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This recent season, I found myself navigating in congested traffic on the sweltering streets of Marseille. At a crossing, my friend in the front seat advised a right turn toward a famous spot for fish soup. However, the navigation app on my phone commanded us to go forward. Fatigued and overheated, I heeded the app's directive. Minutes later, we were stuck at a construction site.

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

The Enlightenment's Promise and A Contemporary Backslide

The influential German philosopher Immanuel Kant once defined the Enlightenment as "humanity's emergence from its self-imposed immaturity." This immaturity, he argued, "represents the incapacity to use one's personal reason without guidance from an external source." For centuries, that directing force for society was frequently the clergyman, the king, or the feudal lord – entities purporting to speak for God's voice. To explain phenomena like volcanic eruptions, people sought answers in theology. In organizing the social world, from economics to love, religious doctrine acted as the primary guide.

“Sapere aude!” or “Have courage to use your own understanding!”

Kant maintained that humans always possessed the capacity for reason. They just didn't have the boldness to employ it. With upheavals in the 18th century, a new dawn emerged: reason would replace superstition, and the human mind, freed from authority, would become the driver of advancement and a more ethical world.

Today, two and a half centuries later, one might wonder if we are slipping back into a form of dependency. An app dictating a driving route is merely the start. AI threatens to become our new "other" – a unseen guide that steers our choices 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 Swift Adoption and Subtle Dangers of AI Dependence

ChatGPT was launched only in 2022, and already 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 selecting a vote, individuals are increasingly turning to machines for counsel. Research suggests a significant portion of user prompts concern non-work topics. Even more striking than our use of AI for judgment is what happens when we allow it express for us. Writing is now one of the top uses for tools like ChatGPT, second only to everyday tasks. The late American author Joan Didion famously said, “I write purely to find out what I am thinking.” What occurs when we stop composing? Do we lose that path?

Worryingly, emerging research hints the answer may be yes. A study from the Massachusetts Institute of Technology used brain monitoring to track the cognitive activity of essay writers who had could use AI, Google, or nothing. Those who could use AI displayed the lowest cognitive engagement and had trouble accurately recalling their own work. Maybe most concerning was that over time, individuals in the AI group became progressively lazier, copying 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 saves time, minimizes work and – importantly – offers a new method to offload 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 preference to surrender autonomy in exchange for the comforting security of subordination. AI offers a digital avenue for relinquishing the burden of having to decide for oneself.

The Opacity Dilemma: Faith Over Reason

AI's primary draw is its capacity to accomplish things beyond human capability – analyzing oceans of data at unprecedented speed. Stuck in the car in Marseille, this was, after all, why I chose to believe the machine over my friend (a decision she took as an insult). With access to all the data, surely the app had superior insight – or so I believed.

The fundamental problem is that AI is a opaque system. It produces answers, but without necessarily fostering human understanding. We do not truly know the process behind its decisions – even its programmers admit this. Nor can we check its logic against transparent standards. So when we heed AI's recommendation, we are not being guided by reason. We are back in the domain of belief. In dubio pro machina: when in doubt, trust the machine – that could be our future credo.

Harnessing Without Eroding: The Essential Challenge

AI can be a formidable ally for mankind in scientific pursuit. It can help inventing drugs, liberate us from tedious tasks, or handle administrative chores – duties that demand little thought and offer little satisfaction. This is beneficial. 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 just about productivity – it was a discipline of liberty and human self-determination.

Human thought is inherently messy and error-prone, but it compels us to debate, to question, to challenge concepts – and to acknowledge the limits of our own knowledge. It fosters confidence, both individually and collectively. For Kant, the exercise 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 creating a moral community based on the shared principle of reason and debate, rather than unquestioning acceptance.

With all the undeniable benefits AI brings, the key question is this: how can we leverage its potential of advanced capability without eroding human rationality, the cornerstone of the Enlightenment and of liberal democracy itself? That is likely one of the defining questions of our time. It is a question we would do well not to delegate to the algorithm.