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This past summer, I found myself navigating in congested traffic on the scorching streets of Marseille. At a crossing, my friend in the passenger seat advised a right turn toward a renowned spot for fish soup. However, the digital guide on my phone commanded us to go forward. Fatigued and in a stifling car, I followed the algorithm's advice. Minutes later, we were stranded at a roadwork site.

A seemingly trivial incident, perhaps. But one that encapsulates a central question of our era, where technology touches almost every aspect of existence: whom do we trust more – fellow humans and our personal instincts, 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-imposed immaturity." This state, he wrote, "is the inability to use one's personal reason without direction from an external source." For ages, that guiding "other" for society was often the clergyman, the monarch, or the landowner – entities claiming to speak for divine will. To explain natural events like changing seasons, people sought answers in religion. In shaping the fabric of society, from economics to love, faith acted as the primary guide.

“Sapere aude!” or “Have courage to use your reason!”

Kant maintained that humans had the capacity for reason. They just didn't have the confidence to employ it. With upheavals in America and France, a fresh era emerged: logic would supplant blind faith, and the human mind, liberated from dogma, would become the engine of advancement and a better world.

Now, two and a half centuries later, one might question if we are slipping back into a form of dependency. An app suggesting a driving route is merely the start. AI threatens to become our contemporary authority – a silent overseer that influences our choices and behaviors. We risk ceding the historically earned courage to reason for ourselves – and this time, not to gods or kings, but to lines of code.

The Swift Adoption and Hidden Risks of Algorithmic Reliance

ChatGPT was launched a mere three years ago, and already a recent study found that an vast number of people had used AI in the previous six months. Whether contemplating a breakup or choosing a candidate, individuals are increasingly turning to algorithms for counsel. Research suggests a significant portion of user queries relate to personal life matters. Even more intriguing than our reliance on AI for judgment is what occurs when we let it speak for us. Composition is now one of the most common uses for tools like ChatGPT, second only to practical requests. The celebrated American author Joan Didion once remarked, “I write entirely to find out what I am thinking.” What transpires when we stop composing? Do we cease discovering?

Worryingly, emerging research suggests 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, Google, or nothing. Those who could use AI displayed the lowest cognitive engagement and had difficulty quoting their own work. Maybe most concerning was that over time, individuals in the AI group became increasingly reliant, copying large sections of text.

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

Certainly, AI's attraction lies in its convenience. It is fast, minimizes work and – importantly – offers a novel way to offload accountability. In his 1941 book, Escape from Freedom, the German psychoanalyst Erich Fromm proposed that the rise of fascism could be partly explained by a preference to give up personal freedom in exchange for the reassuring certainty of subordination. AI presents a digital avenue for relinquishing the weight of having to decide for oneself.

The Opacity Dilemma: Faith Over Reason

AI's greatest allure is its capacity to accomplish things outside human capability – analyzing oceans of data at unprecedented speed. Sitting in the car in Marseille, this was, ultimately, why I opted to trust the machine over my friend (a choice she interpreted as an insult). With access to all the data, surely the algorithm must know best – or so I believed.

The fundamental problem is that AI operates as a black box. It produces answers, but without necessarily fostering human comprehension. We do not truly know the process behind its decisions – even its creators acknowledge the opacity. Nor can we check its logic against transparent standards. So when we follow AI's advice, we are not being led by logic. We are returning to the realm of faith. In dubio pro machina: when in doubt, trust the machine – that may become our future guiding principle.

Harnessing Without Eroding: The Critical Balance

AI can be a formidable ally for mankind in scientific pursuit. It can aid in medical research, liberate us from "bullshit jobs", or manage administrative chores – duties that demand little thought and offer little satisfaction. All to the good. But Kant and his contemporaries did not champion reason over faith just so humans could optimize chores or have extra free time. Independent thought was not just about efficiency – it was a practice of freedom and human emancipation.

Human thought is often chaotic and error-prone, but it compels us to debate, to doubt, to challenge concepts – and to recognize the limits of our own knowledge. It builds confidence, both individually and collectively. For Kant, the exercise of reason was never solely about information; it was about enabling people to become agents of their own destinies, and to oppose control. It was about building a ethical society based on the common foundation of reason and debate, rather than unquestioning acceptance.

With all the advantages AI brings, the key question is this: how can we harness its promise of advanced capability without eroding human rationality, the bedrock of the Enlightenment and of free societies itself? That is likely one of the central dilemmas of our century. It is a question we would do well not to outsource to the machine.