E-Business
The Onslaught of Artificial Intelligence (AI) part 2

By Evans Woherem, Ph.D
The advancement of AGI has ethical and societal implications, as it may alter our interactions with technology and our understanding of intelligence. For example, in the 1980s, Professor Weizenbaum created an AI-based system called ELIZA, which mimics a Rogerian Therapist and was one of the first natural language processing programs.

His system showed the shallowness of human-computer interaction and the risks associated with an overreliance on AI technologies. He was astonished to discover that his secretary had an emotional connection to the system, while using it, as if it were human, despite knowing that he wrote the code for it.
Weizenbaum used this experience to openly criticize the field of AI after he realized that people might treat AI systems like they were people. He argued that the hype surrounding the technology was unjustified and that it was unlikely that machines would ever be able to fully understand human thoughts or emotions.
Weizenbaum’s viewpoint on AI raises the question of whether or not AGI is truly possible and whether or not the concept of AGI is well-defined. It also emphasizes the importance of being realistic about what AI can or cannot do and avoiding overhyping the technology.
It is important to note that the field of AI has evolved significantly since Weizenbaum’s criticism, and some researchers have developed new methods, techniques, and theories that address some of AI’s limitations, such as Symbolic AI, Connectionist AI, and Hybrid AI.
Some AI researchers are working on developing AI systems capable of demonstrating human-like intelligence and consciousness, such as creating AI systems capable of passing the Turing or Chinese Room tests.
It is crucial to remember that Weizenbaum’s worries about AI remain valid today, and the discipline of AI continues to raise ethical and societal implications. As AI systems advance and become more capable, it is critical to consider the implications of their development and application.
For example, as AGI systems become competent at performing tasks previously thought to be unique to humans, it raises concerns about the future of work and the role of AI in society.

Furthermore, as AI systems improve their ability to understand and interpret human behaviour, issues about privacy, autonomy, and the possibility of AI being used negatively by individuals or society as a whole arise.
In light of these concerns, AI researchers and developers must think about the moral and societal implications of their work and develop AI systems that are open, auditable, accountable, and consistent with human values. Furthermore, society as a whole must engage in informed discussions about the future of AI and its potential impacts on our lives.
This includes involving stakeholders from diverse backgrounds and perspectives, such as ethicists, philosophers, sociologists, policymakers, and members of the public, in the development and governance of AI systems.
Additionally, there should be ongoing efforts to ensure that AI systems are developed and used responsibly and ethically, with measures in place to prevent unintended consequences and negative impacts on society.
- Divergent Viewpoints on the Prospects of AGI Morphing into ASI
While some researchers believe that AGI is possible, others think that it’s unlikely and that the concept of AGI is not well defined. The debate over whether AGIs will eventually “morph” into ASIs is divisive among AI researchers and experts for different reasons.
One argument in favour of this viewpoint is that, due to advances in technology and machine learning, AGIs will continue to develop quickly and may one day outperform human intellect in several fields. This means that AGIs will continually grow exponentially over time and eventually transform into ASIs.
However, since there are still many unresolved issues and unknowns surrounding AGI and ASI, many researchers are less optimistic about the timeline for their development. In addition, some specialists believe that the term “superintelligence” is ill-defined and too ambiguous, making it difficult to say whether or when AGIs will develop to that level.
Despite the difficulties, many researchers are still working on developing AGI and ASI because they think the potential advantages outweigh the risks. Improvements in decision-making, increased output, and the ability to solve problems that are currently insurmountable for humans are potential benefits.
However, to benefit from these advantages, the risks associated with AGI and ASI must be decreased by implementing the proper safety measures. In addition to addressing moral and ethical dilemmas, this requires developing strategies for monitoring and controlling AGI behaviour.
As pointed out earlier, majority of AI systems in use today are referred to as “Narrow AIs” because they are designed to carry out specific tasks.

