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This past summer, I was caught in gridlocked traffic on the scorching streets of Marseille. At a crossing, my companion in the passenger seat advised a right turn toward a renowned spot for fish soup. However, the navigation app on my phone commanded us to continue straight. Fatigued and overheated, I heeded the app's directive. Minutes later, we were stuck at a roadwork site.

A seemingly trivial incident, perhaps. But one that encapsulates a central question of our time, 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 Our Modern Relapse

The renowned German philosopher Immanuel Kant once defined the Enlightenment as "humanity's emergence from its self-inflicted immaturity." This immaturity, he wrote, "is the incapacity to use one's personal reason without guidance from an external source." For centuries, that guiding "other" for human thought was often the clergyman, the king, or the landowner – entities purporting to channel divine will. To comprehend phenomena like changing seasons, people looked for explanations in religion. In organizing the social world, from economics to love, faith acted as the main compass.

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

Kant maintained that humans always possessed the ability to think rationally. They simply lacked the confidence to use it. With upheavals in the 18th century, a new dawn arrived: logic would replace superstition, and the intellect, liberated from authority, would become the engine of progress and a better world.

Now, 250 years later, one might question if we are quietly regressing into a form of intellectual immaturity. An app suggesting a direction is merely the start. AI threatens to become our contemporary authority – a silent overseer that steers our choices and behaviors. We risk ceding the hard-won courage to think independently – and now, not to gods or kings, but to lines of code.

The Swift Adoption and Subtle Dangers of Algorithmic Reliance

ChatGPT was launched a mere three years ago, and already a recent study found that an overwhelming majority 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 guidance. Research suggests a significant portion of user prompts relate to personal life matters. Even more intriguing than our reliance on AI for advice is what happens when we allow it express for us. Composition is now among the top uses for generative AI, second only to practical requests. The late American author Joan Didion once remarked, “I write purely to find out what I am thinking.” What transpires when we cease writing? Do we cease discovering?

Worryingly, some evidence 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, traditional search engines, or no aids. Those who could rely on AI displayed the least cognitive engagement and had trouble accurately recalling their own work. Maybe most troubling was that after a few months, participants in the AI group grew progressively lazier, pasting large sections of text.

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

Certainly, AI's appeal lies in its efficiency. It saves time, reduces effort and – critically – offers a new method to offload responsibility. In his 1941 book, Escape from Freedom, the German psychoanalyst Erich Fromm proposed that the rise of fascism could be understood by a preference to give up autonomy in for the sake of the comforting security of subordination. AI offers a modern avenue for relinquishing the burden of having to decide for oneself.

The Opacity Dilemma: Trust Without Understanding

AI's greatest allure is its ability to accomplish things outside our minds – sifting through vast datasets at lightning pace. Stuck in the car in Marseille, this was, after all, why I chose to trust the app over my friend (a decision she took as an affront). With access to real-time information, certainly the algorithm must know best – or so I believed.

The fundamental problem is that AI is a black box. It produces answers, but without necessarily fostering human comprehension. We cannot fully grasp the process behind its decisions – including its programmers acknowledge the opacity. Nor can we verify its logic 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 21st-century guiding principle.

Harnessing Without Eroding: The Essential Challenge

AI can be a formidable ally for humanity in rational inquiry. It can help inventing drugs, free us from tedious tasks, or manage administrative chores – work 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. Independent thought was not just about efficiency – it was a discipline of freedom and human emancipation.

Human thought is often chaotic and fallible, but it compels us to debate, to question, to challenge concepts – and to recognize the limits of our own understanding. It builds self-reliance, both individually and collectively. For Kant, the exercise of reason was never solely about information; it was about empowering people to become agents of their own lives, and to resist control. It was about building a ethical society based on the shared principle of rational discourse, 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 bedrock of the Enlightenment and of free societies itself? That may be one of the defining questions of our time. It is a question we would do well not to delegate to the algorithm.