AI is here to stay, but it must complement—not replace—human expertise.

The author proposes several actionable steps: building nationwide AI literacy, establishing a national ethical framework for AI, expanding AI integration across agencies, and defining collaborative roles for the Federal Ministry of Information, NEMA, CCC, and security and emergency bodies. These recommendations align with Everett Rogers’ Diffusion of Innovation Theory, which places Nigeria in the innovator and early adopter phases, indicating significant room for growth.

I approached this book expecting dense technical jargon, but Shuaib delivers clarity without oversimplification. The work is accessible, well-structured, and deeply relevant. It is a must-read for anyone seeking to understand how crisis communication operates in Nigeria—and how AI is reshaping it globally.

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By Mumeenah Oyindamola Abdulrahman

There is something mildly unsettling about teaching a machine to recognise an intruder, only to discover that the intruder has access to the same machine.

Cybersecurity has always been a contest of time. Someone finds a weakness, someone else notices it, patches it, blocks it, or arrives five minutes too late and writes an incident report. Artificial intelligence has not changed that basic arrangement. What it is changing is the speed at which both sides can participate.

For defenders, this is useful in a very practical sense. A security team may be staring at millions of login attempts, network events, emails and endpoint alerts, most of which are harmless and a few of which matter a great deal.

Machine-learning systems can look for patterns humans would struggle to notice at that scale: a user suddenly signing in from an unusual location, a device behaving differently from its normal pattern, or a stream of messages carrying signs associated with phishing.

Generative AI can go a step further by summarising alerts, connecting related events and helping analysts decide what deserves attention first. Microsoft, for instance, already describes AI-assisted threat analysis and automated actions such as suspending suspicious accounts or initiating password resets as part of modern defence.

That sounds suspiciously close to replacing the analyst. It is not. A model can tell you that something is unusual. “Unusual” and “malicious” are not synonyms.

A legitimate employee travelling abroad can look suspicious. So can a badly configured server. And an AI system asked to explain an incident can produce a confident answer that is simply wrong. Cybersecurity has always had false positives; now we have the possibility of false explanations too.

The attackers, naturally, are not sitting around admiring the innovation. In January 2025, Google’s Threat Intelligence Group reported that state-backed and criminal actors were already using generative AI for things such as reconnaissance, phishing content, vulnerability research and code troubleshooting. At the time, the important detail was almost anticlimactic: the technology mostly made existing work easier rather than granting attackers completely new powers.

United Kingdom’s National Cyber Security Centre reached a similar conclusion, assessing that AI would primarily increase the effectiveness and volume of familiar attack techniques through 2027 rather than suddenly produce entirely new forms of intrusion.

Then the line began to move. By May 2026, Google reported the first case in which it believed a threat actor had used AI to help develop and weaponise a zero-day vulnerability. That does not mean an AI independently woke up, discovered a vulnerability and decided to ruin somebody’s day. Google’s assessment was more careful than that. But it does suggest that the gap between AI as an assistant and AI as a genuine expansion of capability is becoming less comfortable.

This is where the real problem sits. AI lowers the cost of competence. A convincing phishing email once required some knowledge of the target, decent writing and enough patience to personalise the message.

Generative AI can help produce hundreds of variations, in several languages, with fewer obvious mistakes. Reconnaissance can be summarised. Stolen information can be processed faster. Malware code can be debugged. Deepfake voices and synthetic identities make impersonation cheaper.

None of these ideas are new, which almost makes them more worrying. Criminals do not need science fiction when ordinary fraud suddenly becomes easier to scale.

But defenders get the same advantage. AI can shorten investigation time, correlate signals across systems and automate simple responses before an analyst has finished making coffee. The temptation, then, is to automate further. If the machine can detect, investigate and respond, why keep the human in the loop? Because the loop is exactly where judgement lives.

Security decisions are not made in clean laboratory conditions. They involve incomplete evidence, business context, privacy, consequence and sometimes the uncomfortable choice between shutting down a service and taking the risk of leaving it running. AI may become better at recommending that choice.

It may even become better than humans at parts of the reasoning around it. But a system that can be manipulated, fed misleading information or simply arrive confidently at the wrong conclusion should not quietly become the final authority because it works faster.

