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This recent season, I was caught in gridlocked traffic on the sweltering streets of Marseille. At an intersection, my companion in the front seat advised a right turn toward a famous spot for fish soup. However, the digital guide on my phone instructed us to continue straight. Fatigued and overheated, I followed the app's directive. Minutes later, we were stuck at a construction site.

A seemingly trivial event, maybe. But one that captures a defining question of our era, where technology touches nearly every facet of our lives: whom do we trust to a greater degree – fellow humans and our own intuition, or the machine?

A Call for Intellectual Maturity and Our Modern Relapse

The renowned German philosopher Immanuel Kant famously described the Enlightenment as "humanity's emergence from its self-inflicted nonage." This immaturity, he argued, "is the incapacity to use one's personal reason without guidance from another." For ages, that guiding "other" for society was often the clergyman, the king, or the landowner – figures purporting to channel divine will. To comprehend phenomena like changing seasons, people sought answers in theology. In shaping the fabric of society, from economics to matters of the heart, faith acted as the main compass.

“Sapere aude!” or “Have courage to use your reason!”

Kant argued that humans always possessed the capacity for reason. They just didn't have the confidence to use it. With revolutions in the 18th century, a fresh era emerged: reason would replace blind faith, and the human mind, freed from authority, would become the driver of advancement and a more ethical world.

Now, 250 years later, one might wonder if we are quietly regressing into a form of dependency. An app suggesting a driving route is merely the start. AI risks becoming our new "other" – a silent overseer that steers our decisions and behaviors. We are in danger of relinquishing the historically earned autonomy to think independently – and this time, not to deities or rulers, but to lines of code.

The Rapid Rise and Subtle Dangers of Algorithmic Reliance

ChatGPT debuted a mere three years ago, and yet a recent study found that an vast number of people had engaged with artificial intelligence in the preceding half-year. Whether deciding on a breakup or choosing a candidate, individuals are looking to algorithms for counsel. Research suggests a large majority of user prompts relate to non-work topics. Even more intriguing than our reliance on AI for judgment is what occurs when we let it speak for us. Writing is now one of the most common uses for generative AI, second only to practical requests. The celebrated American author Joan Didion famously said, “I write purely to discover what I am thinking.” What transpires when we cease writing? Do we cease discovering?

Alarmingly, some evidence suggests the outcome may be affirmative. A study conducted by the Massachusetts Institute of Technology used brain monitoring to observe the mental engagement of participants who had access to AI, Google, or no aids. Those who could rely on AI displayed the lowest cognitive engagement and had difficulty accurately recalling their own work. Perhaps most troubling was that after a few months, participants in the AI group became progressively lazier, copying entire blocks of text.

“Inertia and fear,” Kant wrote, “are the reasons why so great a proportion of men … stay in lifelong immaturity.”

Of course, AI's attraction stems from its convenience. It is fast, reduces effort and – critically – offers a novel way to offload accountability. In his 1941 book, Escape from Freedom, the German psychoanalyst Erich Fromm proposed that the rise of fascism could be partly explained by a preference to give up personal freedom in for the sake of the reassuring certainty of obedience. AI offers a modern avenue for surrendering the weight of having to decide for oneself.

The Opacity Dilemma: Faith Over Reason

AI's primary draw is its capacity to accomplish things beyond our minds – sifting through vast datasets at unprecedented speed. Sitting in the car in Marseille, this was, after all, why I opted to believe the app over my companion (a choice she took as an insult). With access to all the data, surely the algorithm had superior insight – or so I thought.

The core issue is that AI operates as a opaque system. It generates knowledge, but not always deepening human comprehension. We do not truly know how AI reaches its decisions – even its programmers acknowledge the opacity. Nor can we verify its reasoning against clear, objective criteria. So when we heed AI's recommendation, we are not being led by logic. We are back in the realm of faith. In dubio pro machina: when in doubt, trust the machine – that could be our 21st-century credo.

Using Without Losing: The Essential Challenge

AI can be a formidable ally for mankind in scientific pursuit. It can help medical research, liberate us from "bullshit jobs", or manage taxes – work that are repetitive and are unfulfilling. This is beneficial. But Kant and his peers did not advocate for reason over faith just so humans could assemble better furniture or have more leisure. Critical thinking was not just about efficiency – it was a practice of liberty and human emancipation.

Human thought is often chaotic and fallible, but it forces us to argue, to doubt, to challenge concepts – and to acknowledge the boundaries of our own understanding. It fosters self-reliance, both individually and collectively. For Kant, the exercise of reason was never only about information; it was about enabling people to become agents of their own lives, and to oppose control. It was about creating a moral community based on the common foundation of rational discourse, rather than unquestioning acceptance.

With all the undeniable benefits AI offers, the key question is this: how can we harness its promise of superhuman intelligence without undermining human rationality, the bedrock of the Enlightenment and of free societies itself? That is likely one of the central dilemmas of our time. It is a question we would do well not to delegate to the algorithm.