There is that strange, yet sweet, feeling that kicks in when you see the future that you have predicted playing out before your very eyes. “I told you so.” This is not the feeling I am talking about. This is something much more complicated: a combination of validation, worry, and the understanding that, collectively, we are not moving at the pace that needs to be accomplished.
For the last two decades, I have stood on stages, sat in boardrooms, and written prolifically, trying to raise the warning flag about the technological direction our society is heading towards. I have had moments where I felt like the canary in the coal mine, singing about invisible gas while others were mining for a new spark of immediate gain.
Reflecting on my previous writings, from the period just after the dot.com bubble burst in 2002 to the world just before the pandemic in 2019, it is obvious what the trajectory was. These were not crystal ball readings; they are simply the natural extensions of human nature, technological advancement, and past tendencies. It is no revelation to me today, in a world where headlines are filled with the drama of Generative AI, Market Turbulence, and Governments in a Tizzy, to see that my prognostications are not just “coming real.”
We are living in a time of strategic pivot in human history. The playbook that guides engagement in career success, economic security, and international security has dramatically changed. And unless we take a peek at our scorecards in the last few years to understand what contributed to this paradigm shift, we are doomed to be crushed in the next wave.
Below is a reflection on five key predictions that I have made, and the implications of these being fulfilled in terms of where we progress next.
The Death of Syntax and the Rise of Logic (Prediction: 2019)
Exactly a year after the peak of the movement of “everyone must learn to code,” I wrote, in 2019, the following: “Programming will die; only critical thinking will be left.”
“At the time, this was seen as blasphemy in tech circles,” he says. “Coding bootcamps were churning out junior programmers by the thousands with a ticket to the middle class. Knowing Python and/or JavaScript code was seen as the key to future-proofing.”
However, my point was based on a very basic observation: code writing is fundamentally a matter of translation. You’re translating human thought into computer code. We can learn from history here: any process involving translation will inevitably be mechanized.
Four years ago, however, came the emergence of ChatGPT and GitHub Copilot, and this prediction became harsh reality overnight. Currently, junior developers with assistance from AI can produce more than senior developers in 2019. Remembering syntax or functions of some library is no longer an advantage.
What is the advantage?
“And the other half is going to be critical thinking. Because the machine can generate the equation, but the machine can’t determine that this is the equation that the company needs.”
“Because the machine can generate the equation. But the machine can’t understand the implications of the data that the machine is working with. A machine can’t understand the politics of getting something passed within the company.”
“Language” is English (or any language) now, and “compiler” is critical thinking. Can’t explain your problem? Your problem can’t be solved by the computer system either. We’re ending the age of builders and entering the age of architects. The grunt work involved in the production of the digital object is disappearing and only the higher-level thinking remains. If your talents lie with the syntax language, then you’re redundant. If your talents lie with problem solving, then you possess the greatest tool ever created.
The Anatomy of the Hype Cycle (Prediction: 2020)
In the year 2020, during the flooded era of inexpensive capital and the resultant price appreciation that defied gravity, “Don’t trust bubbles, they will burst.”
It’s almost a redundancy to analyze it, now that we are on the other side of a post-pandemic market correction, a crypto winter, as well as mass layoffs at big tech. But the underlying dynamic is still important to remember, as it has to do with human nature, which does not change.
We love a good story. In 2020, the story was that the pace of digitization was accelerating to the extent that valuation no longer mattered; it was all about growth. This could range from the NFT of bored apes selling for multiple million-dollar backups to the SaaS companies with no clear route to profit commanding 100x multiple prices.
Let me underscore that this is not intended as a condemnation of those with optimistic attitudes about investing in the market. Optimists build wealth. Hypes destroy it. When the easy money that had been around soured with increasing interest rates, correct forecasts reasserted themselves with harsh brutality.
My worry for the day is that it seems like we’re already creating a brand-new bubble for AI and AI applications. Of course, it’s incredible tech, and some of the things being bandied about in 2020 were certainly vaporware, but the economic vibes are very, very familiar. People are adding “AI” to their pitch decks to boost the price of their companies without a viable business model. There’s a rush to distinguish the truly useful tech advances from the economic euphoria, but the problem is always that the bubble pops, and you need to be working towards something tangible while the party ends and the air rushes out of the room
The Need for Long-Range Vision (Forecast: 2002)
It all began way back, when the dot-com bust had left me reeling, back in 2002. It then dawned on me that people in general had far-too-short cycles. The counsel I had was easy to give, but hard to follow: “Think ahead of time.”