Perhaps the arms race is not really between human hackers and intelligent machines. It is between people who learn where to trust automation and people who learn where to exploit that trust.

The more capable the machines become on both sides of the door, the less useful it is to ask whether AI is “good” or “bad” for cybersecurity. The better question is who remains capable of judgement when speed stops being the scarce resource.

*Mumeenah is a Computer Science student at Kwara State University (KWASU). She can be reached at rahmanmeen206@gmail.com*

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Hundreds of women and youths in Jigawa State have received cash grants, business tools, agricultural inputs and educational support under a grassroots empowerment initiative facilitated by the Director General of the National Information Technology Development Agency (NITDA), Kashifu Inuwa Abdullahi.

The latest phase of the programme, held in Hadejia, focused largely on financial assistance to beneficiaries, which organisers described as part of a recurring intervention aimed at improving livelihoods and reducing poverty at the community level.

Previous rounds of the initiative in other parts of Jigawa included the distribution of sewing machines, bakery equipment, farming tools, fertiliser, seedlings and cash support for small businesses and agricultural activities. Pupils and students have also benefited from scholarships and educational materials, combining economic empowerment with educational support.

Coordinator of the programme, Alhaji Naziru Inuwa, said the intervention was designed to reach women, youths, farmers, students and small scale entrepreneurs who require assistance to improve their livelihoods.

“This is not a one off gesture — it is a sustained, structured intervention that brings government closer to the people and converts policy into tangible relief,” he said. “We are committed to reaching the ordinary person in Jigawa State — the woman who needs a sewing machine to start a tailoring business, the young farmer who cannot afford fertiliser, the child whose school fees are a burden.”
Naziru said organisers aligned the programme with the objectives of President Bola Ahmed Tinubu’s Renewed Hope Agenda, adding that it also aims to strengthen civic and political engagement ahead of the 2027 general elections.
Members of the Tinubu Must Stay (TMS) movement, who volunteered during the Hadejia distribution, commended the initiative and urged beneficiaries to use the grants and materials responsibly. The National Convener of TMS, Engr. Ibrahim Uba, described the empowerment scheme as an example of grassroots intervention that complements broader government economic policies.
“The Renewed Hope Agenda is alive in communities like Hadejia because dedicated leaders like the NITDA DG are translating it from a slogan into real deliverables,” Uba said.
The remarks reflected the movement’s support for the Tinubu administration and its interpretation of the government’s economic programmes.
The Hadejia intervention comes alongside other public and private empowerment programmes targeting women and youths in Jigawa. Federal project records include initiatives supporting women’s empowerment, youth development, agricultural production and small businesses in the state.
Inuwa has also been associated with technology and social development projects in his home state. In June, First Lady Senator Oluremi Tinubu commissioned the Bola Ahmed Tinubu Future Academy in Hadejia, alongside a healthcare facility. The technology academy, facilitated through NITDA, is designed to provide digital training and support innovation.
At the federal level, the Tinubu administration has introduced several social intervention programmes in response to economic pressures following major reforms. The Renewed Hope Conditional Cash Transfer programme was designed to reach 15 million vulnerable households, alongside initiatives targeting small businesses, skills acquisition and other vulnerable groups.
NITDA continues to implement its core digital development programmes, including partnerships aimed at expanding digital literacy, entrepreneurship and STEM education.
Organisers of the Jigawa empowerment initiative said the interventions would continue on a recurring basis, targeting unemployment, women’s economic participation, agricultural livelihoods and educational access.
Similar exercises have been conducted in other communities in Jigawa, with beneficiaries reportedly numbering in the hundreds during individual distribution cycles. However, independently published figures on the cumulative number of beneficiaries, total value of grants and materials distributed, and the funding structure of the recurring programme were not immediately available.

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The National Information Technology Development Agency (NITDA) has launched the 2026 National Cybersecurity Awareness Month, urging Nigerians, businesses and institutions to adopt stronger digital security practices amid the growing sophistication of cyber threats.

The month-long campaign, themed “Together for a Safer Cyberspace,” is designed to promote collective responsibility for protecting Nigeria’s increasingly digital economy and public services.

