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This recent season, I found myself navigating in congested traffic on the scorching streets of Marseille. At an intersection, my companion in the front seat advised a right turn toward a famous spot for fish soup. Yet, the digital guide on my phone commanded us to go forward. Weary and in a stifling car, I followed the algorithm's advice. Moments later, we were stuck at a construction site.

A minor incident, maybe. But one that captures a defining question of our time, where digital tools touches almost every aspect of our lives: whom do we trust to a greater degree – fellow humans and our personal instincts, or the algorithm?

A Call for Intellectual Maturity and A Contemporary Backslide

The influential German philosopher Immanuel Kant famously described the Enlightenment as "man's release from its self-imposed immaturity." This immaturity, he wrote, "represents the inability to use one's own understanding without direction from another." For centuries, that guiding "other" for society was frequently the priest, the monarch, or the landowner – entities claiming to speak for divine will. To comprehend natural events like changing seasons, people looked for explanations in theology. In organizing the fabric of society, from economics to matters of the heart, religious doctrine served as the primary guide.

“Sapere aude!” or “Dare to use your reason!”

Kant maintained that humans had the ability to think rationally. They just didn't have the confidence to employ it. With revolutions in America and France, a fresh era arrived: logic would supplant superstition, and the intellect, freed from authority, would become the engine of progress 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 direction is just one example. AI threatens to become our new "other" – a unseen guide that steers our decisions and behaviors. We risk relinquishing the hard-won courage to think independently – and now, not to deities or rulers, but to computer programs.

The Swift Adoption and Hidden Risks of Algorithmic Reliance

ChatGPT debuted a mere three years ago, and already a global survey indicated 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 algorithms for counsel. Data suggests a significant portion of user prompts relate to non-work topics. Even more intriguing than our use of AI for judgment is what happens when we allow it speak for us. Composition is now one of the top uses for tools like ChatGPT, just behind practical requests. The celebrated American author Joan Didion famously said, “I write purely to discover what I am thinking.” What occurs when we stop composing? Do we lose that path?

Alarmingly, some evidence hints the answer may be affirmative. A study from the Massachusetts Institute of Technology used electroencephalography to observe the cognitive activity of participants who had access to AI, traditional search engines, or no aids. Those who could rely on AI showed the lowest brain activity and had trouble quoting their own work. Perhaps most concerning was that after a few months, individuals in the AI group grew progressively lazier, copying large sections of text.

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

Certainly, AI's appeal 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 argued that the appeal of authoritarianism could be partly explained by a human tendency to give up personal freedom in for the sake of the reassuring certainty of obedience. AI presents a modern method of surrendering the burden of having to decide for oneself.

The Opacity Dilemma: Faith Over Reason

AI's primary draw is its capacity to perform tasks outside human capability – sifting through vast datasets at unprecedented speed. Sitting in the car in Marseille, this was, ultimately, why I opted to trust the app over my companion (a decision she took as an insult). With access to all the data, certainly the algorithm had superior insight – or so I believed.

The core issue is that AI operates as a black box. It generates answers, but not always deepening human understanding. We cannot fully grasp how AI reaches its decisions – including its programmers admit this. Nor can we verify its reasoning against clear, objective criteria. 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, side with the machine – that could be our future guiding principle.

Using Without Losing: The Critical Balance

AI can be a formidable ally for mankind in scientific pursuit. It can aid in inventing drugs, liberate us from "bullshit jobs", or handle taxes – work that demand little thought and offer little satisfaction. All to the good. But Kant and his peers did not advocate for enlightenment just so humans could optimize chores or have more leisure. Independent thought was not merely about productivity – it was a discipline of liberty and human emancipation.

Human thought is often chaotic and error-prone, but it compels us to argue, to doubt, to challenge concepts – and to recognize the boundaries of our own knowledge. It fosters self-reliance, both personally and as a society. For Kant, the exercise of reason was never solely about information; it was about enabling people to become authors of their own destinies, and to resist control. It was about creating a ethical society grounded in the shared principle of rational discourse, rather than blind belief.

With all the undeniable benefits AI offers, the paramount challenge remains: how can we harness its promise of advanced capability without undermining human rationality, the cornerstone of the Enlightenment and of liberal democracy themselves? That may be one of the defining questions of our time. It is a question we must strive not to outsource to the algorithm.