Therefore, in the AI era, development is not only a function of infrastructure, capital, or policy. It is a function of trust, and trust must now be engineered. This is irreducible and I hope the Federal Government will direct the Federal Ministry of Communications, Innovation and Digital Economy to begin, quickly, a scalable, phased implementation of Nigeria’s National Artificial Intelligence Strategy (NAIS).
My presentation with the above title, was the first lead paper at the opening ceremony of the First Mass Communication International Conference that took place at the main auditorium of the permanent site of Usmanu Danfodiyo University, Sokoto.
In the preamble, I reiterated that communication IS NOT MERELY THE TRANSFER OF INFORMATION but a meaning-making and meaning sharing activity characterised by shared intentionality – a purely cooperative activity of mutual understanding and shared intent and mutual goals. Yes, the goals are constant. Burgoon and Ruffner (1978) concluded their reasoned definition of communication with that proviso and it is still valid. As such, communication pushes parties involved towards a common ground for the formation of social reality. This is the reason that communication is fundamentally a cooperative social process of meaning-sharing and meaning-making.
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Inspired by “A Usage-Based Theory of Language Acquisition” (Tomasello, 2005), I recalled that communication heralds language, as evident in children’s use of gestures, pointing and pantomimes in communication during their pre-linguistic years and how humans incrementally acquired language. I advanced the logic of cognitive and developmental science, giving it a push with Yuval Harari’s (2011) ‘Cognitive Revolution’, thus implicitly rejecting Chomsky’s (1957, 1959) ‘generative grammar’ and its foundational theory, ‘universal grammar’. I was intentional, certainly not absolutist because there is no absolutism in academia but I wanted to reimagine communication in a more contextual, rational, and contemporary sense.
I mean, how can we hold on to such a simplistic definition of communication when, today, a brief remark or a press statement – frequent, popular activities of communication management – no longer constitute mere information, the moment they hit the virtual networks. As Achi (2026) noted, “a single statement becomes a national [or global] conversation, reputation is no longer shaped by what was said alone. It is shaped by how fast meaning is assigned to it” and meaning is assigned in the context of a variety of pressures in the social environment, Nigerian ‘fault lines’ and geopolitics, legitimate or inordinate emotions, including those emanating from the avant-garde of a largely informed but restless demography of upcoming persons. This is the context in which Moniepoint’s Eniolorunda’s recent concern was received, although he goofed or perhaps did not remember that what you say is not as memorable as how you say it.
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Anyway, I reflected briefly on theory. What about the place of theory, broadly speaking? I explored Amartya Sen’s “The Capability Approach”, Everett Rogers’ “Diffusion of Innovation”, and “Technological Determinism”, particularly from the lens of Marshal McLuhan, to explain how Nigeria might approach the adoption of Artificial Intelligence. I used my work (Ibietan, 2023:107) to explain the role of theories in research and professional practice, as perspectives that offer general clarifications about what a study might reveal, or explain the dimension through which a researcher is investigating a phenomenon. Theories basically exist to explain and interpret situations, to enhance the understanding of our world, our interpretation of occurrences and to support our effectiveness in professional practices.
I spoke to the value of AI and possible derivable benefits and appreciated the Federal Government’s affirmation of the National Artificial Intelligence Strategy (NAIS) 2025, which I reviewed and requested participants at the conference to review too. Nigeria surely needs to be in the AI optimisation loop, as the technology becomes the key driver of the Fourth Industrial Revolution (FIR), but we need to tease out and implement the strategy in phases, and with a focus on culture institutions like the media, then security, agriculture, education (broadly) and health. I stated that if we adopt good models, funding may not really be an issue. The five pillars consolidated into three focal areas and the 32 strategic objectives of NAIS 2025 look good and imaginative, but I wish there was sufficient and more objective considerations for impact assessment.
