Han Dieperink: The blind spot of the human mind
Han Dieperink: The blind spot of the human mind
This column was originally written in Dutch. This is an English translation.
By Han Dieperink, written in a personal capacity
Oracle's spectacular 36% share price explosion in a single day was more than just a stock market rally. It was a wake-up call for those who still underestimate the impact of artificial intelligence. While the order book exploded from $138 billion to $455 billion in a single quarter, analysts were perplexed. How could they have missed this?
The answer lies in a fundamental characteristic of our minds: we understand linear growth, but fail to appreciate exponential developments. Our brains have evolved in a world of gradual change. If you save one euro every day, you will have thirty euros after a month. We understand that intuitively. But when something doubles every seven months, such as the cognitive capabilities of AI systems, our mental models become completely disrupted. We project linearly, while reality accelerates exponentially, causing us to be surprised time and again by developments that seem “sudden” but were actually long in the making.
This cognitive limitation explains why we still underestimate the AI revolution. While we discuss gradual automation, tasks that currently take days will be reduced to seconds within a few years. Microsoft's medical AI already achieves 85% diagnostic accuracy – four times higher than experienced teams of doctors. Amazon's warehouse robots grew from 100,000 to over a million, a tenfold increase that far exceeds the growth of human workers.
The labour market is already experiencing this exponential force in full force, but the signs are often misinterpreted. In AI-intensive sectors, the influx of young workers has fallen by nearly 20% since 2019. This is too often dismissed as temporary market dynamics, when in fact it signals a structural shift in which entry-level positions in customer service and software development are systematically disappearing. We look at individual cases of automation, but in doing so we miss the broader pattern of exponential displacement.
Larry Ellison's metaphor of the AI tsunami is particularly apt. Like a real tsunami, the AI revolution is created by invisible shifts that suddenly release exponential energy. At first, it seems like nothing much is happening – a few new tools here, some automation there – but once the wave rises, it is unstoppable. Oracle's order book explosion is just one wave in a much larger movement that will sweep across markets, sectors and societies.
The problem is that we are trying to understand these exponential dynamics from linear thinking patterns. Investors look at quarterly and annual results, while AI capabilities double every seven months. Policymakers make plans for gradual changes over decades, while entire professions can transform within years. Employees prepare for incremental adjustments, while their field of work may be fundamentally rewritten.
This underestimation has far-reaching consequences. Companies that still see AI as a nice-to-have technology will soon discover that it has become a matter of survival. The question is no longer what a company does, but how intelligently it does it and how quickly it adapts to the exponential curve of AI development. Those who cling to linear strategies in an exponential world run the risk of becoming irrelevant.
The financial markets are slowly beginning to understand this. Oracle's share price explosion may mark a paradigm shift from sector-focused to capacity-focused investing. It is not the sector that determines value, but the extent to which AI is effectively integrated into operational processes. From healthcare to legal analysis, from manufacturing to financial services: the cards are being reshuffled everywhere.
The real value creation of AI lies not in the tools themselves, but in their application. Companies that succeed in deploying artificial intelligence strategically will benefit disproportionately from the accelerating curve. But to reap that benefit, we must first adjust our mental models. We must learn to think in exponential terms, even if it goes against our intuition.
The AI revolution is no longer a future scenario; it is a reality that is unfolding today. Those who still think linearly about exponential changes will be surprised time and again by developments that seem sudden but have been in the making for a long time.