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This recent season, I was caught in gridlocked traffic on the scorching streets of a southern French city. At a crossing, my companion in the passenger seat suggested a right turn toward a famous spot for fish soup. However, the digital guide on my phone instructed us to go forward. Fatigued and in a stifling car, I followed the app's advice. Moments later, we were stranded at a roadwork site.

A minor event, maybe. But one that encapsulates a defining dilemma of our era, where technology permeates almost every aspect of our lives: who gets our trust to a greater degree – other people and our personal instincts, or the algorithm?

The Enlightenment's Promise and A Contemporary Backslide

The renowned German philosopher Immanuel Kant famously described the Enlightenment as "humanity's emergence from its self-imposed immaturity." This immaturity, he wrote, "represents the inability to use one's personal reason without direction from an external source." For centuries, that guiding "other" for society was often the clergyman, the monarch, or the landowner – entities purporting to channel divine will. To comprehend natural events like changing seasons, people sought answers in theology. In shaping the fabric of society, from economics to love, religious doctrine acted as the primary guide.

“Sapere aude!” or “Dare to use your own understanding!”

Kant argued that humans had the ability to think rationally. They simply lacked the boldness to employ it. With upheavals in the 18th century, a fresh era emerged: reason would replace superstition, and the human mind, freed from authority, would become the engine of progress and a better world.

Now, two and a half centuries later, one might wonder if we are slipping back into a state of dependency. An app suggesting a direction is merely the start. AI risks becoming our new "other" – a silent overseer that influences our choices and behaviors. We risk relinquishing the historically earned courage to reason for ourselves – and now, not to gods or kings, but to computer programs.

The Swift Adoption and Hidden Risks of Algorithmic Reliance

ChatGPT was launched a mere three years ago, and yet a global survey found that an vast number of people had used AI in the preceding half-year. Whether deciding on ending a relationship or selecting a vote, individuals are looking to algorithms for counsel. Data suggests a large majority of user queries relate to personal life matters. Even more striking than our reliance on AI for judgment is what occurs when we allow it express for us. Writing is now among the top uses for generative AI, second only to everyday tasks. The late American author Joan Didion famously said, “I write purely to find out what I am thinking.” What transpires when we cease writing? Do we lose that path?

Alarmingly, some evidence suggests the answer may be affirmative. A study conducted by the Massachusetts Institute of Technology used electroencephalography to observe the mental engagement of essay writers who had could use AI, traditional search engines, or no aids. Those who could rely on AI showed the lowest cognitive engagement and had trouble accurately recalling their own work. Maybe most troubling was that over time, individuals in the AI group grew progressively lazier, copying large sections of text.

“Laziness and cowardice,” Kant wrote, “are the reasons why so great a proportion of men … stay in perpetual nonage.”

Certainly, AI's appeal lies in its efficiency. It saves time, minimizes work and – critically – offers a new method to abdicate responsibility. In his 1941 book, Escape from Freedom, the German psychoanalyst Erich Fromm argued that the appeal of authoritarianism could be partly explained by a human tendency to give up autonomy in for the sake of the comforting security of obedience. AI offers a digital method of relinquishing the burden of having to think and choose.

The Opacity Dilemma: Trust Without Understanding

AI's greatest allure is its ability to perform tasks outside our minds – sifting through vast datasets at unprecedented speed. Stuck in the car in Marseille, this was, after all, why I chose to believe the machine over my companion (a decision she interpreted as an affront). With access to real-time information, surely the algorithm had superior insight – or so I thought.

The fundamental problem is that AI operates as a black box. It generates knowledge, but not always deepening human understanding. We do not truly know how AI reaches its decisions – even its creators admit this. Nor can we verify its reasoning against clear, objective criteria. So when we follow AI's recommendation, we are not being led by logic. We are returning to the realm of belief. In dubio pro machina: when in doubt, side with the machine – that may become our future credo.

Harnessing Without Eroding: The Essential Challenge

AI can be a formidable ally for humanity in scientific pursuit. It can help inventing drugs, free us from "bullshit jobs", or manage taxes – duties that demand little thought and are unfulfilling. All to the good. But Kant and his peers did not champion reason over faith just so humans could assemble better furniture or have more leisure. Critical thinking was not merely about productivity – it was a practice of liberty and human emancipation.

Human thought is inherently messy and error-prone, but it forces us to debate, to doubt, to challenge concepts – and to acknowledge the boundaries of our own knowledge. It builds confidence, both individually and as a society. For Kant, the use of reason was never solely about information; it was about enabling people to become authors of their own destinies, and to oppose control. It was about creating a moral community based on the common foundation of reason and debate, rather than blind belief.

With all the undeniable benefits AI offers, the paramount challenge remains: how can we harness its promise of advanced capability without undermining human reasoning, the bedrock of the Enlightenment and of liberal democracy themselves? That may be one of the defining questions of our time. It is a question we must strive not to delegate to the machine.