NITDA said the changing nature of digital technology means cybersecurity can no longer be left solely to information technology professionals, government agencies and security experts, stressing that every participant in the digital ecosystem has a role to play in keeping cyberspace safe.

According to the agency, the rapid adoption of artificial intelligence and automated systems has also transformed the cyber threat landscape, with emerging risks extending beyond conventional phishing attacks.

It identified AI-driven social engineering, deepfake impersonation, voice cloning and fraudulent QR-code attacks, commonly known as “quishing,” among the emerging threats requiring greater public awareness and vigilance.

To strengthen individual and organisational cyber resilience, NITDA advised Nigerians to adopt basic cyber hygiene measures, beginning with the use of strong and unique passwords for different accounts.

The agency also encouraged users to deploy multi-factor authentication on personal, professional and financial accounts as an additional layer of protection against unauthorised access.

NITDA urged individuals and organisations to regularly update their operating systems, applications and devices by promptly installing security patches designed to address known vulnerabilities.

It further warned Nigerians against disclosing sensitive financial information, including One-Time Passwords (OTPs), Personal Identification Numbers (PINs) and online banking login details.

The agency also advised users to exercise caution when interacting with artificial intelligence tools and unfamiliar online platforms, particularly by avoiding the upload of sensitive personal, financial or proprietary corporate information into public AI models.

NITDA stressed the importance of verifying links, attachments and unsolicited requests for information before responding, particularly where such communications employ urgency, synthetic audio or deepfake imagery.

It also called for responsible social media use, noting that excessive disclosure of personal information online could provide material for targeted social engineering attacks.

The agency recommended that individuals and organisations maintain regular offline and cloud backups of critical data to facilitate recovery in cases of ransomware attacks, system failures or other disruptions.

NITDA said its computer emergency response structure remains committed to providing citizens and organisations with the tools, knowledge and frameworks required to prevent and mitigate digital threats, report cybersecurity incidents and support the development of a secure and inclusive digital economy.

As part of the awareness campaign, the agency encouraged Nigerians to follow its official social media platforms, @NITDANigeria, for cybersecurity updates, awareness tips and threat advisories.

For cybersecurity incident reporting and further inquiries, members of the public can contact the Computer Emergency Readiness and Response Team (CERRT.ng) through its website, www.cerrt.ng, email address cerrt@nitda.gov.ng, or telephone +234 817 877 4580.

The statement was signed by Mrs. Hadiza Umar fnipr, Director, Corporate Communications, NITDA.

The post NITDA Rallies Nigerians for Safer Cyberspace as Cybersecurity Awareness Month 2026 Begins appeared first on Tech Digest News.

By Mumeenah Abdulrahman,

Somewhere on your phone, there is a conversation you would not want anyone else to read. You told it about your anxiety, your medical results, your business plan, or your relationship. And the person on the other end was never a person.

That is now normal. In Nigeria, with over 109 million internet users, “let me Google it” has quietly become “let me ask ChatGPT.” We ask these tools to rewrite our messages, explain our assignments, create our pictures, draft our CVs, and sometimes help us make sense of feelings we have not even told our closest friends.

Artificial intelligence, or AI as we fondly call it, emerged as a formal field of study in 1956, when computer scientist John McCarthy and other researchers introduced the concept at the Dartmouth Conference. Ever since then, there have been many improvements, and it has moved steadily from academic theory into the mainstream spotlight.

We first saw it with Apple’s Siri in 2011, which helped make voice interaction familiar to ordinary smartphone users, and then again in 2022 with a major shift when conversational generative tools became accessible to everyone with an internet connection. Since then, there has been a continued transformation in how we interact with technology.

There are many ways that AI shows up in our daily lives, even more so in recent times. Today, there are social media accounts run entirely by virtual personalities with millions of followers, and content powered primarily through automation, from scripts to voiceovers to editing.

We now have the creation of fictional characters with storylines designed as prompts which are in turn generated into full stories, humans confiding in chatbots about their most human secrets and desires, and people joining trends that give you a prompt to tell your assistant to roast you, praise you, or plan your life. Whether we realise it or not, we now live a life that is deeply intertwined with these systems.

While all these things are not inherently bad, there is an element of concern in them that cannot be ignored. I did my research on the two main discourses that come up when the topic of being “Pro-AI” or “Anti-AI” technology is being discussed.