In a world that is seemingly consumed with today’s bottom line and today’s news headlines, planning five, ten, or twenty years out is a luxury. It is a requirement for survival.
“The seeds of the AI revolution that’s occurring today were planted decades ago in academic papers that nobody read. “The seeds of the AI revolution that’s occurring today were planted decades ago in academic papers that nobody read.” This article is saying that the roots or beginnings of the current AI evolution happened in the past through research that was never considered or looked at.
Thinking ahead of time doesn’t require a crystal ball. It requires an understanding of second and third-order effects. It requires that we ask ourselves, “If this technology works, what will break?”
In the present times, the pace at which change is happening has become so rapid that the meaning of “long-term” has shrunk. What used to take twenty years in the last century now happens in five years. If you are taking actions only for yesterday’s event, then you are certainly lagging behind. We must develop an attitude of strategic discernment where we look at the horizon not for the “next wave” but for the “tide” that carries the wave.
Foundations Over Frameworks (Prediction: 2018
Seeing the trend in 2018, I realized that people were obsessed with the “tool of the time.” The advice I gave in 2018 remains, I think, the most relevant even today: “Understand basics of tech, not learn only tools.”
I’ve met numerous young professionals who were highly knowledgeable about a particular framework in JavaScript but had no knowledge about how the internet actually works, concepts such as DNS, HTTP, or data structures. They’re carpenters who are familiar with a particular brand and type of power drill but know nothing about physics and material science.
“Tools are transitory. They keep changing every few years. What’s in now is React and PyTorch. Tomorrow it will be something else. Your career will expire if your identity is linked to a tool.”
But the fundamentals themselves, logic, algorithms, design of systems, principles of network security, human psychology are things that don’t ever change. It is easy to pick up any other tool that comes after because you grasp the principles that the tool is based on. An AI world is one that is going to change endlessly every day because the tools that you are going to be working with will change daily.
The Regulatory Vacuum and the Human Cost (Prediction: 2019)
Finally, my prediction that keeps me up at night. In 2019, from the gathering clouds of unrestricted data gathering, algorithmic discrimination, and the emerging might of decentralized finance, I encouraged our leaders to “Make policies of AI, Blockchain & Cybersecurity ASAP, especially for Manpower.”
“Manpower” particularly, since the hardest hit by the technology disruption will not be old industries, but people who are not prepared. The problem is, we are now witnessing what happens if we fail to adapt and move forward. We are witnessing the dangers of deep fakes disrupting democratic elections. We are witnessing enormous breaches of our personal data, revealing the identities of millions of people. We are witnessing AI systems making employment and loan decisions with inherent biases that are hard to audit. And we are witnessing a workforce fearful that their employment is about to be automated out of existence with very little in place to catch them. Finally, governments are waking up, scrambling to introduce things like the EU AI Act. Policy will always trail technology by a number of years.
The differential between the pace of innovation and the pace of regulation is where the risk originates. We require policies that are proactive as well as reactive. We have to articulate what human rights are in the new world of technology. How do you retrain people in mid-stream professionals whose sectors shrink? What happens to the property rights of the output of generative AI? How do you prevent blockchain solutions only working on the dark web? We have waited for too long. We are attempting to build the airplane and fly it at the same time while navigating through a thunderstorm. The Way Ahead Viewing these forecasts come to pass is rather sobering. It not only proves that we are operating in new territory, but it proves that the tides can be traced if we are paying attention.
However, the crucial linking thread within these foresight analyses is the focus on the centralized role of the human factor. Whereas “how” is increasingly the function of the machine, the importance of “why” cannot be overstated. The future will belong to critical thinkers, skeptics of the hype, long-term planners, experts at fundamentals, and to men and women with the courage to insist on guiding principles for our powerful new technologies. The time of passive observation will soon be over. We must be about the future we want to create, or we will be forced to endure it.
The author is the founder and CEO of Pakistan Blockchain Institute and AnZ Technologies, leading initiatives in blockchain education and technological innovation.
