I have received a lot of questions after my recent articles on jobs, future opportunities and redesigns in our economies: “I want my child to be a successful coder, what do you suggest we do now in this secondary education phase?”

First, I am not a career counselor and have zero license in that space. Nonetheless, from my experiences and others I know, a child who is well groomed in physics, mathematics and chemistry at the foundational phases has a better chance of thriving, than one, who is forced to start coding and learning computer languages, without those basics.

The best developers and creators in computer science and engineering are great math and physics persons, leveraging computational thinking to tackle complex problems effectively. The challenges you solve are first of the natural philosophy type, and which must be solved at the mathematics and physics level, before they are translated into codes. The coding is not really the zenith: mathematics and physics define everything.

As a PhD student in Johns Hopkins, my main project  for a course titled Computer Integrated Surgery was to build a machine that can control a needle via an endoscope/laryngoscope to get through the larynx to enable a doctor perform minimally invasive surgery of the throat, with da Vinci medical robot connected. It was a really tough engineering problem but looking at all, one had to solve complex mathematical equations which will ensure you can track the needle, the equipment, human tissues (you use markers), etc. We were grouped in pairs!

I had booked a flight to Scotland and needed to travel. I did the equations and sent the written math to my colleague, and left for Scotland. He implemented it in Python (my Python coding was basic). But he did one more thing: he wrote a complaint to the professor that I allowed him to do the work.

When I returned, the professor summoned two of us, and asked what happened. I explained that I did the math but with limited  experience using Python (just largely coming from Lagos), I asked him to help since he was proficient with it. Right there, Prof Taylor said “Nd, you did this”? I responded and the guy confirmed. The Prof gave me a fellowship, and gave me a lab space, and I joined his computer science group, expanding my fellowships. He explained – the focus of the PhD is solving the math, not writing codes. With that, I had two labs – one in electrical and electronics engineering, and another in the computer science department. Hope that explains what really matters!

Of course, you need to code. But no useful coding happens without algorithms and those happen because of a good understanding of mathematics and logic. Code but be loaded with Math also to get to the sweetest part of coding (the upstream), instead of the downstream which offers nothing much.

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Comment 1: If they are mutually exclusive, then by all means a child needs to master math and physics before learning to code.
The great thing is that they can be learned together and mastered together. Coding at age 8 should actually start with a course on Computational Thinking which in itself is a serious skill for problem solving. In well designed CS curriculums for high school, students write programs to solve mathematical and physical problems, thereby integrating these three worlds in beautiful harmony. They should all be compulsory for the broad training of the child’s mind.

My Response: “Coding at age 8 should actually start with a course on Computational Thinking” – that would be super awesome if we have that. Possibly, it is integrated within Quantitative Aptitude which is possibly woven within General Mathematics in primary/secondary school. In entrance exams to move  from primary to secondary school, they used to have two core components: verbal and quantitative aptitudes. That QA is actually logic which can go for this Computational Thinking. The problem now is that most of those things are making way for html syntax.

Comment 2: As someone who did physics, maths and logic at various points in my formal educational, and a programmer, I will tell you logic is fundamental and more important to coding than mathematics and/or physics. Way more important.

My Response: Logic of numbers  is a branch of mathematics. In your primary school entrance exam for secondary school, you took two components: verbal and quantitative aptitudes. And everything is philosophy, the very reason why PhD is appended after those doctoral degrees. PhD in Economics means that you have mastered the philosophy of economics. Philosophy is logic. Mathematics translates it. So, if you studied the logic of numbers, you actually did mathematics.

Comment 3: Spot on Ndubuisi Ekekwe . This right here is what the big techs always look out for in candidates. The ability to grab concepts and apply them to solve problems. Explains why you will always be put to data structure & algorithms test in any serious engineering role. I once attended a white board live coding interview where a final yr electrical engr student finished top. In the room were people with years of experience, those who couldn’t make it were asked to go home and the rest proceeded with the process.

