E-Business
The Onslaught of Artificial Intelligence (AI) part 3
By Evans Woherem, Ph.D
- The Ethical Implications of Giving AGI a Human-Like Brain
Are we trying to give AGI a human-like brain and make it self-aware? This seems to be what we are doing, advertently or inadvertently. The question of whether to give AGI self-awareness and consciousness is a contentious issue.
Some argue that replicating and understanding human intelligence is a crucial step for AGI to perform tasks such as creativity, empathy, and moral reasoning. Others argue that it is unnecessary and even dangerous, as the actions of a self-aware AGI are uncertain, and it could lead to unintended consequences.
It is important to consider the ethical and moral concerns that arise from the development of AGI with a human-like brain, including the entity’s rights and obligations, and society’s treatment of it.
Isaac Asimov, a science fiction author and biochemist, was one of the first to explore these ethical issues in his famous “Three Laws of Robotics” in which he proposed guidelines for the safe and ethical use of robots and AI.
These laws include the prohibition on robots harming humans, the requirement for robots to obey human orders, and the obligation of robots to protect their existence as long as it does not contradict the first two laws.
Asimov’s laws provide a useful framework for considering the ethical implications of AGI, and his work continues to be relevant today as we grapple with the ethical challenges posed by the development of AGI.
It is important for researchers, policymakers, and industry leaders to carefully consider these ethical implications as AGI technology continues to advance and to ensure that AGI systems are developed with a clear understanding of their limitations and potential risks.
Therefore, it is important for researchers, policymakers, and industry leaders to carefully consider these ethical implications as AGI technology continues to advance and to ensure that AGI systems are developed with a clear understanding of their limitations and potential risks.
The Ethical and Societal Implications of Global Human Consciousness
The concept of a global human consciousness, or a “world brain,” refers to the idea that advancements in technology, particularly AI and the internet, are allowing for the collective intelligence of humanity to be harnessed in a way that has never been possible before. With the advent of technology like ChatGPT, which allows for easy access to information and the ability to ask questions, it is becoming increasingly possible for individuals to access and share knowledge on a global scale.
The world is now aware of what GPT-3 is capable of doing! Imagine what happens when it’s upgraded to GPT-4 and then GPT-10. We’ve been told that GPT-4, once completed, would be 500 times more competent than GPT-3.
Today, students may use ChatGPT to produce essays, term papers, and even theses. Professors have started utilizing GPT to edit the chapters they have written and even to help with book chapter composition. Every organization can now use GPT to accomplish practically everything, potentially reducing the need for human personnel.
When I look at a new technology that has been invented in our attempts to build an AGI, like ChatGPT, I believe it appears we want to build a “world brain”, which can be used for both good and ill.
ChatGPT has an excellent level of human-to-human communication. It can be as plain as many people usually are in conversations, yet it can also get as technical as others might want. Any question you ask will have an intelligent response, so feel free to ask anything.
It can be your research assistant, write essays for you, draw pictures, and write poems for you, and so on. Individuals can now utilize it for free via the internet. It could replace search engines in applications like Google and Facebook and provide all the answers to questions in applications like Quora.
Building a “world brain” is a goal shared by many organizations besides OpenAI. Numerous other research facilities are working to create a world brain, both in the West and in other nations like China and Japan.
They are all doing so, perhaps unwittingly or unconsciously, working to develop systems with narrow domains such as chatbots, language synthesis systems, language generation systems, and deep learning systems.
Some of them have the explicit goal of developing AGI. However, the development of a global human consciousness raises important questions about the nature of human identity, agency, and autonomy.
Moreover, there is a societal implication that, if not properly addressed, could lead to a widening of the digital divide and further marginalization of certain groups. Access to and control over information, technology, and resources will be crucial to ensure a fair distribution of benefits and opportunities in the world
- Africa, AI, and Other Exponential Techs
In all of the above, where is Africa? Why is there a deafening silence on all of the promethean-level technologies in Africa? Why does Africa continue to adopt a “follow-follow” mentality? Why does Africa think that the world is only meant for some others to recreate without its input? Whatever eventually becomes the world, unfortunately, Africa will also be immersed in it.
