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This recent season, I found myself navigating in congested traffic on the sweltering streets of a southern French city. At an intersection, my companion in the front seat advised a right turn toward a famous spot for bouillabaisse. However, the navigation app on my phone commanded us to continue straight. Fatigued and overheated, I heeded the algorithm's directive. Minutes later, we were stranded at a construction site.

A minor event, perhaps. But one that captures a defining question of our time, where technology touches almost every aspect of existence: who gets our trust more – fellow humans and our own intuition, or the machine?

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 wrote, "is the incapacity to use one's personal reason without direction from another." For centuries, that directing force for society was often the priest, the monarch, or the feudal lord – figures claiming to channel God's voice. To explain natural events like volcanic eruptions, people sought answers in theology. In organizing the social world, from commerce to matters of the heart, religious doctrine served as the primary guide.

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

Kant argued that humans always possessed the ability to think rationally. They just didn't have the confidence to use it. With revolutions in the 18th century, a new dawn arrived: reason would replace superstition, and the human mind, freed from dogma, would become the driver of advancement and a more ethical world.

Today, 250 years later, one might wonder if we are slipping back into a form of intellectual immaturity. An app suggesting a driving route is just one example. AI risks becoming our contemporary authority – a unseen guide that influences our choices and behaviors. We are in danger of ceding the historically earned autonomy to think independently – and this time, 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 yet a global survey indicated that an vast number of respondents had used AI in the previous six months. Whether deciding on a breakup or choosing a candidate, individuals are increasingly turning to machines for counsel. Research suggests a significant portion of user queries concern non-work topics. 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 most common uses for generative AI, second only to 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?

Worryingly, emerging research suggests the outcome may be affirmative. A study from the Massachusetts Institute of Technology used electroencephalography to observe the mental engagement of participants who had access to AI, traditional search engines, or no aids. Those who could use AI showed the lowest brain activity and had difficulty quoting their own work. Perhaps most troubling was that over time, participants in the AI group became increasingly reliant, pasting large sections of text.

“Laziness and cowardice,” Kant wrote, “are the reasons why so many of men … remain in lifelong immaturity.”

Certainly, AI's appeal stems from its efficiency. It saves time, minimizes work and – importantly – offers a new method to offload responsibility. In his 1941 book, Escape from Freedom, the German psychoanalyst Erich Fromm argued that the rise of fascism could be partly explained by a preference to give up autonomy in exchange for the comforting security of subordination. AI offers a digital avenue for surrendering the burden of having to decide for oneself.

The Black Box Problem: Faith Over Reason

AI's greatest allure is its capacity to perform tasks outside human capability – sifting through vast datasets at unprecedented speed. Stuck in the car in Marseille, this was, ultimately, why I opted to trust the app over my friend (a choice she took as an affront). With knowledge of all the data, certainly the algorithm must know best – or so I believed.

The core issue is that AI is a black box. It produces answers, but not always deepening human understanding. We cannot fully grasp the process behind its conclusions – including its creators admit this. Nor can we check its reasoning 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 could be our 21st-century credo.

Using Without Losing: The Essential Challenge

AI can be a powerful tool for mankind in rational inquiry. It can help inventing drugs, liberate us from tedious tasks, or handle administrative chores – work that are repetitive and offer little satisfaction. This is beneficial. But Kant and his contemporaries did not advocate for enlightenment just so humans could optimize chores or have more leisure. Critical thinking was not merely about productivity – it was a discipline of freedom and human self-determination.

Human thought is often chaotic and error-prone, but it compels us to argue, to question, to test ideas – and to acknowledge the limits of our own knowledge. It builds self-reliance, both individually and collectively. For Kant, the use of reason was never solely about acquiring knowledge; 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 blind belief.

With all the advantages AI offers, the key question is this: how can we harness its promise of superhuman intelligence without undermining human rationality, the cornerstone of the Enlightenment and of liberal democracy itself? That is likely one of the defining questions of our time. It is a question we must strive not to outsource to the algorithm.