How do you rise at work or in your industry to become a General Manager, Executive Director or even a CEO? Let me share an experience I had during my days in Diamond Bank Lagos; our learners in Tekedia Mini-MBA should be familiar with this, as I have shared it in our career-planning focused sessions.

In my first week in Diamond Bank, I visited the websites of the leading banks in Nigeria. I created a table, adding core skills, certifications, and degrees those senior executives had, as listed on their bios. When I was done, I saw one commonality: most were chartered accountants with an MBA.

Right there, I knew that if Ndubuisi should also be listed there one day, getting an ICAN and MBA should not be a bad thing, even though I have started as an engineer, out of FUT Owerri. (Later, I registered for ICAN, did the Graduate and Intermediate phases before I abandoned it when I left for the United States for a graduate program in engineering. I completed an MBA in UNICAL). The table gave me a window of what I had to do for the least requirements for the ascension to the top, in case my plan to emigrate did not work out.

Then, as I worked in Diamond Bank, I developed another table. In that table, I was trying to make sense of the durability of careers in the banking sector. This was crucial as personally I like to be ahead of things. A first year lecture on logic and philosophy in FUTO shaped me: I see the world as numbers, and if you investigate numbers (yes, data), you can get revelations.

Over lunch, I asked the bank’s HR guys how many were hired in Year X, and how many remained in the bank, and in the industry (where data was available), after 3, 5, and 10 years. As I worked on the informal personal research, the data was like a  yramid and brutal: most bankers in Nigeria peak at 5 years, and may never earn as much as they earned in their first 5 years, on average, ever!

In other words, I noticed that more than 50% of those who joined as entry level executive trainees will not survive the first 5 years, and less than 20% will be there in ten years. And most of those people will never get a job which would pay them better than what they were making in the banking sector, before they left the sector.

I looked at that Pyramid-shaped outcome and was concerned; they were not many opportunities at the top. What was the reason? The economy did not have a lot of opportunities for mid-level managers because it was yet to be fully developed. Except oil & gas, the fledgling telecom sector was yet to stabilize, but the oil & gas rarely hired from outside at mid-management. 

In other words, there were limitations on transferring that 10-year banking experience to another industry, and being paid as well. Simply, the retail, agro, transportation, etc sectors were not going to compensate as much if one should be cut from the banking sector. 

That data and the fact that the work I was doing (IT) convinced me to return back to electrical engineering. I used to couple and assemble laptops and computers; it was something geeky. But over time, it required no skill as people who did not even enter primary school were doing it as well. So, the IT career vulnerability was huge; IT then largely coupling and networking systems as software was not a big component of it. A refuge: engineering which I concluded was at the upstream level.

Sure, I might not have modeled it well. But there are things you could learn if you are still at the early stages of your career in Nigeria from my experience.. If you have a ten year banking experience in the US, you could be paid as well, if not more, if you decide to join the retail, transportation, venture investing, etc sectors, because most of those sectors have been well developed. Consequently, you can move across industries delivering your skill with no diminished compensation because of limited options.

In conclusion, it comes down to this: if you make it, glory awaits at the top of the pyramid, but if you do not make the cut, you will remain underpaid, should you be forced out of the banking sector.

My First Day in America and Kindness of Diamond Bank Lagos

Artificial Intelligence (AI) is rapidly advancing, presenting new and significant challenges for global governance. As AI technologies become more integrated into various aspects of society, the need for comprehensive governance frameworks becomes increasingly critical. The rapid development of AI has outpaced the current regulatory mechanisms, necessitating the creation of new approaches to ensure responsible and ethical use of AI.

The challenges of AI governance are multifaceted, involving ethical considerations, data privacy, security, and the potential for societal disruption. To address these challenges, a collaborative effort is required among states, technology companies, and international organizations to develop strategies that protect individual rights while fostering innovation.

Recent discussions have highlighted the importance of establishing clear ethical frameworks and lines of cooperation between different stakeholders. Proposals such as EU-style regulations, open-source governance, and international research collaborations are being evaluated for their potential to create a responsible AI ecosystem. The establishment of centers and think tanks dedicated to AI governance, such as the Center for Artificial Intelligence by the Future of Privacy Forum, indicates a move towards a more structured approach to AI regulation.

Moreover, the concept of a ‘CERN for AI’ has been proposed, suggesting the creation of an international AI research organization that could address the global challenges posed by AI and facilitate the sharing of knowledge and resources. This idea aligns with the call for multi-stakeholderism in AI governance, emphasizing the need for common goals and cooperation across borders.

Here are some of the most pressing issues that regulators, companies, and AI practitioners face today:

Ethical Concern: AI systems can inadvertently perpetuate bias and discrimination if not carefully monitored and corrected. Ensuring that AI decisions do not reflect historical prejudices or societal inequalities is a significant challenge.

Misuse Prevention: Limiting the misuse of AI technologies, especially those that can be weaponized or used to infringe on human rights, is a critical governance issue. This includes the development of lethal autonomous weapons and surveillance systems that could be used for oppressive purposes.

Data Privacy: With AI systems processing vast amounts of personal data, safeguarding privacy becomes a paramount concern. Governance must address the potential for privacy rights violations and unauthorized data access.

Copyright Protection: AI’s ability to replicate and create content poses challenges for intellectual property rights and copyright laws. Governance frameworks need to adapt to protect creators’ rights in the digital age.

Transparency and Explainability: As AI algorithms become more complex, making them transparent and understandable to users and regulators is increasingly difficult. This is essential for accountability and trust in AI systems.

Security: Ensuring the security of AI systems against hacking and other cyber threats is a significant challenge. This includes protecting the data that AI systems use and the decisions they make from malicious interference.

Accountability: Establishing clear lines of accountability for AI’s decisions and actions is challenging, especially when multiple entities are involved in its development and deployment.

Regulation and Oversight: Creating regulations that keep pace with AI’s rapid development while not stifling innovation is a delicate balance for governance. This includes international cooperation to establish standards and best practices.

The global governance of AI also needs to resist colonialism by embedding the values of historically oppressed communities into AI systems, ensuring that AI development does not perpetuate existing inequalities. This approach is crucial for creating AI technologies that are inclusive and fair, reflecting the diverse needs and perspectives of global populations.

The global governance of AI is a complex and pressing issue that requires immediate attention. The development of responsible AI governance mechanisms is essential for managing the risks associated with AI while unlocking its potential benefits for society. As AI continues to evolve, it is imperative that governance strategies are adaptive and inclusive, ensuring that AI serves the common good and respects the dignity of all individuals. The ongoing discourse and research on AI governance provide a foundation for building a sustainable and just AI future.