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This past summer, I found myself navigating in congested traffic on the scorching streets of a southern French city. At a crossing, my companion in the passenger seat advised a right turn toward a famous spot for fish soup. Yet, the digital guide on my phone commanded us to go forward. Fatigued and in a stifling car, I heeded the algorithm's directive. Minutes later, we were stranded at a construction site.

A minor incident, maybe. But one that captures a defining question of our time, where digital tools permeates almost every aspect of existence: who gets our trust to a greater degree – fellow humans and our own intuition, or the algorithm?

The Enlightenment's Promise and Our Modern Relapse

The influential German philosopher Immanuel Kant famously described the Enlightenment as "humanity's emergence from its self-imposed nonage." This immaturity, he argued, "represents the inability to use one's own understanding without direction from an external source." For centuries, that directing force for human thought was frequently the priest, the king, or the feudal lord – figures claiming to channel God's voice. To comprehend natural events like changing seasons, people looked for explanations in theology. In shaping the fabric of society, from economics to love, religious doctrine acted as the main compass.

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

Kant argued that humans had the capacity for reason. They just didn't have the confidence to employ it. With revolutions in the 18th century, a new dawn emerged: reason would supplant blind faith, and the human mind, freed from authority, would become the engine of advancement and a more ethical world.

Now, two and a half centuries later, one might question if we are quietly regressing into a form of dependency. An app suggesting a direction is just one example. AI threatens to become our new "other" – a silent guide that steers our choices and actions. We risk ceding the historically earned courage to think independently – and now, not to deities or rulers, but to lines of code.

The Rapid Rise 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 respondents had used AI in the previous six months. Whether deciding on a breakup or choosing a candidate, individuals are increasingly turning to algorithms for guidance. Research suggests a significant portion of user queries concern personal life matters. Even more intriguing than our reliance on AI for judgment is what occurs when we let it speak for us. Writing is now among the most common uses for generative AI, just behind practical requests. The late American author Joan Didion famously said, “I write entirely to discover what I am thinking.” What transpires when we cease writing? Do we lose that path?

Alarmingly, emerging research suggests the outcome may be yes. A study from the Massachusetts Institute of Technology used electroencephalography to observe the mental engagement of essay writers who had access to AI, Google, or no aids. Those who could rely on AI displayed the least brain activity and had trouble quoting their own work. Perhaps most troubling was that after a few months, participants in the AI group became progressively lazier, pasting 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 appeal stems from its convenience. It is fast, reduces effort and – critically – offers a novel way to abdicate 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 personal freedom in exchange for the reassuring certainty of obedience. AI presents a modern method of surrendering the weight of having to think and choose.

The Opacity Dilemma: Faith Over Reason

AI's primary draw is its capacity to perform tasks beyond human capability – sifting through vast datasets at lightning pace. Sitting in the car in Marseille, this was, ultimately, why I opted to trust the machine over my companion (a choice she took as an insult). With knowledge of all the data, surely the algorithm must know best – or so I thought.

The fundamental problem is that AI operates as a black box. It produces knowledge, but not always fostering human comprehension. We do not truly know how AI reaches its decisions – even its programmers acknowledge the opacity. Nor can we verify its reasoning against clear, objective criteria. So when we heed AI's recommendation, we are not being led by logic. We are back in the realm of belief. In dubio pro machina: when in doubt, side with the machine – that may become our future guiding principle.

Using Without Losing: The Essential Challenge

AI can be a formidable ally for humanity in scientific pursuit. It can aid in medical research, liberate us from tedious tasks, or handle taxes – work that are repetitive and are unfulfilling. 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 merely about productivity – it was a discipline of freedom and human emancipation.

Human thought is often chaotic and error-prone, but it forces us to argue, to question, to test ideas – and to acknowledge the limits of our own knowledge. It fosters confidence, both personally and as a society. For Kant, the use of reason was never only about acquiring knowledge; it was about enabling people to become agents of their own destinies, and to resist domination. It was about creating a ethical society grounded in the shared principle of rational discourse, rather than unquestioning acceptance.

With all the advantages AI brings, the paramount challenge remains: how can we leverage its promise of superhuman intelligence without eroding human reasoning, the bedrock of the Enlightenment and of liberal democracy itself? That is likely one of the central dilemmas of our time. It is a question we must strive not to delegate to the algorithm.