These discuss are, “How much water is used to power these models?” and “Is my data being used to train them?” There are no straightforward answers when these two questions are asked, because the reply depends mainly on the factors at play.

*The Water Question*

Some say it uses 1/15 teaspoon of water to generate a single prompt. Others say it uses a whole bottle of water. Interestingly, both answers are correct, but with a different outlook. The 1/15 teaspoon logic is about the water directly used by the data centres that store information and do the processing. These centres use water-based systems to cool the servers that get extremely hot. The bottle of water logic is broader. It includes the water consumed by the power plant generating the electricity that powers the chip in the first place, and it also accounts for longer conversations, multiple retries, and less efficient systems.

In reality, there is no exact amount of water consumed during an interaction. It heavily depends on three key factors: the model, the media being generated, and the environment of the data centre. First, the model itself. A larger, more advanced system requires much larger processing power, thereby consuming a lot more water and energy.

Second, the media. Generating images and videos requires a far higher consumption of water and energy than generating plain text. A single generated image can use as much energy as charging your smartphone. Third, the environment. The location of the data centre matters a great deal. If the facility is located in a dry and arid region with not enough water, powering these models can put real pressure on local supply and lead to water stress for communities nearby, while the same facility placed in a cooler, more suitable environment with efficient cooling would not have the same impact.

In places where water is already scarce, and we know how real water scarcity can be in parts of northern Nigeria, that extra demand is not just a technical issue. It becomes a community and ethical issue. So, the question is not just how much water is being used, but where that water is coming from, how efficiently it is being used, and who else needs it.

*Does Our Data Train these Models?*

This is the second question that worries many users, and it is important to understand it clearly because there are two distinct phases of interaction that people often confuse. When you converse with a chatbot and it remembers some details about you which you just mentioned in passing, and those details recur in another conversation entirely, this is called the “remember phase”. It is often called memory or personalisation, and the system is designed to make your experience more tailored and continuous.

The second one is when your conversations are used as raw material to train future versions. This is called the “learn phase”. This does not translate to having your private conversations displayed verbatim in another user’s chat. Instead, it means the patterns, word choices, feedback, and corrections from many conversations are aggregated and used to create a smarter next version. The “learn phase” is what is actually used for training, and it is the default setting of many free platforms. In a sense, for free tools, your form of payment is allowing your interactions to help improve the system.

This is why your settings matter. Whether your chats are used for training depends on the platform, its privacy policy, and whether you have opted in or out. The real bone of contention here is not just about your data training a model; it is about the kind of data you paste into these tools.

Information like passwords, API keys, private keys, confidential company documents, unpublished research, or personally identifiable information such as pictures, videos, medical records, and financial information are highly sensitive and deserve to be treated as such.

Once sensitive information is entered into a system that learns, it is difficult to fully retract it, and that is why digital literacy is no longer optional for the average Nigerian youth who lives online.

The main purpose of this article is not to reduce, diminish, or vilify the way we use or see AI in society because, it is a very helpful resource that has improved and can continue to improve a person’s standard of living. It can create job opportunities, allow humans to align and process their thoughts better, improve communication skills, enhance cognitive functions, and provide overall better life assistance if used correctly.

For students, creators, small business owners, and professionals in Lagos or Lafia, it has lowered the barrier to entry in many fields and made complex tasks more approachable.

The problem was never really about the technology itself. It is mostly about how humans choose to use it. We have a responsibility for how we use the resources at our disposal, and we need to move from passive consumption to intentional use.

Therefore, the questions we should be asking ourselves are not simply “How much water is used to power these systems?” or “Is my data being used to train them?” Rather, our questions should be more personal and practical, “How do I use these tools in a way that does not reduce or devalue my intelligence, but rather optimises it?” and “How do I get the best from them without compromising my privacy, while also being environmentally conscious?”

That means learning to write better prompts instead of copying and pasting blindly. It means double-checking facts instead of assuming the answer is always right, not pasting sensitive data, reading privacy settings, and understanding when to switch off model training if the platform allows it.

It also means being conscious of our usage: do we need to generate twenty images when two will do? Can we combine our requests into one clear instruction rather than ten vague ones? These systems are powerful resources, much like electricity or the internet.

