Nnanna's Blog

“The ATM is the only useful innovation in banking in the last 20 years, it is omnipresent and under-appreciated and allows customers to retrieve cash from street-side dispensers at any time during the day or night.” – Former Chairman of the Fed, Paul Volcker during the height of the 2008 financial crisis (The ATM was invented in 1967)

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Artificial Intelligence and multiple forms of Machine Learning have existed in the mainstream military, government, and academic spaces since the early 1970s, but they have witnessed a form of democratisation since 2006.

With Open AI and other generative AI solutions gaining popularity in 2021, a different kind of marketing and doomerism has flooded various online spaces, especially along the lines of AI making us freer and leading to less work, or worse, loss of jobs. 

Just like ATMs revolutionised banking, AI will automate repetitive elements within jobs. While ATMs reduced the number of bank tellers needed at a branch, they allowed banks to expand their branch networks, and reach, effectively leading to an increased demand for tellers and creating new opportunities for expansion, new jobs, and cheaper branches.

Similarly, AI-powered tools will free us from tedious aspects of our professions, allowing us to focus on what machines can’t replicate: creativity, critical thinking, physical labour, and efficient problem-solving.

The introduction of VisiCalc and later Excel also eliminated the traditional role of accountants but birthed the modern finance department. AI assistants will handle financial data analysis, freeing today’s accountants to focus more on strategic planning. 

For most fields, AI will have similar effects, but in varying degrees. Manufacturing and data processing might see significant automation, while sectors like healthcare and education will likely require a more human touch. Doctors will still diagnose patients, but AI could analyse medical data to suggest treatment options. Teachers won’t be replaced by robots, but AI tutors could personalize learning experiences. Basically, tasks that used to take a whole day can now be done in minutes (or seconds), across various industries.

This current wave seems to affect white-collar workers, more than blue-collar workers, reflecting a shift in the tide of technology automation, and creating an automation paradox where for every simplification introduced by automation and AI, new complexities and demands are imposed on the human worker, underscoring the need for a need for a balanced approach, where AI augments human capabilities rather than entirely replacing them.

As we navigate this AI-driven transformation, it is crucial to embrace a mindset of continuous learning and adaptation. While some jobs may be displaced, new opportunities will emerge, requiring a workforce equipped with the necessary skills to thrive in the AI-powered future. Debugging complex AI systems and ensuring they function correctly will require human expertise.

AI is yet to get its iPhone or even ATM moment, the least we can do now is key in and use it to advance our respective workflows and industries in the interim.

More brilliant minds than mine have written multiple essays on how AI will transform many industries. But the beautiful thing is that nobody knows exactly how. Everyone is making projections based on their interpretation of trends and what they’ve seen in the past.

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3 years ago, everyone talked about how crypto and Blockchain were the future. While the possibilities of a blockchain enabled future exist, I think that the barrier to entry is still too high for most people. There’s still too much to learn and understand, given the prominent technicalities here. 

The internet didn’t become mainstream until the barriers were reduced. Personal computing didn’t become mainstream until the barriers were removed. You didn’t have to go through a complicated process of creating your computer or setting up a network system and the more the underlying technology is improved and abstracted from the user, the more mainstream it has become. 

I think AI will be most valuable in the previously impossible or super difficult research. Making new links and connections. But those links and connections may be tenuous, wrong, and not make sense at times.

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Enter Devin: 

So maybe the number of developers per company will decline, but more companies will be created, leading to more jobs in general. I guess time will tell if this thesis is right.

Historically, every time we made it easier to write code, we increased the need for software engineers. On an aggregate level, the tech industry should be fine in the longer term. All that AI-generated code will break in very interesting ways that need a human to debug.

Until now, making software was expensive, complex, and difficult. Now, with AI, tons of software will be made. More low-quality software will reach production than ever before. There could be more demand for software engineers, not less.

When telephones became popular, phone connectors and operators as a career choice dwindled, but phone repairers, installers, OEMs, and even airtime resellers came up within the same industry, solving relatively the same problem.

Amazon hasn’t killed bookstores, but we have found a way to expand the entire publishing industry by virtue of its existence.

It’s hard to say what the real, actual long-term impact will be. But in the short term, we’re already seeing lots of knee-jerk AI replacements being promoted ahead of their time. 

Some industries are better suited to being disrupted by AI than others. A few years ago, the word on the street, was that “physical labour” was more likely to be impacted (Think self-driving cars, robot-waiters, etc.). But now, the tide has turned, and all the projections are that knowledge workers are more likely to be impacted.

Will AI significantly change everything everywhere all at once? I think not. But will AI be part of everything everywhere, eventually? Yes, most likely.

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Humane, Frame, Rabbit R1, and the Meta Ray Ban glasses have made consumer hardware interesting again, despite their early flops and slow starts. However, these are still niche and expensive products.

The OpenAI and Google I/O demos last week were beautiful to behold, offering a glimpse into the future. But at the end of the day, that future seems expensive.

Sam Altman says he needs $7 trillion, Emad Mostaque of Stability had to resign after raising $126 million and calling AI a $1 trillion bubble, and Mustafa Suleyman (probably AI’s biggest celebrity since Ilya Sutskever, Andrew Ng, Timnit Gebru, and Jeff Dean) has, since selling DeepMind for $400 million, bounced from his Inflection AI that raised $1.3 billion to a cushy job at Microsoft.

If the humans responsible for ushering in this future, despite the billions spent, are unable to do so (in the case of Google and Microsoft) or believe more funding is required, it raises doubts about when we can achieve the democratisation of AI that could disrupt jobs.

As an occasional betting man, my bet is that this AI wave will go the way of the cloud wars between 2008 and 2015: A few companies will compete on price in a race to the bottom, and at the end of the day, we’ll be stuck with 3–5 companies charging a premium for their service.

AI access will improve your productivity and advance your skills and output, but it will not kill your job (yet). However, it could possibly kill the company you work for or the product you’re currently working on.