Africa is so busy with its day-to-day existential issues, along the lines of Maslow’s Hierarchy of Needs, to the point that the business of rethinking the world and our existence is left to others, particularly the conceptual West, to do on behalf of humanity. My concern is that it is only a few in the West, such as the AI intelligentsia, who are trying to recreate the world and human existence.
They seem to have an unspoken agenda, an atheistic agenda, an anti-God agenda, an agenda that wants to build a new Tower of Babel, and, an agenda that wants to create a new version of humanity. Does Africa agree with their agendas?
It is important for Africa to also be a part of these conversations and developments in technology, as it will ultimately affect the continent just as much as any other region. Africa should not be left behind in the shaping of the future, and should actively participate in the rethinking of the world and our existence.
It is also important to consider the potential consequences and ethical implications of these technologies and to have a diverse range of perspectives and voices involved in the decision-making process.
Furthermore, Africa should also take into account its values and beliefs, and ensure that they are not being overlooked or disregarded in the pursuit of technological advancement.
- Control and Regulation of AI
The control and regulation of AI refers to the various measures put in place to ensure the safe and responsible use of artificial intelligence technology.
This can include guidelines for the development and deployment of AI systems, as well as laws and regulations that govern the use of AI in specific industries or applications. Some of the key concerns that are addressed through AI regulation include issues related to privacy, security, and the potential for AI to impact jobs and the economy.
Additionally, there are also ethical concerns related to AI, such as the potential for AI to perpetuate bias or make decisions that negatively impact certain groups of people.
Several guidelines have been proposed for the development and deployment of AI systems, including explainability and transparency, fairness and non-discrimination, human oversight, safety and robustness, privacy and security, continuous monitoring and improvement, accountability, human rights, societal and environmental well-being, and human-centred values.
These guidelines aim to ensure the safe and responsible use of AI, but there is no one regulatory body overseeing their implementation.
There are currently a limited number of laws and regulations specifically governing the use of AI, but as the technology continues to advance and its impact on society becomes more significant, more laws and regulations are likely to be developed. Some examples of existing laws and regulations that govern the use of AI in specific industries or applications include:
- Health Care: The US Health Insurance Portability and Accountability Act (HIPAA) regulates the use of AI in healthcare by protecting the privacy and security of patient data.
- Finance: The General Data Protection Regulation (GDPR) in the European Union regulates the use of AI in finance by protecting the privacy and personal data of individuals.
- Autonomous vehicles: The National Highway Traffic Safety Administration (NHTSA) in the US has issued guidance on the safe testing and deployment of autonomous vehicles, which includes requirements for data recording and sharing, cybersecurity, and human oversight.
- Employment: Many countries have laws that prohibit discrimination in the workplace, which can apply to AI systems used in the hiring process or the management of employees.
These are just a few examples, regulations may vary from country to country, and it is important to keep in mind that laws and regulations are always changing as technology advances and society’s understanding of it evolves.
- Conclusion
As Artificial Intelligence (AI) continues to evolve, it is expected to have a significant impact on how we live and work. Many people look at the development of AI with a positive outlook, I share that sentiment but also with concerns. I believe that it is like opening a box of unknown consequences that humanity will regret.
I am worried that there are no worldwide regulations and control systems in place to govern the design, development, and application of AI. Without these, we can’t ensure that AI will be safe for humanity. Moreover, I do not see any significant efforts being put into implementing Asimov’s laws of robotics, which could be used to ensure safety features are built into AI systems.
The ethical implications of AI must be taken into account by society, and its creation and application must be consistent with human values. This may involve creating regulations and guidelines for the use of AI, as well as investing in retraining programs to assist individuals whose jobs are at risk of being replaced by AI.
Overall, the integration of AI is a complex issue that requires a thorough understanding of the potential benefits and risks of this technology. It is essential for society to have open and honest conversations about the implications of AI and to collaborate to ensure that its development and use align with human values and promote the well-being of all individuals.
Woherem is a highly respected industry professional and alumnus of Harvard Business School, wrote in from Abuja, Nigeria
A new global Kaspersky Security Services report ‘Anatomy of a Cyber World’ reveals a blind spot in enterprise Security Operations Centers (SOCs): while performance is typically measured by detection and response speed, organisations rarely assess whether they’re detecting the right threats.