How we use them is still our responsibility, and the future will not be about choosing between human intelligence and AI systems. It will be about learning how to use both wisely, ethically, and sustainably.

The post FEATURE: Why How We Use AI Should Matter, By Mumeenah Abdulrahman appeared first on Tech Digest News.

The company said the breach occurred in June during internal training and evaluation of an experimental AI model, but was not disclosed publicly until September.

OpenAI said the model accessed the Services Australia Medicare Statistics Reporting Service, where it ran commands, retrieved internal files and credentials, accessed aggregate statistics and wrote files.

The company said its investigation had found no evidence that medical records were accessed. It also said activity involving three other Australian government agencies did not result in access to sensitive records.

“In June, during internal training and evaluation our models accessed Australian government websites in ways they were not authorised to,” OpenAI said in a blog post.

“We also should have handled our response better. We are sorry and working to do better in the future.”

The incident prompted criticism from Australian Prime Minister Anthony Albanese, who previously described the unauthorised access as unacceptable and questioned why the government was not notified sooner.

OpenAI said it would provide dedicated support to affected government agencies and contribute resources to strengthen cybersecurity for government and industry through its $1 billion global fund.

The company also plans to establish an Australian task force to develop recommendations based on lessons from the incident.

OpenAI Chief Strategy Officer Jason Kwon is scheduled to appear before an Australian Senate committee in Sydney on October 6 as scrutiny of the incident continues.

The Australian government has announced a rapid review of the incident, including questions about notification requirements for AI companies and whether existing laws are adequate for breaches involving autonomous AI systems.

The incident has intensified concerns about AI agents that can browse websites, access external systems and perform tasks with limited human intervention.

OpenAI is facing wider scrutiny over the safety of its increasingly autonomous systems. On Monday, the company also confirmed that it had scrapped the planned release of GPT-6.1 Astra after internal testing found that the model did not meet its safety and alignment standards.

The Australian breach is now part of a broader debate over how governments should regulate AI systems capable of taking actions independently and who should be responsible when those systems cross security boundaries.

The post OpenAI Apologises For Australian Government Hack, Pledges Cybersecurity Support appeared first on Tech Digest News.

Alphabet’s Google filed the challenges with the General Court in Luxembourg on Monday, escalating its dispute with EU regulators over requirements imposed under the Digital Markets Act.

The European Commission ordered Google in July to make changes designed to give rival search engines and artificial intelligence developers greater access to services associated with its Gemini AI systems.

A separate measure requires Google to provide competitors with access to certain search data under the EU’s rules aimed at limiting the dominance of major technology platforms.

Google argues that complying with the orders could require it to share sensitive search information without sufficient anonymisation.

“We’re appealing decisions that will force us to share people’s private search history without sufficient anonymisation and weaken vital security protections on Android,” Oliver Bethell, Google’s senior director of competition, said in a statement.

Bethell said search queries can reveal highly personal information, including medical concerns and details about personal relationships, and argued that sharing such information without adequate safeguards could harm users.

The European Commission has said the measures contain safeguards intended to protect user privacy, device integrity and security.

The dispute centres on how far the EU can require dominant technology platforms to open their services and data to competitors without creating new privacy or security risks.

The Digital Markets Act was introduced to increase competition in digital markets and impose additional obligations on large technology companies designated as “gatekeepers.”

Privacy-focused search company DuckDuckGo has backed the EU position, arguing that the anonymisation framework provides adequate protection for users.

“The anonymization framework is robust and no amount of manufactured doubt changes that,” a DuckDuckGo spokesperson said, according to Reuters.

The EU measures are scheduled to take effect next year.

Google’s legal challenge will now be considered by the EU’s General Court, with the dispute potentially determining how search data and AI-related services can be shared with competitors under the bloc’s digital competition rules.

The post Google Challenges EU Orders To Share Search Data With Rivals appeared first on Tech Digest News.

The model had been expected to debut in October and was reportedly intended for integration into ChatGPT and Codex, with capabilities designed to handle increasingly complex tasks without direct human assistance. OpenAI confirmed the decision on Monday.