In a new report, Goldman Sachs posits that many jobs could be lost as a result of AI and broad automation: “roughly two-thirds of current jobs are exposed to some degree of AI automation, and that generative AI could substitute up to one-fourth of current work. Extrapolating our estimates globally suggests that generative AI could expose the equivalent of 300mn full-time jobs to automation”.

When things are automated, on average, jobs are lost at scale, even though a smaller number of jobs are created within a close category of those jobs. (In the broad industry, more jobs could actually be created over time.)

You may dismiss it. But note this: that redesign has already started.  For years, I have not seen the type of job losses we’re experiencing right now in the technology industry in the United States. From Facebook* to Electronic Arts, announcements of job cuts have become a constant. 

Unlike during the great recession when losses came big and then stopped, this new redesign is totally different: companies are constantly cutting even when they’re making more money. In short, some startups raise big money, then they announce job cuts. How is that possible? They possibly raised money to automate many things.

But it is not all bad; people with great modern skills will thrive. Prompt engineers, new species of engineers who can “talk” and “whisper” to AI chatbots, making them better, are going to $335,000 per year on salaries. Indeed, we will see new dimensions of opportunities even as the old ones are being displaced.

The recent emergence of generative artificial intelligence (AI) raises whether we are on the brink of a rapid acceleration in task automation that will drive labor cost savings and raise productivity. Despite significant uncertainty around the potential of generative AI, its ability to generate content that is indistinguishable from human-created output and to break down communication barriers between humans and machines reflects a major advancement with potentially large macroeconomic effects.

If generative AI delivers on its promised capabilities, the labor market could face significant disruption. Using data on occupational tasks in both the US and Europe, we find that roughly two-thirds of current jobs are exposed to some degree of AI automation, and that generative AI could substitute up to one-fourth of current work. Extrapolating our estimates globally suggests that generative AI could expose the equivalent of 300mn full-time jobs to automation

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Comment 1: While technology can certainly impact the job market, it is not the sole factor driving workforce restructuring. It is important to consider various factors and opportunities for upskilling and reskilling in order to navigate the changing nature of work.

The rise of AI is disruptive in a different way and the market may not recover from this disruption. However, new roles such as data analysts, machine learning engineers, and AI ethicists will emerge or continue to be in vogue.

My Response: Absolutely, new vistas will emerge. The world is a dynamic system.

Comment 1A: Not so. With Microsoft’s Copilot you can highlight entire spreadsheets and/or databases and simply “ask” it to do whatever you want and it’ll do it. Need to run a regression? Just ask it in plain language and boom there it is….no need for a data analyst or analytics “expert” – the system is the expert. Same goes for software engineers – one intelligent individual trained on the language of AI could replace an entire team of software engineers. The reality of AI capabilities are simply amazing, and we are at its infancy. I like your optimism but it’s not reality.

My Response: why will people go to school or learn anything when you can command machines to do anything. An interesting age awaits.

Comment 2: Prof. thanks for the insights you always provide. Yes AI is causing and will cause significant disruptions and job losses. But it will be more of a reclassification of income classes, (where people in lower upper class maybe pushed to a  lower class, and vice versa ) as against permanent job losses. One of the fundamental human rights of human beings is the right to earn a living. AI cannot and will not deny humanity that right essentially because the future of work is and will continue to be driven by people and not technology or AI. Notwithstanding, the need to upskill cannot be overemphasized.
Thanks Prof.

My Response: sure. There will be work. But note this – if you track the revenue of Microsoft and Zenith Bank, you will notice one thing: the revenue growth is faster than staff growth. Zenith Bank got close to N1 trillion revenue last year even though its staff strength has remained flat. There will always be work. The issue is this: will Ndubuisi and Obichukwu be ready for those new jobs? AI will create new types of jobs but not everyone will qualify.

More so, it is easier for a rich investor to compound more wealth than a worker since AI can make it easier to create products and services. Bill Gates is donating billions but he is not meeting up with the rate he is creating more wealth. That pattern cuts across domains. While new people can join, those already there may not drop. Tech accelerates inequalities because it can scale wealth faster and only those with means are usually at the production phase.