Examples of these types of AI include IBM’s Watson and DeepBlue, Expert Systems, and AlphaGo, all of which exhibit intelligent behaviour within a specific domain, but do not possess the general intelligence that humans have. Some of these systems may have high levels of proficiency or intelligence in their specific areas, but they do not have the broad intelligence that humans possess.
It is important to note that this is often a starting point in the progress towards creating a general AI. Some researchers typically begin by developing AI systems that are particularly skilled in one area and then use the insights and knowledge gained from these systems to advance the development of more general AI systems. Organizations such as the AGI Society, Berkeley Artificial Intelligence Research, CSAIL at MIT, Facebook AI Research, Google DeepMind, and the Human-Level Artificial Intelligence (HLAI) Conference demonstrate that there is ongoing work in the field of AGI and that many experts are working to create more general AI systems.
I am among those who are nervous about the unleashing of AGI systems in our society. I therefore believe that when designing and implementing AGI, it is critical to proceed with caution and care.
Technologies are amoral; they can be used for good, such as increased efficiency and productivity in various industries, but they can also pose risks, such as job displacement, security threats, and ethical concerns, depending on the motivations of those who create them.
Before proceeding with AGI development and implementation, it is critical to consider the potential risks and benefits, as well as the consequences of AGI morphing into ASI and the impact they could have on human jobs and sense of uniqueness in the world.
Even though we still do not have AGIs today, Ray Kurzweil, among other AI experts, predicts that AGIs will be developed by 2045, citing the Law of Accelerating Returns, which deduces that the rate of technological growth is exponential.
It is crucial to keep in mind that these projections are based on current trends and advancements in the field of AI and that developing AGI is a complex and ongoing process that might not occur in a specific order.
It is also worth noting that AGI does not necessarily imply replicating all human capabilities; rather, it could refer to systems that are advanced enough that humans perceive them as AGI, but the consequences of having such systems are unknown.
It could be compared to opening a Pandora’s Box or attempting to construct a new Tower of Babel, with unknown and potentially negative consequences for humanity and the world. I believe in the long run, the net effect will be negative, perhaps even catastrophic, for our earth, unless we do something to regulate them appropriately.
- Implications of AI
Humans have been attempting to increase the forms, types, places, and reach of communication, resulting in the emergence of many forms of communication, including written language, oral language, sign language, and more recently, digital communication.
For example, through the use of books, letters, and other written documents, written language has made it possible for humans to communicate over great distances and long periods. The printing press facilitated written communication after the fifteenth century. The telephone and telegraph enabled long-distance communication in the nineteenth century.
The development of radio, television and the internet has significantly expanded the reach and extensibility of communication and information during the 20th century. Communication with anyone at any time is now possible thanks to the internet and mobile technology. Social networking and instant messaging are new forms of communication as well.
Most machines developed during the agrarian, industrial, and post-industrial eras have ended up deskilling and displacing humans from their traditional vocations, whether in crafts, blue-collar, or clerical work.
However, they have also increased production and opened up new areas of labour for individuals who were displaced. As a result, there have been more employment increases than job losses overall. Many of stakeholders believe that this will always be the case, even for artificial intelligence systems.
However, AI can replace not only monotonous administrative and physical tasks, but also virtually every other job, including those of artists, programmers, teachers, doctors, researchers, lawyers, accountants, and managers—indeed, everyone’s work. Managers have believed that having 1,000 employees will cause 1,000 headaches for them since the beginning of time. So, they will employ whatever machines or methods that allow them to eliminate numerous workers.
However, it is important to note that the impact of AI on the workforce will likely be more complex than simply replacing jobs. AI has the potential to improve human capabilities, produce more work, and create new jobs. Additionally, the rate at which AI will impact different industries and job types will vary, and some jobs may be more resilient to automation than others. It is also important to consider the ethical and societal implications of AI and its impact on the workforce.
For example, there may be concerns about income inequality and the displacement of certain groups of workers. It is crucial for policymakers and industry leaders to carefully consider these issues and develop strategies to mitigate negative impacts while harnessing the potential benefits of AI. Moreover, there is a need to think about retraining programs, education and upskilling of the workforce, and to ensure that the benefits of AI are shared equitably across society.
Continues in part 3…..
E-Business
Nigeria Targeted with 4,622 Cyber-attacks Per Week in December 2025

In December 2025, organisations globally faced sustained cyber pressure, as the average number of cyber-attacks per organisation per week reached 2 027, a 1% increase from the previous month and a 9% increase from December 2024.

This is according to December 2025 Global Cyber Attack Statistics by Check Point Research, the threat intelligence arm of Check Point Software Technologies.
According to the statistics, Latin America was the hardest hit, with companies experiencing an average of 3 065 cyber-attacks per week, a 26% year-over-year increase.
In contrast, Africa saw a decline in attacks, with Nigeria (4 622 attacks per week) and Angola (4 002 attacks per week) being the most targeted countries on the continent.
The report’s findings highlight the evolving cyber threat landscape, with ransomware and GenAI-driven data risks posing significant challenges to companies worldwide.
Ransomware attacks jumped 60% year over year, with 945 publicly reported incidents in December. Qilin was the most active ransomware operator, responsible for 18% of publicly disclosed attacks.
“Ransomware continues to scale through industrialised operations, while unmanaged GenAI usage is creating widespread data exposure at enterprise level,” said Omer Dembinsky, data research manager at Check Point Research.
The report noted the education sector was the most targeted industry globally, with 4 349 cyber attacks per week; followed by government (2 666 attacks per week); and associations and non-profits (2 509 attacks per week).
The widespread adoption of GenAI tools has introduced new cyber security risks, with one in 27 GenAI prompts posing a high risk of sensitive data leakage.
Experts warn that companies must prioritise prevention-first security, real-time AI threat intelligence and strong governance over AI tools to mitigate these risks.
Hendrik de Bruin, head of security consulting at Check Point Software, added: “Strengthening ransomware resilience, deploying AI-powered prevention and enforcing clear GenAI governance will be critical to reducing cyber risk in the year ahead.”
E-Business
Half of Global Companies Build SOCs to Enhance Cybersecurity, with a Focus on Human Expertise

Among the primary reasons for establishing a Security Operations Center (SOC) are strengthening cybersecurity posture, enabling faster detection and response and gaining a competitive edge.