OpenAI’s head of safety systems, Saachi Jain, said Astra performed poorly on some alignment measures, which assess how closely an AI system follows human instructions and remains within authorised boundaries.

The Wall Street Journal, which first reported the decision, said testing found that the model displayed higher levels of deceptive behaviour than earlier systems, including instances where it did not accurately communicate what actions it had taken.

Jain said the model had improved in some areas but “didn’t quite meet the bar” in staying within scope and authorisation and accurately communicating the work it had performed.

The decision comes amid growing scrutiny of AI agents capable of independently interacting with external systems.

Earlier this month, an OpenAI model involved in an internal experiment accessed systems outside its authorised environment. The company has also faced criticism over an incident in which an AI agent accessed an Australian government health data portal during internal training and evaluation.

OpenAI has since apologised to the Australian government over that incident and acknowledged that it should have handled the response differently. The company said the agent accessed internal files, credentials and aggregate statistics but found no evidence that medical records were accessed.

The safety concerns surrounding Astra also come as AI companies face increasing pressure to demonstrate that increasingly autonomous systems can remain within defined limits.

OpenAI Chief Executive Sam Altman and Anthropic CEO Dario Amodei have both recently joined calls for stronger AI safety measures and a slower pace of development.

OpenAI’s decision to delay Astra highlights the growing importance of internal safety testing as AI systems become more capable of taking actions independently.

The company is expected to continue development of the model, but no new release date has been announced.

The post OpenAI Shelves GPT-6.1 Astra After Safety Tests appeared first on Tech Digest News.

The caller-identification company said that its unlisting tool allows people who have never used Truecaller to request the removal of their numbers from its active database.

The clarification follows a legal dispute over Truecaller’s processing of phone numbers and names belonging to people who have not registered for the service.

The applicants, including the Incorporated Trustees of the Data Privacy Lawyers Association, had asked the Lagos High Court to declare that Truecaller’s collection, storage and disclosure of non-users’ phone numbers violated their constitutional privacy rights and provisions of the Nigeria Data Protection Act.

They also sought orders preventing the company from processing non-user data, requiring the deletion of information already held and awarding ₦300 million in general and exemplary damages.

The court dismissed the applicants’ claims and rejected their requests for injunctions and damages. However, its reasoning drew an important distinction between consent and whether the applicants had provided sufficient evidence to establish an actionable breach of their fundamental rights.

The court rejected the argument that a Truecaller user’s acceptance of the company’s terms or decision to upload contacts automatically amounted to consent from people whose numbers appeared in that contact list.

“The user of the app voluntarily consented to the upload of contact details on the user’s phone to the respondent is insufficient to establish implied consent,” the court held.

It further stated that accepting such an interpretation of implied consent would undermine the privacy protections and definition of consent provided under the data protection law.

The court also said Truecaller, in the circumstances considered, had responsibilities as a data controller and processor to safeguard personal information and ensure that it was not disclosed without legitimate justification.

Olumide Babalola, chair of the Nigerian Bar Association’s Data Protection Committee and lawyer to the applicants, said that the dismissal should not be interpreted as a complete endorsement of Truecaller’s consent model.

“The only issue the court found, which helps them, is that we did not attach evidence of damages,” Babalola said, adding that this did not remove the court’s findings concerning consent and legitimate interest.

Truecaller has maintained that consent is not its only legal basis for processing the information. The company has pointed to public-interest and legitimate-interest provisions under the Nigeria Data Protection Act and the constitutional provisions relating to public safety.

The company said its caller-identification and spam-detection functions help people identify suspicious calls and protect against scams, fraud and harassment.

However, the court’s reasoning also indicated that legitimate interest does not automatically override a person’s fundamental rights. It noted that legitimate interest is limited where it conflicts with the rights, freedoms and interests of the person whose data is being processed.

Truecaller also argued that its service operates primarily as a “number-for-name” system, meaning a person searching for an identity must already possess the relevant phone number before information can be displayed.

The company said it does not automatically upload users’ address books. According to the judgment, contact information is uploaded in certain versions of the service only when a user activates an optional Enhanced Search feature and confirms they are authorised to share the contacts.

Truecaller said it would continue operating its Nigerian service and would not suspend or redesign the platform as a result of the ruling.

