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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 suggested a right turn toward a famous spot for bouillabaisse. However, the navigation app on my phone instructed us to go forward. Weary and in a stifling car, I heeded the algorithm's advice. Minutes later, we were stuck at a construction site.

A minor event, maybe. But one that encapsulates a defining question of our era, where technology permeates nearly every facet of our lives: whom do we trust to a greater degree – fellow humans and our own intuition, 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 nonage." This immaturity, he argued, "is the inability to use one's personal reason without guidance from another." For centuries, that guiding "other" for society was frequently the priest, the king, or the feudal lord – figures claiming to channel divine will. To comprehend phenomena like volcanic eruptions, people sought answers in religion. In shaping the social world, from commerce to matters of the heart, faith 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 just didn't have the confidence to use it. With revolutions in the 18th century, a new dawn arrived: reason would supplant superstition, and the intellect, liberated from dogma, would become the engine of advancement and a better world.

Today, 250 years later, one might wonder if we are slipping back into a form of dependency. An app suggesting a direction is merely the start. Artificial intelligence risks becoming our contemporary authority – a unseen overseer that steers our decisions and actions. We risk relinquishing the hard-won autonomy to reason for ourselves – and this time, not to gods or kings, but to computer programs.

The Rapid Rise and Subtle Dangers of Algorithmic Reliance

ChatGPT debuted a mere three years ago, and already a global survey indicated that an overwhelming majority of respondents had used AI in the preceding half-year. Whether contemplating a breakup or choosing a candidate, individuals are increasingly turning to algorithms for guidance. Data suggests a large majority of user queries relate to personal life matters. Even more intriguing than our use of AI for judgment is what occurs when we let it express for us. Composition is now among the top uses for generative AI, second only to practical requests. The celebrated American author Joan Didion once remarked, “I write purely to discover what I am thinking.” What occurs when we stop composing? Do we cease discovering?

Worryingly, emerging research suggests the outcome may be yes. A study conducted by the Massachusetts Institute of Technology used electroencephalography to observe the mental engagement of essay writers who had access to AI, traditional search engines, or nothing. Those who could rely on AI showed the least cognitive engagement and had trouble quoting their own work. Perhaps most concerning was that over time, individuals in the AI group grew increasingly reliant, copying large sections of text.

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

Certainly, AI's attraction stems from 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 proposed that the appeal of authoritarianism could be partly explained by a human tendency to give up autonomy in for the sake of the reassuring certainty of subordination. AI offers a digital avenue for relinquishing the burden of having to decide for oneself.

The Black Box Problem: Trust Without Understanding

AI's primary draw is its ability to perform tasks beyond our minds – analyzing vast datasets at unprecedented speed. Stuck in the car in Marseille, this was, ultimately, why I opted to believe the machine over my companion (a decision she interpreted as an insult). With knowledge of all the data, certainly the app had superior insight – or so I believed.

The core issue is that AI is a opaque system. It generates answers, but not always fostering 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 transparent standards. So when we follow AI's recommendation, we are not being guided by reason. We are returning to the realm of faith. 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 humanity in rational inquiry. It can aid in inventing drugs, liberate us from "bullshit jobs", or handle taxes – duties that demand little thought 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. Independent thought was not merely about productivity – it was a practice of freedom and human emancipation.

Human thought is inherently messy and fallible, but it compels us to argue, to question, to challenge concepts – and to recognize the limits of our own knowledge. It fosters self-reliance, both personally and collectively. For Kant, the use of reason was never only about acquiring knowledge; it was about enabling people to become authors of their own lives, and to resist control. It was about building a moral community grounded in the common foundation of rational discourse, rather than unquestioning acceptance.

With all the undeniable benefits AI offers, the paramount challenge remains: how can we leverage its potential of advanced capability without eroding human rationality, the cornerstone of the Enlightenment and of free societies themselves? That is likely one of the defining questions of our century. It is a question we must strive not to delegate to the algorithm.