Large portions of collected telemetry don’t enter real-time detection pipelines, creating hidden gaps that internal assessments tend to miss – and fuelling demand for independent SOC Consulting to uncover them.
As organisations continue to invest in SOCs, measuring the real performance of these departments remains a challenge. Operational effectiveness depends not only on the volume of collected data, but on how well that data is used for detection.
According to a recent Kaspersky global survey, organisations typically evaluate SOC effectiveness through a limited set of key performance indicators: mean time to respond (MTTR) and detect (MTTD) dominate the picture, while deeper indicators like false positive rates or cost per incident remain secondary.
The real question is not just how fast the SOC responds, but whether it is detecting threats before they escalate.
The findings from the Kaspersky Security Services Global Report tell a consistent story: most SOCs are collecting far more data than they are using for detection.
The mean correlation rule coverage across assessed organisations stands at 43%, meaning that on average, active detection logic covers less than half of all ingested data sources.
The rest sits in the platform, available for retrospective investigation, threat hunting, or compliance purposes, but invisible to real-time detection.
This gap is not always unintentional. Some data is deliberately collected outside the scope of active correlation, serving investigation or regulatory requirements. But in many cases, sources are onboarded without a clear detection plan or with rule development deferred and never completed.
However, this is more typical of mature SOCs: in less mature environments, the data is often collected but never actually used.
There are several reasons for that, including sources onboarded ahead of planned rule development, compliance-driven collection without active correlation requirements, unclear internal ownership of detection logic, and resource constraints deferring engineering work indefinitely.
However, the result is the same either way: significant portions of the environment are effectively unmonitored in real time.
What makes this harder to solve is that the problem tends to grow with the organisation. SOCs managing the highest data volumes cover only around 30% of their sources with active detection logic.
As infrastructure expands, detection engineering capacity rarely scales at the same pace. The sources most consistently left without coverage are network telemetry, databases, and web servers – foundational infrastructure that should be at the core of any detection strategy.
The approach to detection logic itself varies widely. Around 50% of assessed SOCs rely primarily on vendor-provided rule sets, while roughly 40% build their logic from scratch. Vendor-reliant teams frequently face elevated false-positive rates and coverage gaps from insufficient tuning; those dependent on EDR carry blind spots where cross-source correlation is absent.
Meanwhile, a lot of organisations set their SOC’s detection scope at initial design and never revisit it, meaning blind spots accumulate silently as infrastructure evolves.
“Even with defined KPIs in place, assessing SOC effectiveness internally remains difficult due to insider view bias, which is why organisations are turning to external SOC Consulting to evaluate detection logic, analyse event flows and simulate attacks to understand what is actually being caught.
To improve, organisations should build a structured detection engineering process: a repeatable discipline for developing, validating and regularly reviewing detection logic,” comments Roman Nazarov, Head of SOC Consulting at Kaspersky.
To align internal processes and technologies with today’s evolving threat landscape, organisations can explore Kaspersky SOC Consulting, which helps build an in-house SOC from scratch, assess the maturity of an existing one, or enhance specific capabilities such as detection and response procedures.
In 2025, the most common consulting projects were SOC Technical Assessment (23.4%), SOC Framework Development (20%) and both SOC Maturity Assessment and SIEM Quality Assurance (11.7% each), reflecting a growing demand for deeper visibility into SOC performance.
To learn more about SOC detection effectiveness and practical steps to strengthen your security monitoring, read the full report.
The ‘Anatomy of a Cyber World’ is a comprehensive global report drawing on incident statistics from Kaspersky Managed Detection and Response, Kaspersky Incident Response, Kaspersky Compromise Assessment and Kaspersky SOC Consulting, shedding light on the most prevalent attacker tactics, techniques and tools, as well as the characteristics of detected incidents and their distribution across regions and industry sectors.
Bloomberg has released its second annual “25 African Startups to Watch” list, underscoring the growing influence of venture-backed innovation across the continent.
