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This recent season, I was caught in gridlocked traffic on the scorching streets of a southern French city. At an intersection, my companion in the passenger seat suggested a right turn toward a famous spot for fish soup. However, 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 roadwork site.

A minor event, perhaps. But one that captures a defining question of our era, where technology permeates nearly every facet of existence: who gets our trust to a greater degree – fellow humans and our personal instincts, or the algorithm?

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 nonage." This state, he wrote, "is the inability to use one's personal reason without guidance from an external source." For ages, that directing force for society was frequently the clergyman, the king, or the feudal lord – entities purporting to speak for divine will. To explain phenomena like volcanic eruptions, people looked for explanations 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 capacity for reason. They just didn't have the boldness to employ it. With upheavals in the 18th century, a fresh era emerged: logic would supplant superstition, and the human mind, freed from authority, would become the driver of advancement and a better world.

Today, two and a half centuries later, one might question if we are slipping back into a state of intellectual immaturity. An app dictating a driving route is merely the start. Artificial intelligence risks becoming our new "other" – a unseen guide that steers our choices and behaviors. We are in danger of relinquishing the hard-won autonomy to think independently – and this time, not to gods or kings, but to lines of code.

The Swift Adoption and Hidden Risks of AI Dependence

ChatGPT debuted a mere three years ago, and already a global survey found that an vast number of respondents had used AI in the previous six months. Whether deciding on a breakup or selecting a vote, individuals are looking to machines for guidance. Data suggests a significant portion of user prompts relate to non-work topics. Even more striking than our use of AI for advice is what occurs when we let it speak for us. Composition is now one of the most common uses for generative AI, just behind 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?

Alarmingly, emerging research suggests the answer may be affirmative. A study from the Massachusetts Institute of Technology used brain monitoring to track the mental engagement of essay writers who had access to AI, Google, or no aids. Those who could rely on AI displayed the lowest brain activity and had trouble accurately recalling their own work. Perhaps most concerning was that after a few months, participants in the AI group grew increasingly reliant, copying entire blocks of text.

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

Of course, AI's appeal stems from its efficiency. It saves time, minimizes work and – critically – offers a new method to abdicate accountability. In his 1941 book, Escape from Freedom, the German psychoanalyst Erich Fromm argued that the rise of fascism could be understood by a human tendency to surrender personal freedom in exchange for the reassuring certainty 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 perform tasks beyond our minds – sifting through oceans of data at unprecedented speed. Sitting in the car in Marseille, this was, after all, why I opted to believe the machine over my friend (a choice she took as an insult). With access to real-time information, surely the app must know best – or so I thought.

The fundamental problem is that AI operates as a black box. It produces answers, but not always deepening human understanding. We cannot fully grasp the process behind its conclusions – even its programmers admit this. Nor can we check its logic against clear, objective criteria. So when we follow AI's advice, we are not being guided by reason. We are returning to the realm 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 rational inquiry. It can help medical research, liberate us from tedious tasks, or handle administrative chores – work that demand little thought and are unfulfilling. This is beneficial. But Kant and his contemporaries did not champion enlightenment just so humans could optimize chores or have extra free time. Independent thought was not merely about efficiency – it was a discipline of freedom and human self-determination.

Human thought is inherently messy and error-prone, but it compels us to argue, to question, to test ideas – and to acknowledge the boundaries of our own knowledge. 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 authors of their own destinies, and to oppose control. It was about creating a ethical society based on the shared principle of reason and debate, rather than unquestioning acceptance.

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