Interestingly, despite the increasing demand for automated cybersecurity solutions, businesses rely on skilled security professionals to make key decisions, as human expertise remains essential for effective security management.
A Security Operations Center (SOC) is a dedicated organisational unit responsible for continuous monitoring and safeguarding of a company’s IT infrastructure. Its core mission is to proactively detect, analyse and respond to cybersecurity threats.
To identify the main drivers, strategic priorities, and potential challenges in SOC planning and implementation, Kaspersky has conducted a comprehensive global study involving senior IT security specialists, managers and directors from companies with 500 or more employees.
All participants operate without a SOC but have plans to establish one in the near future. The study spans 16 countries across APAC, META, LATAM, Europe, and Russia, providing valuable insights into the emerging trends and best practices in SOC development worldwide.
The findings of the research reveal that 50% of companies intend to establish SOCs to strengthen their cybersecurity posture, and 45% are motivated by the need to address increasingly sophisticated and dangerous threats.
Other drivers include budget optimisation, the necessity for faster detection and response, and the expansion of software, endpoints and user devices – factors that demand more comprehensive and layered security measures.
These are cited by 41% of organisations. Additionally, 40% seek better protection of confidential information, 39% aim to meet regulatory requirements and one-third (33%) expect SOC capabilities to provide a competitive edge. Larger enterprises tend to cite each of these reasons more often, reflecting the broader operational and regulatory pressures they experience.
Continuous monitoring becomes the leading SOC requirement
Among the key functions organisations plan to delegate, 24/7 security monitoring leads at 54%. This around-the-clock vigilance enables early detection of anomalies, prevents escalation and sustains cyber resilience in real-time. This demand highlights a strategic requirement for proactive risk management, as organisations aim to defend against persistent threats that can strike at any moment.
Companies intending to fully outsource SOC operations show a stronger interest in applying “lessons learned” methodologies, whereas those developing internal SOCs focus more on access management to maintain tighter control.
Human expertise drives SOC technology choices
While SOCs use advanced technology, the choices made by organisations show that human analysts are very important. Among the solutions that organisations plan to include in SOC are – Threat Intelligence Platforms (48%), Endpoint Detection and Response (42%) and Security Information and Event Management systems (40%) – sophisticated solutions that automate data collection and reduce operational load, however, they depend heavily on skilled security professionals who provide critical context, interpret complex findings and make final decisions when guiding appropriate responses.
Other solutions chosen include Extended Detection and Response (38%), Network Detection and Response (37%) and Managed Detection and Response (33%). Large enterprises tend to adopt more technologies (5.5 per SOC on average), while smaller ones integrate fewer (3.8).
“To successfully build a SOC, companies must prioritise not only the right mix of technology but also the careful planning of processes, clear goal-setting and effective resource distribution.
“Well-defined workflows and continuous improvement are essential to ensure that human analysts can focus on critical tasks, making the SOC a proactive and adaptable component of their cybersecurity strategy,” comments Roman Nazarov, Head of SOC Consulting at Kaspersky.
E-Business
Nigerian Terra Industries Secures $11.8m for Expansion

Terra Industries, a Nigerian defence technology startup, has raised $11.75 million to expand its development of defensive systems that protect critical facilities across Africa.

The fundraising round was led by Silicon Valley venture firm 8VC, which was founded by Palantir co-founder Joe Lonsdale.
Other investors in the round include Valour Equity Partners, Lux Capital, SV Angel, and Nova Global, as well as African-focused funds Tofino Capital, Kaleo Ventures, and DFS Lab.
Terra Industries, founded in Abuja by Nathan Nwachuku and Maxwell Maduka, provides multi-domain security solutions for both air and land. Its solutions are intended to detect and respond to threats including terrorism, sabotage, and armed attacks on infrastructure.
The company’s product portfolio includes surveillance drones, ground-based robotic systems, and fixed monitoring towers deployed around sensitive locations.
Co-founder and CEO Nathan Nwachuku said the company has now fully embraced its identity as a defence-focused startup, citing the growing urgency of security challenges across Africa.
He said safeguarding critical infrastructure from terrorist threats has become unavoidable.
Nwachuku argues that protecting Africa’s infrastructure requires a different approach, one that combines local manufacturing, end-to-end system control, and software capable of independently identifying and responding to threats over large areas.
The company aims to position itself as a defence prime, similar to the role played by firms such as Anduril Industries and Palantir in the United States.
Nwachuku also disclosed that the company had earlier raised $800,000 in pre-seed funding.
With the new funding, Terra plans to increase manufacturing capacity within Africa, establish additional defence production facilities, and expand its artificial intelligence and software teams.
While software offices are planned for San Francisco and London, the company said manufacturing operations will remain on the continent.
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