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This past summer, I found myself navigating in gridlocked traffic on the scorching streets of Marseille. At an intersection, my friend in the passenger seat advised a right turn toward a renowned spot for bouillabaisse. However, the navigation app on my phone commanded us to go forward. Fatigued and in a stifling car, I followed the app's directive. Moments later, we were stuck at a roadwork site.

A minor event, maybe. But one that encapsulates a defining question of our era, where digital tools touches almost every aspect of existence: who gets our trust more – fellow humans and our own intuition, or the algorithm?

A Call for Intellectual Maturity and A Contemporary Backslide

The renowned German philosopher Immanuel Kant once defined the Enlightenment as "humanity's emergence from its self-inflicted immaturity." This state, he argued, "is the incapacity to use one's personal reason without guidance from another." For centuries, that guiding "other" for society was frequently the priest, the monarch, or the feudal lord – figures purporting 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, faith served as the primary guide.

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

Kant argued that humans always possessed the capacity for reason. They simply lacked the boldness to use it. With revolutions in the 18th century, a fresh era emerged: logic would supplant blind faith, and the intellect, liberated from authority, would become the driver of advancement and a more ethical world.

Now, two and a half centuries later, one might wonder if we are quietly regressing into a state of dependency. An app suggesting a driving route is just one example. AI risks becoming our new "other" – a unseen overseer that steers our choices and actions. We risk relinquishing the hard-won autonomy to think independently – and this time, not to deities or rulers, but to lines of code.

The Rapid Rise and Subtle Dangers of AI Dependence

ChatGPT was launched only in 2022, and already a recent study indicated that an vast number of people had engaged with artificial intelligence in the previous six months. Whether contemplating a breakup or choosing a candidate, individuals are looking to machines for counsel. Data suggests a large majority of user prompts concern non-work topics. Even more intriguing than our reliance on AI for advice is what occurs when we allow it express for us. Writing is now one of the most common uses for generative AI, second only to everyday tasks. The late American author Joan Didion once remarked, “I write purely to discover what I am thinking.” What transpires when we stop composing? Do we cease discovering?

Worryingly, some evidence hints the answer may be yes. A study conducted by the Massachusetts Institute of Technology used brain monitoring to observe the mental engagement of participants who had could use AI, Google, or nothing. Those who could rely on AI displayed the lowest cognitive engagement and had trouble accurately recalling their own work. Maybe most concerning was that after a few months, participants in the AI group grew progressively lazier, pasting large sections of text.

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

Certainly, AI's attraction stems from its convenience. It saves time, minimizes work and – critically – offers a new method to offload responsibility. In his 1941 book, Escape from Freedom, the German psychoanalyst Erich Fromm proposed that the rise of fascism could be partly explained by a human tendency to surrender autonomy in exchange for the reassuring certainty of subordination. AI offers a digital avenue for surrendering the weight of having to think and choose.

The Black Box Problem: Trust Without Understanding

AI's primary draw is its ability to perform tasks beyond human capability – analyzing vast datasets at lightning pace. Sitting in the car in Marseille, this was, after all, why I chose to believe the app over my companion (a decision she interpreted as an insult). With knowledge of real-time information, certainly the algorithm must know best – or so I believed.

The core issue is that AI operates as a opaque system. It produces answers, but without necessarily fostering human comprehension. We cannot fully grasp the process behind its conclusions – including its programmers admit this. Nor can we check its logic 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 21st-century guiding principle.

Using Without Losing: The Critical Balance

AI can be a formidable ally for humanity in rational inquiry. It can help medical research, free us from tedious tasks, or handle administrative chores – work that are repetitive and are unfulfilling. This is beneficial. But Kant and his peers did not champion enlightenment just so humans could assemble better furniture or have extra free time. Independent thought was not just about efficiency – it was a discipline of freedom and human emancipation.

Human thought is often chaotic and fallible, but it compels us to debate, to doubt, to test ideas – and to acknowledge the limits of our own understanding. It fosters self-reliance, both personally and as a society. For Kant, the exercise of reason was never solely about acquiring knowledge; it was about empowering people to become agents of their own destinies, and to resist control. It was about creating a moral community grounded in the shared principle of reason and debate, rather than blind belief.

With all the advantages AI brings, the paramount challenge remains: how can we harness its promise of advanced capability without eroding human reasoning, the bedrock of the Enlightenment and of liberal democracy themselves? That is likely one of the central dilemmas of our time. It is a question we would do well not to outsource to the algorithm.