Kenya recently called off a partnership with Microsoft on data centres because the country found that it had no capacity to generate the amount of electricity required for it. Nigeria already identified funding, “ethical applications, algorithmic transparency, data privacy and potential labour market displacement,” but we must revisit the impact on other resources of life we require to survive. Indeed, we may also need to reflect on the warnings of Pope Leo XIV (and his immediate predecessor), Yuval Noah Harari and Kissinger et al. (2021) on the general direction and use. AI is a tool; we cannot make it a thought leader.
Reimagining the Media In the Era of Artificial Intelligence: The Blackbox Problem: When AI Becomes the Writer and the Editor
Blackbox, a proper noun representing a variety of things, is essentially used figuratively and descriptively here to refer to a paradigmatic shift in the communication space where AI now performs functions once reserved for human editors – content curation, algorithmic amplification, headline generation, audience targeting, and increasingly, story selection itself. These functions shape what millions of citizens see, believe, and act upon. Yet the mechanisms behind these outputs remain largely invisible, operating within what can be described as the Blackbox – systems whose logic, training data, bias structures, and decision pathways are opaque to editors, audiences, and regulators alike.
The Glassbox side of the coin: When Transparency, Trust-Building, Accountability and Responsibility Take Charge
Glassbox, also a proper noun for many entities and applications, is used here metaphorically to represent another order, a counterpoint to the despicable reality that the depicted Blackbox throws at us.
The distinction is critical. While Blackbox AI produces outcomes without accountability for process, the Glassbox AI produces outcomes that are interpretable, auditable, and correctable. In the context of media and national development, this is not a technical nuance – it is a governance question.
An AI system that determines which communities receive health information, which political voices are amplified, which economic narratives dominate and many more, is not a neutral tool. It is an unelected editorial authority operating without visibility or obligation to national interest. For nations such as Nigeria, where the media play a constitutionally recognised role in national development (Section 39 of the Constitution), the implications are profound – when the algorithm becomes the gatekeeper and its gate is invisible, real communication as fundamentally a process and activity of mutual understanding and sharing of intentions and, more importantly, development communication, lose their democratic character and their essences are vitiated.
The Verify Protocol: Defending Truth In Real Time
Achi’s (2026) VERIFY Protocol comes not just handy but to the rescue because the readily potent threat that AI poses to media’s developmental role is the industrialisation and manufacturing of falsehoods. Synthetic media – deepfake videos, AI-generated audio, and fabricated news content – now operate at a scale and speed that outpace traditional editorial verification systems. One implication of this is the creation of a climate of structural imbalance that enables falsehood to travel at algorithmic speed, while truth moves at institutional pace. Consequently, we will have a regime of reputation lopsidedness (troubling asymmetry), where damage to public trust accumulates faster than it can be corrected.
To address this, media institutions must move from correction to systemic verification using the VERIFY Protocol – a structured, six-stage real-time framework for media institutions confronting AI-generated misinformation. It transforms editorial verification from a reactive process into a systemic institutional defence.
V – Validate the Source – Authenticate the originating account, channel, or publication before any editorial engagement with the claim.
E – Examine the Signal – Analyse the claim against known data, expert consensus, and cross-platform presence.
R – Reconstruct the Timeline – Establish when the claim first appeared, how rapidly it spread, and which amplification nodes drove its reach.
I – Interrogate the Intent – Apply forensic linguistics and metadata analysis to assess whether the content exhibits characteristics of deliberate deception.
F – Flag or Forward Content that fails – VERIFY thresholds is flagged for editorial quarantine and escalated for specialist review before any further distribution.
Y – Yield a Public Record – Every VERIFY determination is logged, published, and contestable. This creates the institutional accountability that Blackbox AI systems systematically deny.
When applied institutionally, the VERIFY Protocol transforms media organisations from passive victims of AI-generated misinformation into active defenders of the information environment; a precondition for effective development communication in the AI era.
Engineering of Trust: The Developmental Doctrine
Last year, in my presentation to the Nigerian Public Relations Week at Uyo (interestingly also the first paper of the conference even before the opening ceremony) I gave reasons why Edward Bernays’ (1947, 1955) ‘Engineering of Consent’ should be discarded because its foundational logic offends three key doctrinal thoughts that I find more reasonable. First is the philosophy of Ọ̀rúnmìlà (in its spiritual offerings and as a knowledge system), second is Martin Buber’s (1923/1937) ‘I and Thou’, and the third is Tomasello’s (2005, 2008) ‘shared intentionality’.