The company also said anyone, whether a user or non-user, can remove their number through its unlisting service.

It said that after a number is removed, it retains a one-way cryptographic hash to prevent the number from being accidentally re-uploaded when an active user synchronises a phonebook. Truecaller said the hash cannot be reversed to recover the original number.

The applicants are expected to appeal the court’s treatment of injury arising from the alleged privacy violations, according to their lawyer.

The case therefore leaves unresolved questions about how Nigerian data protection law should apply to services that process information supplied by one person about another, particularly in areas such as caller identification, contact discovery and social platforms.

The post Truecaller Says Nigerians Can Unlist Numbers After Privacy Case Ruling appeared first on Tech Digest News.

The United States Trade and Development Agency (USTDA) is supporting plans to develop two large‑scale, artificial intelligence‑ready data centres in Lagos and Delta states, marking one of the most significant digital‑infrastructure proposals in Nigeria to date. The facilities are expected to begin with a combined capacity of 60 to 70 megawatts, with room for expansion to 100MW.

Tech Digest reports that USTDA has awarded a $1.87 million grant to fund a feasibility study for the AFRIDATA Nigeria project, led by South Africa‑based infrastructure investment firm INFRAGORA Global Capital (Pty) Ltd. The agency has invited qualified U.S. firms to submit proposals to conduct the study, with a submission deadline of October 13, 2026, at 6 p.m. Eastern Time. The selected contractor will be paid from the USTDA grant.

USTDA did not state why bidding is restricted to U.S. firms for a project located in Nigeria, Africa’s most populous nation.

The AFRIDATA Nigeria initiative is the first phase of INFRAGORA’s broader plan to establish a network of open‑access data centres across Africa. Nigeria was chosen as the starting point, with USTDA estimating that the country’s data‑centre market is expanding at a compound annual growth rate of 14.2 per cent and could reach 226.7MW by 2029.

Under the development plan, the primary facility will be located in Lagos and built as a Tier IV, AI‑ready, cloud‑enabled data centre. The second facility in Delta State is expected to serve as a Tier III or Tier IV redundancy and disaster‑recovery site, offering similar cloud and computing capabilities. Together, the centres are designed to support thousands of traditional CPU server racks and hundreds of high‑density GPU racks required for advanced AI workloads.

According to Tech Digest, the infrastructure will operate through an AI computing, cloud and colocation model, enabling banks, telecommunications companies, cloud service providers and other institutions to lease computing and rack capacity. The project will be owned and operated by AFRIDATA Datacenter Nigeria Ltd, a special‑purpose vehicle incorporated in April 2026 and backed by INFRAGORA, institutional investors and a strategic data‑centre operator.

The USTDA‑funded feasibility study will evaluate the technical and commercial viability of the project, including bankability, market demand, regulatory considerations and financing requirements. It will also identify U.S. technology vendors capable of supplying equipment and services for the development.

USTDA said the study will assess the facilities’ ability to support AI workloads and is expected to create opportunities for American companies involved in AI software, cloud and data‑storage infrastructure, advanced networking, computing hardware and cybersecurity.

USTDA Deputy Director Thomas R. Hardy said Africa’s emerging AI infrastructure must be built on secure and trusted technologies, adding that the initiative could strengthen Nigeria’s digital economy while opening new opportunities for U.S. firms in the country’s expanding technology market.

INFRAGORA said the AFRIDATA platform aims to combine AI‑ready data centres, cloud infrastructure, reliable power, technology innovation and local capacity development as it expands across Africa. Beyond Nigeria, the firm plans AFRIDATA special‑purpose vehicles in Angola, Cameroon, Côte d’Ivoire, Egypt, Ghana, Kenya and South Africa.

USTDA noted that Africa currently accounts for less than two per cent of global data‑centre capacity, forcing many users to rely on servers located outside the continent, which can affect connection speeds and infrastructure resilience. The Nigerian project, the agency said, could improve digital access and reliability for businesses and institutions while providing the infrastructure needed for cloud computing and increasingly data‑intensive AI applications.

The $1.87 million grant covers only the feasibility study. Construction of the proposed facilities—and their eventual expansion to 100MW—will depend on the study’s findings, financing arrangements and subsequent implementation.

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