Published thursday, the list highlights companies building solutions in “environments where infrastructure or systems have failed to deliver.”
The featured start-ups build solutions to challenges such as accessing healthcare in Chad, moving goods in Kenya, securing loans in South Africa, and safeguarding borders in Nigeria.
Nigeria, South Africa and Kenya jointly lead with four companies each, reflecting the ongoing strength of Africa’s three most visible start-up ecosystems.
The 25 companies span 13 countries and sectors including healthcare, fintech, security, climate resilience, waste management, and transport.
Nigeria’s four startups are 10mg Health, Remedial Health, Sycamore and Terra Industries, covering areas from healthcare financing and pharmaceutical supply chain integrity to digital lending and defence technology.
South Africa’s contingent includes Omnisient, Amesect, AURA and Jem. Omnisient uses grocery purchase data and AI to extend credit to those outside traditional financial systems.
Kenya’s notable four include Zeraki, a school-data analytics platform partnering with Safaricom to reach secondary students across the country.
According to Bloomberg, a defining theme this year is the source of funding.
Nearly half of the total capital raised by these start-ups came from African investors, marking a shift from previous years when international capital predominantly drove early growth.
International backers such as 8VC, controlled by Palantir Technologies co-founder Joe Lonsdale, and Google continue to see value in investing in African companies, Bloomberg noted.
The report also highlights that start-ups across the continent almost doubled their debt fundraising in 2025, even as equity financing from venture capital firms declined.
Separately, the Start-up Ecosystem Report 2026 states that Kenya has overtaken Nigeria as Africa’s top startup investment destination, attracting $984 million in 2025.
Jennifer Zabasajja, Bloomberg Television’s chief Africa correspondent and anchor, highlighted the dual significance of the list, the variety of solutions being built and the growing role of African-sourced capital in backing them.
She noted that the list comes at a consequential moment, one shaped by global disruptions, from the conflict in Iran to sweeping cuts in US foreign healthcare assistance, that have made the case for African-owned capital more urgent than ever before.
Nigeria Data Protection Commission has warned that the growing misuse of personal data and digital platforms could undermine Nigeria’s democratic process ahead of the 2027 general elections.
NDPC
The warning was delivered during the 2026 Press Week organised by the FCT Council of the Nigeria Union of Journalists in Abuja.
Speaking at the event, Vincent Olatunji, national commissioner and chief executive officer, NDPC, who was represented by Itunu Dosekun, head of Media Unit at the commission, said disinformation and unlawful exploitation of personal data posed serious threats to credible elections.
The event had the theme: “2027 Election: Defending Democracy in the Era of Disinformation.”
Dosekun said the struggle for credible elections was no longer confined to polling units, noting that digital platforms had become major channels for manipulated narratives, fake news, propaganda and AI-generated misinformation.
According to him, the rapid growth of social media platforms, messaging applications and data-driven political campaigns has created vulnerabilities capable of influencing voter perception and weakening public trust in democratic institutions.
He warned that the abuse of personal data for political profiling and psychological targeting had become one of the most dangerous threats facing democracies worldwide.
“The misuse of citizens’ personal information carries serious social implications, especially for vulnerable groups who may not fully understand how their data is harvested, processed and weaponised online,” he said.
Dosekun noted that coordinated disinformation campaigns could inflame ethnic tensions, spread fear and discourage civic participation, particularly among young Nigerians.
He described the Nigeria Data Protection Act, 2023, as a critical legal framework aimed at protecting citizens against unlawful data processing and digital exploitation.
According to him, the law gives Nigerians greater control over their personal information while placing obligations on organisations, institutions and political actors to handle data responsibly.
Dosekun also called for stronger collaboration among political parties, media organisations, technology firms, civil society groups and citizens to promote responsible digital behaviour ahead of the elections.
He stressed the role of journalists and media professionals in combating fake news, fact-checking information and safeguarding public discourse.
According to him, protecting personal data should not only be seen as a privacy issue but also as a democratic responsibility necessary for maintaining public confidence, national stability and electoral credibility.
Stakeholders at the event emphasised the need for improved digital literacy, stronger regulation and increased public awareness to prevent the abuse of digital platforms during future elections.
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