In any case, how do you engineer consent through a model analogous to the Hypodermic Needle Theory successfully in an era in which attentional resources have been ruptured! Extracting attention from its ecology is so central to successful communication, that is why ‘attention’ is fundamental to any discourse on communication – one reason Tomasello is more interesting to me in reconstructing language and communication.
Therefore, if we want to heed the counsel of Buber that “When we encounter another individual truly as a person, not as an object for use, we become fully human”, then we need to migrate quickly from the engineering of consent to the engineering of trust. Therefore, if the Blackbox–Glassbox framework defines the problem, and the VERIFY taxonomy foregrounds and addresses the operational challenge, the Engineering of Trust provides the foundational doctrine for the AI era.
What is Engineering Trust?
It is the deliberate design of AI-media systems, data flows, and governance structures that make truth visible, traceable, and fosters institutionally accountability. It shifts the central question from: How do we communicate credibly and with the imprimatur of credibility? To: How do we build systems where credibility is inevitable?
So, we advance the argument that THE ENGINEERING OF TRUST MODEL assumes life through three system-level commitments – Transparency (Glassbox Systems), an AI system that is interpretable, auditable, and open to scrutiny; Verification (Real-Time Integrity Protocols) that ensures information is continuously validated through structured mechanisms such as VERIFY; Accountability (Human Governance Layer) that ensures every algorithmic outcome is mapped to a visible institutional and human responsibility. This integrative and structured template transforms trust from a communicative outcome into a designed system property.
Let us quickly reflect on the implications of the Black-Glassbox Paradox for media and national development. If we fail to engineer trust, the consequences are huge and the destruction to our social fabric will be incalculable, but four are readily discernible – erosion of institutional credibility, increased susceptibility to misinformation, weak citizen-state engagement, and declining global reputation.
Conversely, nations that successfully implement Engineering of Trust will unlock: scalable citizen engagement, real-time governance intelligence, credible national storytelling, and stronger investment and diplomatic confidence.
Concerning the last point, the central idea is that while all the citizens of a nation cannot all be good people, the bad guys must be subdued through majority of the good people’s organised conscious self-activity in unofficial ambassadorial capacity, because trust is not a soft asset. It is national infrastructure and nations that want to leverage it must architect it intentionally.
What are the policy implications for Nigeria? We need a Glassbox Disclosure Standards, an AI Verification Competency Framework (Remember VERIFY), a National AI-Media Trust Index, and an Institutionalisation of Trust Audits (RPI-aligned). The Reputation Perception Index is a huge field of exploration. It is built on seven pillars of reputation and perception, comprising 23 distinct attributes and evaluated using a methodologically driven scoring system. So, that is a different discourse entirely.
As I move to closing my presentation, I emphasised that the role of the media in national development is not diminished by artificial intelligence, it is intensified by it; media institutions that can maintain integrity, govern AI transparently, and engineer trust will become indispensable to national development. Those that cannot risk becoming vectors of instability; nations that do not engineer trust into their AI-media systems will not merely struggle with misinformation; they will struggle with legitimacy itself.
Therefore, in the AI era, development is not only a function of infrastructure, capital, or policy. It is a function of trust, and trust must now be engineered. This is irreducible and I hope the Federal Government will direct the Federal Ministry of Communications, Innovation and Digital Economy to begin, quickly, a scalable, phased implementation of Nigeria’s National Artificial Intelligence Strategy (NAIS). This can be considered for media and culture institutions while pragmatic thinkers and patriots can be rallied to give us template to implement similar ideas in education, health, agriculture, and importantly in the security governance sector. Nigeria is behind but it is not too late to start.
Omoniyi Ibietan is the secretary general of the African Public Relations Association (APRA).
