🔗 Share this article

This past summer, I was caught in gridlocked traffic on the sweltering streets of Marseille. At an intersection, my companion in the passenger seat advised a right turn toward a renowned spot for bouillabaisse. Yet, the digital guide on my phone instructed us to continue straight. Weary and in a stifling car, I followed the app's advice. Moments later, we were stranded at a construction site.

A seemingly trivial incident, perhaps. But one that encapsulates a defining question of our era, where digital tools touches nearly every facet of our lives: whom do we trust more – fellow humans and our personal instincts, or the machine?

The Enlightenment's Promise and Our Modern Relapse

The influential German philosopher Immanuel Kant once defined the Enlightenment as "humanity's emergence from its self-inflicted immaturity." This immaturity, he wrote, "represents the inability to use one's personal reason without direction from another." For ages, that directing force for human thought was frequently the clergyman, the monarch, or the feudal lord – entities purporting to speak for divine will. To comprehend phenomena like volcanic eruptions, people sought answers in religion. In organizing the fabric of society, from economics to love, religious doctrine served as the primary guide.

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

Kant maintained that humans had the capacity for reason. They simply lacked the boldness to employ it. With revolutions in the 18th century, a fresh era arrived: logic would supplant superstition, and the human mind, liberated from dogma, would become the driver of progress and a better world.

Now, two and a half centuries later, one might wonder if we are quietly regressing into a state of intellectual immaturity. An app dictating a direction is just one example. AI threatens to become our new "other" – a silent guide that influences our decisions and actions. We risk ceding the hard-won autonomy to reason for ourselves – and this time, not to deities or rulers, but to lines of code.

The Swift Adoption and Subtle Dangers of Algorithmic Reliance

ChatGPT debuted only in 2022, and yet a recent study indicated that an vast number of people had engaged with artificial intelligence in the previous six months. Whether contemplating ending a relationship or choosing a candidate, individuals are increasingly turning to algorithms for guidance. Data suggests a significant portion of user queries concern personal life matters. Even more striking than our reliance on AI for judgment is what occurs when we allow it speak for us. Writing is now one of the top uses for tools like ChatGPT, just behind practical requests. The celebrated American author Joan Didion once remarked, “I write entirely to discover what I am thinking.” What transpires when we stop composing? Do we cease discovering?

Alarmingly, emerging research suggests the answer may be affirmative. A study from the Massachusetts Institute of Technology used electroencephalography to track the cognitive activity of participants who had access to AI, Google, or nothing. Those who could use AI showed the least brain activity and had difficulty quoting their own work. Perhaps most concerning was that over time, individuals in the AI group became progressively lazier, pasting large sections of text.

“Laziness and cowardice,” Kant wrote, “are the reasons why so many of men … remain in perpetual nonage.”

Of course, AI's attraction lies in its efficiency. It is fast, reduces effort and – critically – offers a new method to abdicate accountability. In his 1941 book, Escape from Freedom, the German psychoanalyst Erich Fromm proposed that the appeal of authoritarianism could be partly explained by a human tendency to surrender autonomy in for the sake of the reassuring certainty of subordination. AI presents a modern avenue for surrendering the weight of having to think and choose.

The Black Box Problem: Trust Without Understanding

AI's greatest allure is its capacity to perform tasks beyond our minds – sifting through vast datasets at lightning pace. Stuck in the car in Marseille, this was, ultimately, why I chose to believe the machine over my companion (a choice she took as an affront). With knowledge of all the data, certainly the app must know best – or so I thought.

The core issue is that AI operates as a black box. It generates answers, but without necessarily fostering human comprehension. We do not truly know the process behind its conclusions – even its creators acknowledge the opacity. Nor can we check its reasoning against clear, objective criteria. So when we heed AI's advice, we are not being guided by reason. We are returning to the domain of belief. In dubio pro machina: when in doubt, side with the machine – that may become our future credo.

Using Without Losing: The Essential Challenge

AI can be a powerful tool for mankind in rational inquiry. It can aid in inventing drugs, liberate us from tedious tasks, or manage administrative chores – duties that demand little thought and are unfulfilling. All to the good. But Kant and his peers did not champion enlightenment just so humans could assemble better furniture or have more leisure. Critical thinking was not just about productivity – it was a practice of freedom and human self-determination.

Human thought is inherently messy and fallible, but it compels us to argue, to doubt, to test ideas – and to recognize the limits of our own understanding. It fosters confidence, both individually and collectively. For Kant, the use of reason was never solely about information; it was about enabling people to become authors of their own lives, and to oppose control. It was about creating a ethical society based on the common foundation of reason and debate, rather than unquestioning acceptance.

With all the advantages AI brings, the paramount challenge is this: how can we harness its potential of advanced capability without eroding human reasoning, the cornerstone of the Enlightenment and of free societies itself? That may be one of the central dilemmas of our century. It is a question we must strive not to outsource to the algorithm.